Post on 10-Jun-2020
INVESTIGATING THE ROLE OF
KNOWLEDGE MANAGEMENT AT VARIOUS
LEVELS OF PROJECT MANAGEMENT
OFFICE
SHAHRAM SOKHANVAR
MSc of Socio-Economic Systems Engineering (IRPD-Iran)
BSc of Economics (Shahid Beheshty University-Iran)
Certified Program and Portfolio Management (Microsoft-USA)
Project Management Professional (PMI- USA)
Microsoft Certified Technologies (Microsoft-USA)
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
Science and Engineering Faculty
Queensland University of Technology
2015
Investigating the Role of Knowledge Management at Various levels of Project Management Office i
ii Investigating the Role of Knowledge Management at Various levels of Project Management Office
To my beloved Mum, Akram
My dad, my Hero, who I sadly lost
My lovely family members, and
Without whom none of success would be possible.
Investigating the Role of Knowledge Management at Various levels of Project Management Office iii
iv Investigating the Role of Knowledge Management at Various levels of Project Management Office
KEYWORDS
Investigating the Role of Knowledge Management at Various levels of Project Management Office v
LIST OF PUBLICATION AND PAPERS
1) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The Required
Types of Project Knowledge in Various Maturity Levels of Project Management
Office, The Journal of Project Management, Status : Submitted
2) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The Challenges of
Project Management Office from Knowledge Management Perspective, The
International Journal of Project Management, Status : Submitted
3) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), Management of
Project Knowledge in a Project-based Organisation: A Theoretical Framework, The
2014 PMI® Research and Education Conference, 27th -29th July 2014, Portland
Marriott Waterfront, Portland, Oregon, USA.
4) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), Management of
Project Knowledge in a Project-based Organisation: a Case Study of Mining
Industry, The 2014 International Conference Knowledge Engineering- IKE14, 21st -
24th July 2014, Monte Carlo Resort, Las Vegas, Nevada, USA.
5) Shahram Sokhanvar, Bambang Trigunarsyah, Prasad Yarlagadda (2014), Project
Knowledge Management in PMOs, Book Chapter, Cambridge Scholar Publishing,
under publishing process.
6) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), Management of
Project Knowledge in a Project-based Organisation: a Case Study of Research
Enterprise, 15th European Conference on Knowledge Management, 4th -5th
September 2014, The Santarém School of Management and Technology, Santarém,
Portugal.
7) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The importance of
Knowledge Management Processes in a Project-based organization: a Case Study of
Research Enterprise, 12th Global Congress on Manufacturing And Management-
GCMM, 8th -10th December-2014, School of Mechanical and Building Sciences, VIT
University, in Association with Queensland University Of Technology, Tamil Nadu,
India.
8) Shahram Sokhanvar, Bambang Trigunarsyah, Prasad Yarlagadda (2011), The role of
knowledge in the project management office, 25th International Project Management
vi Investigating the Role of Knowledge Management at Various levels of Project Management Office
Association (IPMA) Proceeding Conference, 9th -13th October 2011, Brisbane
Convention and Exhibition Centre, Brisbane, QLD, Australia.
ABSTRACT
Organisations undertake projects to achieve diverse objectives such as operational efficiency,
technological enhancement, customer satisfaction, service improvement, and organisational
development. Project management (PM) is the application of knowledge, skills, tools, and
techniques to meet project objectives. Project management practices are essential to both ensure
the efficiency and effectiveness of projects, and also achieve quality outcomes. In addition,
project Knowledge Management (KM) is an important factor in improving the quality of a
project, and increasing its success rate. In other words, knowledge management practices not
only increase the quality of project outputs, but also, they resolve some of project management
challenges such as loss of knowledge and the need for rework.
Larger organisations often establish a Project Management Office or PMO, an organisational
department or unit, to both develop project management practices, and also oversee as well as
control organisational projects. The Project Management Maturity Model, or PMMM, addresses
the development of the project management office, from immature to mature levels, through the
recommendation of numbers of practices, and criteria in the various levels. Theoretically, the
project management office is responsible for providing and maintaining knowledge
management practices. Hence, project management maturity models should address the
development of knowledge management within the project management office. In other words,
the PM maturity models should guide how a project management office could be improved
from a knowledge management perspective. However, little research has been carried out to
indicate the relationship between a Project Management Maturity Model and Knowledge
Management. In other words, the absence of knowledge management practices in the current
PM maturity model is obvious in the existing literature.
This study aims to investigate Knowledge Management practices in the current Project
Management Maturity Models through: A) analysing the role of knowledge management
practices in various maturity levels of the PMO, B) exploring the contribution(s) of the PMO for
managing project knowledge, and C) developing a framework to address knowledge
management practices in various maturity levels of the PMO. In order to meet the research
objectives, three research questions have been defined: 1) To what extent are knowledge
management processes and practices employed in the PMOs, 2) How do knowledge
management practices contribute to maturity level of PMO, and 3) How can knowledge be
integrated in the PM Maturity Model. The ultimate objective of this research is to develop a
Investigating the Role of Knowledge Management at Various levels of Project Management Office vii
framework to address four knowledge management processes, i.e. capturing; creation;
transferring; and reusing, in five maturity levels of the Project Management Office.
An extensive literature review was undertaken to understand the current debates regarding
project management and its related methodology, project management office and project
management PM maturity models, and knowledge management in functional and project-based
organisations. This endeavour resulted in the development of the preliminary research
framework to determine the scope of the study. This developed framework comprises three
major elements: 1) knowledge management processes, sub processes and practices in the
project-based environments, 2) a project management maturity model to assist the development
of project management office, 3) a knowledge management maturity model to address the
development of knowledge management in the project management office.
Due to the exploratory and inductive nature of this research, a qualitative approach and
multiple case study methods were adopted. Cases were chosen on the basis of theoretical
sampling of large enterprises with a project management office in their structure and three
distinct organisations were chosen as the research case studies. Data collection using research
questions, derived from the proposed research framework, was carried out through interviews
with senior managers, project managers, and project and PMO staff. Further data from
workplace observations and document analysis were gathered. All data were analysed to both
examine the research framework, and develop number of emerging propositions and
recommendations. A range of analytical techniques, such as grounded theory and pattern
matching, were employed to work with the collected data, alongside the Nvivo for data
management.
The research findings concluded that there is a significant relation between the maturity level
of the project management office, and the utilised knowledge management practices. This
means that a project management office with higher maturity level has more effective project
knowledge management. In addition, knowledge capturing is the most important knowledge
management process, while knowledge reusing is the least important knowledge management
process in various maturity levels of the project management office. This means that the project
management office’s first priority is to capture project knowledge, then knowledge creation,
transferring, and finally reusing. For instance, the research findings revealed that for developing
knowledge capturing in a project management office with first level of maturity, two basic sub-
processes of knowledge storing and classification will be considered through addressing some
knowledge management practices, such as document management systems and databases.
Furthermore, the research findings revealed that the type of project management office is
another factor in determining the priority of knowledge management development. For instance,
in a PMO as the centre of excellence, knowledge transferring is the second most important KM
viii Investigating the Role of Knowledge Management at Various levels of Project Management Office
process, while in a practical PMO, knowledge creation is prioritised before knowledge
transferring. In addition, according to the current literature, only a knowledge capturing process
should be employed in the closing phase, however, the research findings have explored some
challenges in this regard. In other words, it was revealed that in the closing phase, some
knowledge transferring practices are used in PMO with higher maturity levels. So it could be
proposed that in a PMO with a higher maturity level, knowledge transferring practices should be
employed, accordingly.
Also, the research findings explored the level of maturity impacts on types of knowledge
management challenges. In a PMO with low maturity level, the majority of challenges related to
the existing knowledge management systems and applications, while in a PMO with higher
maturity level, the PMO is faced with more advanced challenges, such as absence of knowledge
management practices for knowledge reusing and transferring, and integration of the existing
applications with knowledge management practices.
This research contributes to literature in project management, specifically the Project
Management Office, through integrating Knowledge Management practices in Project
Management Maturity models. The developed framework addresses the recognised gap by
recommending appropriate knowledge management processes, and practices in various maturity
levels of the Project Management Office. In addition, the research outcomes propose numbers
of criteria to assess the maturity levels of the Project Management Office, from a knowledge
management point of view. This study is the first attempt to discuss the maturity of the Project
Management Office from a knowledge management perspective, and it develops a new direction
in the literature of Project Management Maturity Models.
Investigating the Role of Knowledge Management at Various levels of Project Management Office ix
TABLE OF CONTENTS
Keywords ............................................................................................................................................... iv List of Publication and Papers ................................................................................................................ v Abstract .................................................................................................................................................. vi Table of Contents ................................................................................................................................... ix List of Figures ....................................................................................................................................... xiv List of Tables ....................................................................................................................................... xvii List of Abbreviations ............................................................................................................................. xx Statement of Original Authorship ......................................................................................................... xxi Acknowledgements .............................................................................................................................. xxii
INTRODUCTION .................................................................................................. 1 CHAPTER 1
Research background ................................................................................................................... 1 1.1
Problem statement ....................................................................................................................... 3 1.2
Research Aim and Objective ....................................................................................................... 4 1.3
Research questions ...................................................................................................................... 4 1.4
Research approach ....................................................................................................................... 4 1.5
Thesis structure ............................................................................................................................ 5 1.6
LITERATURE REVIEW ....................................................................................... 7 CHAPTER 2
Introduction ................................................................................................................................. 7 2.1
The notion of knowledge and knowledge management............................................................... 7 2.2
Knowledge management frameworks .............................................................................. 8 2.2.1
The evolution of Project Management....................................................................................... 11 2.3
Project and Project Management .................................................................................... 11 2.3.1
Project In Controlled Environment (PRINCE2) ............................................................. 12 2.3.2
Project Management Body of Knowledge (PMBOK) .................................................... 14 2.3.3
The Project Management Office (PMO) ........................................................................ 15 2.3.4
Taxonomies of knowledge ............................................................................................. 18 2.3.5
The Project Management Maturity Models .................................................................... 20 2.3.6
Conclusion ...................................................................................................................... 22 2.3.7
Knowledge management in project-based organisations ........................................................... 23 2.4
Type of Knowledge and KM in Project-based Organisations ........................................ 24 2.4.1
A succinct summary of the existing KM discussion in PBO .......................................... 25 2.4.2
Challenges of knowledge management in project environments ................................... 28 2.4.3
The Research Problem ............................................................................................................... 29 2.5
Problem Definition ......................................................................................................... 29 2.5.1
The Research Aim .......................................................................................................... 31 2.5.2
The Significance of Research ......................................................................................... 32 2.5.3
The Research Questions ................................................................................................. 32 2.5.4
x Investigating the Role of Knowledge Management at Various levels of Project Management Office
The Research Objectives ................................................................................................ 33 2.5.5
The Research limitations ................................................................................................ 33 2.5.6
The Research Purposes ................................................................................................... 34 2.5.7
Conclusion ................................................................................................................................. 34 2.6
THE CONCEPTUAL FRAMEWORK ................................................................ 36 CHAPTER 3
Introduction................................................................................................................................ 36 3.1
Theoretical Background ............................................................................................................. 36 3.2
Knowledge management processes in project environments ......................................... 36 3.2.1
Knowledge management processes in project lifecycle ................................................. 37 3.2.2
Tacit and explicit dimensions of knowledge at project environment ............................. 38 3.2.3
PMBOK and knowledge management ........................................................................... 39 3.2.4
Methods of transforming Tacit to Explicit knowledge ................................................... 40 3.2.5
Project management maturity model .............................................................................. 41 3.2.6
Knowledge Management Maturity Model ...................................................................... 42 3.2.7
Conceptual Framework Premises .............................................................................................. 47 3.3
Types of the required knowledge ................................................................................... 47 3.3.1
Knowledge Management Processes in PMOs ................................................................ 48 3.3.2
Project management maturity model .............................................................................. 51 3.3.3
Knowledge management maturity model ....................................................................... 52 3.3.4
Conclusion ................................................................................................................................. 52 3.4
RESEARCH DESIGN .......................................................................................... 55 CHAPTER 4
Introduction................................................................................................................................ 55 4.1
A snapshot of research flow ....................................................................................................... 55 4.2
Epistemological and philosophical position of this research ..................................................... 55 4.3
Research Method ....................................................................................................................... 57 4.4
The Rationale for selection of case study ....................................................................... 57 4.4.1
Research Design ........................................................................................................................ 58 4.5
The structure of the research design ............................................................................... 59 4.5.1
Research method implementation .............................................................................................. 61 4.6
Selection of Case studies ................................................................................................ 61 4.6.1
Case study protocol ........................................................................................................ 62 4.6.2
Data collection implementation ................................................................................................. 62 4.7
Interviews ....................................................................................................................... 62 4.7.1
Survey questionnaire ...................................................................................................... 64 4.7.2
Direct observation .......................................................................................................... 64 4.7.3
Documentations analysis ................................................................................................ 64 4.7.4
Data analysis .............................................................................................................................. 65 4.8
Grounded theory as inductive theory building method ................................................... 65 4.8.1
Data analysis processes .................................................................................................. 66 4.8.2
Data organisation ............................................................................................................ 66 4.8.3
Data display .................................................................................................................... 67 4.8.4
Investigating the Role of Knowledge Management at Various levels of Project Management Office xi
Complementary analytical techniques ............................................................................ 68 4.8.5
The quality of research .............................................................................................................. 70 4.9
Internal validity .............................................................................................................. 71 4.9.2
External validity ............................................................................................................. 72 4.9.3
Reliability ....................................................................................................................... 72 4.9.4
Conclusion ................................................................................................................................. 72 4.10
CASE STUDY ANALYSIS: SCIENCO ............................................................... 74 CHAPTER 5
Introduction ............................................................................................................................... 74 5.1
SCIENCO’s background ........................................................................................................... 74 5.2
Research Objectives and Questions ........................................................................................... 75 5.3
Data collection procedures ........................................................................................................ 76 5.4
The data collection schedule .......................................................................................... 76 5.4.1
The data collection methods ........................................................................................... 77 5.4.2
The data analysis ....................................................................................................................... 78 5.5
The level of maturity for SCIENCO’s Project Management Office............................... 78 5.5.1
Knowledge management practices and processes in SCIENCO .................................... 95 5.5.2
Discussion and Implications .................................................................................................... 115 5.6
Knowledge capturing’s sub processes and practices in SCIENCO .............................. 115 5.6.1
Knowledge creation’s sub processes and practices in SCIENCO ................................ 117 5.6.2
Knowledge transferring’s sub processes and practices in SCIENCO .......................... 119 5.6.3
Knowledge reusing sub-processes and practices in SCIENCO .................................... 120 5.6.4
Conclusion ............................................................................................................................... 121 5.7
CASE STUDY ANALYSIS: GOVCO ................................................................ 124 CHAPTER 6
Introduction ............................................................................................................................. 124 6.1
GOVCO’s background ............................................................................................................ 124 6.2
Data collection procedures ...................................................................................................... 125 6.3
The data collection methods .................................................................................................... 126 6.4
The data analysis ..................................................................................................................... 126 6.5
The maturity level of GOVCO’s Project Management Office ..................................... 127 6.5.1
Knowledge management processes and practices in GOVCO ..................................... 142 6.5.2
The importance of knowledge management processes in GOVCO ............................. 157 6.5.3
Discussion and Implications .................................................................................................... 162 6.6
Knowledge capturing’s sub processes and practices in GOVCO ................................. 162 6.6.1
Knowledge transferring’s sub processes and practices in GOVCO ............................. 164 6.6.2
Knowledge creation’s sub processes and practices in GOVCO ................................... 165 6.6.3
Knowledge reusing’s sub processes and practices in GOVCO .................................... 167 6.6.4
Conclusion ............................................................................................................................... 168 6.7
CASE STUDY ANALYSIS: MINCO ................................................................. 171 CHAPTER 7
Introduction ............................................................................................................................. 171 7.1
MINCO’s background ............................................................................................................. 171 7.2
Data collection procedures ...................................................................................................... 172 7.3
xii Investigating the Role of Knowledge Management at Various levels of Project Management Office
Data analysis ............................................................................................................................ 173 7.4
MINCO’s PMO maturity level ..................................................................................... 174 7.4.1
Knowledge management processes and practices in MINCO ...................................... 193 7.4.2
The importance of knowledge management processes in MINCO .............................. 207 7.4.3
Discussion and Implications .................................................................................................... 211 7.5
Knowledge transferring’s sub-processes and practices in MINCO .............................. 211 7.5.1
Knowledge reusing’s sub processes and practices in MINCO ..................................... 212 7.5.2
Knowledge capturing’s sub processes and practices in MINCO .................................. 213 7.5.3
Knowledge creation’s sub processes and practices in MINCO .................................... 215 7.5.4
Conclusion ............................................................................................................................... 217 7.6
DISCUSSION AND RESULT ............................................................................ 220 CHAPTER 8
Introduction.............................................................................................................................. 220 8.1
The analysis procedure ............................................................................................................ 220 8.2
An overview of case studies .................................................................................................... 221 8.3
Organisational structure ........................................................................................................... 222 8.4
Project management maturity level in three case studies ......................................................... 226 8.5
Knowledge management practices in various levels of PMO .................................................. 228 8.6
The Challenges of PMO from knowledge management perspective ............................ 228 8.6.1
The required types of knowledge in Project Management Offices ............................... 230 8.6.2
KM processes and KM practices at various levels of maturity ................................................ 233 8.7
Knowledge Capturing ................................................................................................... 233 8.7.1
Knowledge creation ...................................................................................................... 236 8.7.2
Knowledge Transferring ............................................................................................... 238 8.7.3
Knowledge Reusing ...................................................................................................... 241 8.7.4
PMO’s contributions to knowledge management .................................................................... 242 8.8
The importance of KM processes in various levels of PMO ........................................ 242 8.8.1
How PMO can contribute for managing the project knowledge .................................. 244 8.8.2
Model Development ................................................................................................................ 259 8.9
Integration of KM practices at various level of maturity .............................................. 259 8.9.1
Conclusion ............................................................................................................................... 269 8.10
CONCLUSIONS ................................................................................................. 273 CHAPTER 9
Overview ................................................................................................................................. 273 9.1
Knowledge Management Challenges in the PMO ................................................................... 274 9.2
The required types of knowledge in various levels of maturity ............................................... 275 9.3
Utilisation of knowledge management practices in PMO ........................................................ 276 9.4
The importance of knowledge management processes in PMO .............................................. 277 9.5
PMO’s contributions to knowledge management .................................................................... 277 9.6
Knowledge management processes in five maturity levels ..................................................... 278 9.7
Research Contributions ............................................................................................................ 279 9.8
General Contributions................................................................................................... 279 9.8.1
Theoretical Contributions ............................................................................................. 280 9.8.2
Investigating the Role of Knowledge Management at Various levels of Project Management Office xiii
Research limitations ................................................................................................................ 280 9.9
Future research ........................................................................................................................ 281 9.10
BIBLIOGRAPHY ....................................................................................................................... 284 APPENDICES ............................................................................................................................. 294
Appendix A - The Case Study Protocol................................................................................... 294 Appendix B - The research questions and Survey-questionnaire ............................................ 298 Appendix C - Ethics Approval ................................................................................................ 302 Appendix D - Samples of interview transcription in SCIENCO ............................................. 304
xiv Investigating the Role of Knowledge Management at Various levels of Project Management Office
LIST OF FIGURES
Figure 2-1 Modes of Knowledge Creation (Nonaka and Takeuchi 1995) .............................................. 8
Figure 2-2 PRINCE2's project lifecycle(adapted from (Bentley 2009)) ............................................... 13
Figure 2-3 PRINCE2’s components (adapted from (Bentley 2009)) .................................................... 13
Figure 2-4 OPM3 framework (Project Management Institute 2008b) .................................................. 21
Figure 2-5 The development of PM and KM (developed for this research) ......................................... 30
Figure 2-6 The significance of this Research (developed for this research) ......................................... 32
Figure 3-1 KM process at project-based organisation (Owen, et al. 2004) ........................................... 37
Figure 3-2 Kerzners’ Maturity Level (2005) ......................................................................................... 41
Figure 3-3 The research KM processes model (developed for this study) ............................................ 48
Figure 3-4 KM process and practices model (developed for this research) .......................................... 49
Figure 4-1 Research methods and data inquiry techniques (developed for this research)..................... 57
Figure 4-2 Research Design (developed for this research) ................................................................... 60
Figure 4-3 Interview and survey questions tree (developed for this research) ...................................... 63
Figure 4-4 Data analysis processes (developed for this research) ......................................................... 66
Figure 4-5 Sample of Coding (developed for this research) ................................................................. 69
Figure 5-1 A snapshot of SCIENCO's structure (from SCIENCO’s organisational chart) ................... 75
Figure 5-2 PMO’s ML from PMBOK's knowledge areas perceptive (developed for this study) ......... 80
Figure 5-3 SCIENCO’s Maturity level from PLC perceptive (developed for this research) ................ 81
Figure 5-4 PM Methodologies in SCIENCO (developed for this study) ............................................. 84
Figure 5-5 The exsisting KM challenges in SCIENCO’s PMO (developed for this study) .................. 89
Figure 5-6 Types of required knowledge in SCIENCO (developed for this research).......................... 92
Figure 5-7 The required types of knowledge in SCIENCO (developed for this research) .................... 94
Figure 5-8 A snapshot of KM process categories in the Nvivo (developed for this research) .............. 97
Figure 5-9 KM processes at project lifecycle (developed for this research) ......................................... 99
Figure 5-10 Knowledge capturing in SCIENCO’s PMO (developed for this research) ..................... 101
Figure 5-11 Knowledge Creation practices in SCIENCO (developed for this research) .................... 105
Figure 5-12 Knowledge Transferring at project lifecycle (developed for this research) ..................... 108
Figure 5-13 Knowledge reusing in SCIENCO’s PMO (developed for this research) ......................... 110
Figure 5-14 The importance of KM processes in SCIENCO (developed for this research) ............... 113
Figure 5-15 The general ranking of KM processes in SCIENCO (developed for this research) ........ 114
Figure 5-16 The SECI Model at SCIENCO (Nonaka and Teece 2001) .............................................. 118
Investigating the Role of Knowledge Management at Various levels of Project Management Office xv
Figure 6-1 A snapshot of GOVCO’s structure (from GOVCO’s organisational chart) ...................... 125
Figure 6-2 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study) ...... 128
Figure 6-3 The ML of GOVCO’ PMO: project lifecycle (developed for this research) ..................... 129
Figure 6-4 The exsisting KM challenges of GOVCO’s PMO (developed for this study) .................. 138
Figure 6-5 Types of required knowledge in GOVCO (developed for this research) .......................... 140
Figure 6-6 A snapshot of KM process categories in the Nvivo (developed for this research) ............ 143
Figure 6-7 KM processes at project lifecycle: GOVCO (developed for this research) ....................... 145
Figure 6-8 Knowledge Capturing in project lifecycle: GOVCO (developed for this research) .......... 148
Figure 6-9 Knowledge Transferring practices in GOVCO (developed for this research) ................... 151
Figure 6-10 Knowledge Creation in GOVCO (developed for this research) ...................................... 154
Figure 6-11 Knowledge reusing in GOVCO (developed for this research) ....................................... 156
Figure 6-12 Importance of KM process in project lifecycle: GOVCO (developed for this study) ..... 159
Figure 6-13 The general ranking of KM processes in GOVCO (developed for this research) ........... 160
Figure 6-14 The SECI model in GOVCO’s PMO (Nonaka and Teece 2001) .................................... 167
Figure 7-1 Snapshot of MINCO’s structure ((extracted from MINCO’s organisational chart) .......... 171
Figure 7-2 ML of MINCO’s PMO’s from knowledge areas perceptive (developed for this study) ... 175
Figure 7-3 MINCO’s Maturity level from project lifecycle perceptive (developed for this research) 176
Figure 7-4 MINCO's project life cycle (adopted from MINCO’s PM framework) ............................ 179
Figure 7-5 Selection &definition phase (adopted from MINCO’s PM framework) ........................... 180
Figure 7-6 The current KM challenges in MINCO’s PMO (developed for this study) ...................... 187
Figure 7-7 Types of required knowledge at MINCO’s PMO (developed for this research) ............... 191
Figure 7-8 KM processes at project lifecycle in MINCO (developed for this research) ..................... 195
Figure 7-9 Knowledge Capturing in MINCO’s PMO (developed for this research) .......................... 198
Figure 7-10 Knowledge Creation in MINCO (developed for this research) ....................................... 200
Figure 7-11 Knowledge transferring in MINCO (developed for this research) .................................. 204
Figure 7-12 Knowledge reusing at project lifecycle: MINCO (developed for this research) ............. 206
Figure 7-13 The importance of KM processes in MINCO (developed for this research) ................... 208
Figure 7-14 The general ranking of KM processes: MINCO (developed for this research) ............... 209
Figure 7-15 The SECI in MINCO’s PMO (Nonaka and Teece 2001) ................................................ 216
Figure 8-1 PMO level of maturity and project managers authorities (developed for this research) ... 223
Figure 8-2 Maturity of PMOs from project lifecycle perspective (developed for this study) ............. 226
Figure 8-3 Maturity of PMOs from knowledge area perspective (developed for this research) ......... 227
Figure 8-4 Challenges of KM at different maturity levels (developed for this study) ........................ 229
Figure 8-5 Importance of knowledge types in various maturity level (developed for this research) .. 230
xvi Investigating the Role of Knowledge Management at Various levels of Project Management Office
Figure 8-6 Numbers of the coded comments for KM processes (developed for this study) ............... 233
Figure 8-7 Knowledge capturing in various levels of maturity (developed for this study) ................. 234
Figure 8-8 Knowledge creation at various levels of maturity (developed for this study) ................... 237
Figure 8-9 Knowledge transferring at various levels of maturity (developed for this study) .............. 239
Figure 8-10 Knowledge reusing at various levels of maturity (developed for this study) .................. 241
Figure 8-11 Importance of KM processes in project lifecycle: All cases (developed for this study) .. 243
Figure 8-12 Knowledge caprtuing's sub-processes (developed for this study) ................................... 246
Figure 8-13 K. capturing’s sub processes in various level of maturity (developed for this study) ..... 247
Figure 8-14 Knowledge creation's sub-processes in three case studies( developed for this study) ..... 249
Figure 8-15 K. creation’s sub processes in various levels of maturity (developed for this study) ...... 251
Figure 8-16 Knowledge transferring's sub-processes case studies (developed for this study) ............ 253
Figure 8-17 K. transferring’s sub-processes in various levels of maturity (developed for this study) 254
Figure 8-18 Knowledge reusing’s sub-processes in three case studies (developed for this study) ..... 256
Figure 8-19 K. reusing’s sub processes in various level of maturity (developed for this study) ......... 257
Figure 8-20 KM sub processes in the first level of maturity (developed for this study) ..................... 261
Figure 8-21 KM sub processes in the second level of maturity (developed for this study) ................ 264
Figure 8-22 KM sub processes in the third level of maturity (developed for this study) .................... 267
Figure 8-23 KM processes in the fourth and fifith level of maturity (developed for this study) ......... 269
Figure 8-24 Summary of the research findings (developed for this study) ......................................... 270
Figure 8-25 KM challenges in PMOs (developed for this research) ................................................... 271
Investigating the Role of Knowledge Management at Various levels of Project Management Office xvii
LIST OF TABLES
Table 2-1 Knowledge perspectives and their definitions (Alavi and Leidner 2001) ............................... 9
Table 2-2 KM processes frameworks (developed for this study) ........................................................... 9
Table 2-3 Knowledge areas and Phases in PMBOK (developed for this research) .............................. 14
Table 2-4 Characteristics of tacit and explicit Knowledge (developed for this research) ..................... 18
Table 2-5 The comparison of PMMMs (developed for this study) ....................................................... 22
Table 2-6 Knowledge types in Projects (developed for this research) .................................................. 24
Table 2-7 KM initiatives and barriers in PMO (developed for this research) ....................................... 27
Table 2-8 The benefits of study findings (developed for this research) ................................................ 34
Table 3-1 Project phases and KM Processes Adapted from (Owen and Burstein 2005) ...................... 38
Table 3-2 KM objects of PMBOK (Reich and Wee 2006) ................................................................... 39
Table 3-3 Knowledge types in project context (Srikantaiah, et al. 2010) ............................................. 40
Table 3-4 KM maturity model, proposed by Feng (F-KMMM) (Feng 2006) ....................................... 44
Table 3-5 General KMMM (Kankanhalli and Pee 2009) ..................................................................... 47
Table 3-6 Types of knowledge in research framework (developed for this research) .......................... 48
Table 3-7 Knwoledge Creation pratices in project enviroments (developed for this research) ............ 49
Table 3-8 Knowledge capturing practices in project environment (developed for this research) ......... 50
Table 3-9 Knowledge transferring pratcices in project enviroment (developed for this research) ....... 50
Table 3-10 Knowledge reusing practices in project environment (developed for this research) .......... 51
Table 3-11 The customised KM Maturity Model or R-KMMM (developed for this research) ............ 53
Table 4-1 Different methods with their relevant situation (Yin , 2009, p. 8) ........................................ 58
Table 4-2 The proposed quality tactics (Yin 2009) .............................................................................. 71
Table 5-1 The Research Questions (developed for this research) ......................................................... 76
Table 5-2 Interviewees’ list and schedule in SCIENCO (developed for this research) ........................ 77
Table 5-3 The Data collection methods (developed for this research) .................................................. 78
Table 5-4 PMO’ ML from PM knowledge perspective (developed for this research) .......................... 79
Table 5-5 PMO’ ML from project lifecycle perspective (developed for this research) ........................ 80
Table 5-6 Participants’ quotes in SCIENCO’s PMO (developed for this research) ............................. 82
Table 5-7 The current systems and tools in SCIENCO’s PMO (developed for this research) ............. 85
Table 5-8 Example of using Axial &Open coding in SCIENCO (developed for this study) ................ 88
Table 5-9 Types of required knowledge in SCIENCO (developed for this research) ........................... 93
Table 5-10 KM processes and PLC (adopted from Owen and Burstein (2005)) .................................. 95
xviii Investigating the Role of Knowledge Management at Various levels of Project Management Office
Table 5-11 KM processes and their associated KM practices (developed for this research) ................ 96
Table 5-12 The usage of KM processes in SCIENCO (developed for this research) ........................... 98
Table 5-13 Knowledge capturing’s categories and practices (developed for this research)................ 102
Table 5-14 Knowledge creation’s categories and pratices (developed for this research).................... 104
Table 5-15 Knowledge transferring categories and pratices (developed for this research) ................. 107
Table 5-16 Knowledge Resing in SCIENCO’s PMO (developed for this research) ........................... 109
Table 5-17 Knowledge capturing sub-processes in SCIENCO (developed for this research) ............ 116
Table 5-18 Knowledge creation sub procesess in SCIENCO (developed for this research) ............... 117
Table 5-19 Knowledge transferring sub processes in SCIENCO (developed for this research) ......... 119
Table 5-20 Knowledge reusing sub-processes in SCIENCO (developed for this research)................ 120
Table 6-1 Interviewees’ list and schedule in GOVCO (developed for this research) ......................... 126
Table 6-2 Data collection methods (developed for this research) ....................................................... 126
Table 6-3 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study) ....... 127
Table 6-4 The ML of GOVCO’ PMO: project lifecycle (developed for this research) ...................... 128
Table 6-5 Participants’ quotes in regards to GOVCO’s PMO matuirty (developed for this research) 130
Table 6-6 The current system and tools in GOVCO’s PMO (developed for this research) ................ 133
Table 6-7 Example of using Axial &Open coding in GOVCO’s PMO (developed for this study) .... 137
Table 6-8 Types of knowledge and their rank at GOVCO (developed for this research) ................... 141
Table 6-9 KM processes and PLC (adopted from Owen and Burstein (2005)) .................................. 142
Table 6-10 The usage of KM processes in GOVCO (developed for this research) ............................ 144
Table 6-11 Knowledge capturing’s practices: GOVCO (developed for this research) ....................... 147
Table 6-12 Knowledge Transferring categories and pratices: GOVCO (developed for this research)149
Table 6-13 Knowledge creation’s categories in GOVCO (developed for this research) .................... 152
Table 6-14 Knowledge Reusing in GOVCO (developed for this research) ........................................ 155
Table 6-15 Knowledge capturing sub-processes in GOVCO (developed for this research) ............... 162
Table 6-16 Knowledge transferring sub processes in GOVCO (developed for this research) ............ 164
Table 6-17 Knowledge creation sub procesess in GOVCO (developed for this research) .................. 165
Table 6-18 Knowledge reusing sub-processes in GOVCO (developed for this research) .................. 167
Table 7-1 Interviewees’ list and schedule in MINCO (developed for this research) .......................... 173
Table 7-2 The Data collection methods (developed for this research) ................................................ 173
Table 7-3 PMO’ ML from PM knowledge perspective (developed for this research) ........................ 174
Table 7-4 MINCO’s PMO ML from project lifecycle perspective (developed for this research)....... 175
Table 7-5 Participants’ quotes in regards to MINCO’s PMO matuirty (developed for this research) 178
Table 7-6 The current systems and tools in MINCO’s PMO (developed for this research) ............... 181
Investigating the Role of Knowledge Management at Various levels of Project Management Office xix
Table 7-7 Example of Axial and Open coding in MINCO’s PMO (developed for this study) ........... 185
Table 7-8 Types of required knowledge in MINCO (developed for this research .............................. 192
Table 7-9 KM processes and PLC (adopted from Owen and Burstein (2005)) .................................. 193
Table 7-10 The usage of KM processes in MINCO (developed for this research) ............................. 194
Table 7-11 Knowledge capturing categories and practices: MINCO (developed for this research) ... 197
Table 7-12 Knowledge creation categories and pratices: MINCO (developed for this research) ....... 199
Table 7-13 Knowledge transferring pratices in MINCO (developed for this research) ...................... 202
Table 7-14 Knowledge Resing practices in MINCO (developed for this research) ............................ 205
Table 7-15 Knowledge transferring sub processes in MINCO (developed for this research) ............. 211
Table 7-16 Knowledge reusing sub-processes in MINCO (developed for this research) ................... 212
Table 7-17 Knowledge capturing sub-processes in MINCO (developed for this research) ................ 214
Table 7-18 Knowledge creation sub procesess in MINCO (developed for this research) .................. 215
Table 8-1 The research questions (developed for this study) .............................................................. 220
Table 8-2 A snapshot of three case studies (developed for this research) .......................................... 224
Table 8-3 A snapshot of three case stuides (continued ) ..................................................................... 225
Table 8-4 Knowledge capturing's sub-processes in various PMOs (developed for this study) .......... 244
Table 8-5 Knowledge creation’s sub-processes in various PMOs (developed for this study) ............ 248
Table 8-6 Knowledge transferring’s sub-processes in various PMOs (developed for this study) ...... 252
Table 8-7 Knowledge reusing’s sub-processes in various PMOs (developed for this study) ............. 255
xx Investigating the Role of Knowledge Management at Various levels of Project Management Office
LIST OF ABBREVIATIONS
PM
KM
KMS
PMO
PMMM
KMMM
GKM
ML
PBO
PMBOK
PRINCE2
PMI
AHP
OGC
DB
DMS
CoP
MIS
DSS
FMS
FAQ
ES
FIE
Project Management
Knowledge Management
Knowledge Management System
Project Management Office
Project Management Maturity Model
Knowledge Management Maturity Model
General Knowledge Model
Maturity Level
Project-Based Organisation
Project Management Body of Knowledge
Project In Controlled Environment
Project Management Institute
Analytic Hierarchy Process
Office of Government Commerce
Data base
Document Management System
Community of Practice
Management Information System
Decision Support System
File Management System
Frequently Asked Questions
Expert System
Formal and Informal Event
Investigating the Role of Knowledge Management at Various levels of Project Management Office xxi
STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted to meet requirements for
an award at this or any other higher education institution. To the best of my knowledge and
belief, the thesis contains no material previously published or written by another person except
where due reference is made.
Signature: QUT Verified Signature
Date: May 2015
xxii Investigating the Role of Knowledge Management at Various levels of Project Management Office
ACKNOWLEDGEMENTS
I would like to express my deep and sincere appreciation to my principal supervisor,
Professor Prasad Yarlagadda, for his unconditional support, friendly concern, professional
guidance, and encouragement over the past four years. Also I would like to deeply thank my
associate supervisor, Dr Judy Matthews, for her support and constructive guidance during the
course of this research project. In addition, I would like to cordially thank my external
supervisor, Associate Professor Bambang Trigunarsyah, for his friendly support for this
research.
QUT’s research office and SEF’s HDR staff, specifically Ms Elaine Reyes, have been very
helpful during this journey and I would like to appreciate their contribution. Also, I would like
to thank Professor Acram Taji for her kind support and friendly consideration. In addition, I like
to appreciate Ms Diane Kolomeitz’s professional services for proofreading and editing this
thesis.
I also would like to thank all the organisations and individuals who took part in this research,
for their cooperation and being helpful to me in accessing the required information. Due to
confidentiality, I am not able to mention their names, but this PhD would have not been
accomplished without their help and support. Also, I would like to thank my friends in Australia
who have been like family to me during this journey.
Last but certainly not least, I am forever indebted to my lovely parents and beloved family.
Thank you all.
Chapter 1 | INTRODUCTION 1
Chapter 1
INTRODUCTION
RESEARCH BACKGROUND 1.1
Knowledge is an organisational asset that comes from an individual’s mind, belief or values
and it creates value for improving competitive advantages (Drucker 1993; Drucker 2013).
According to Davenport and Prusak (2000) knowledge is "a fluid mix of experiences, values,
contextual information, and expert insights that provides a framework for evaluation and
incorporating new experiences and information." Hence, knowledge entails the subsequent
characteristics: 1) it is in people’s mind so cannot be easily transferred, 2) knowledge is a
judgement based on individual beliefs therefore it can be different from one person to another,
3) it is a vital element for creating new knowledge, 4) knowledge can be lost if it’s not properly
transferred or captured, and 5) it is an important asset for organisations and their competitive
advantages (Alavi and Leidner 2001; Davenport 1997; Davenport 2013). People, technology
and process are three core components of knowledge management in both functional and
project-based organisation (Davenport and Prusak 2000). From a process point of view,
knowledge management is defined as “a systemic and organisationally specified process for
acquiring, organising and communicating both tacit and explicit knowledge of employees so
that other employees may make use of it to be more effective and productive in their work”
(Alavi and Leidner 1999).
Project management is a relatively new approach to improve organisational competitive
advantages (Kerzner 2013). Project is defined as a temporary set of activities to obtain
predetermined objectives (Project Management Institute 2013). Project management is the
application of skill, tools, knowledge, and experience to achieve project objectives (Project
Management Institute 2013). It is generally accepted that the employment of appropriate PM
practices significantly impacts on delivering successful projects (Anbari 2005).
An investigation by the Standish Group (1995) in 1994 revealed that only 16% out of 175
000 Information Technology (IT) projects were successfully completed in the United States,
while 31% failed and the remaining 53% struggled with about 190% overrun costs. According
to Anbari (2005) the rate of unsuccessful project implementation and project failure has been
significantly increased since early 2000. A study by KPMG international claims that the lack of
project management methodology is the major cause of project failure (Whittaker 1999). In
other words, projects will most likely fail or be faced with numbers of issues and challenges, if
appropriate PM practices are not utilised (Anbari 2005; The Standish Group 1995). Due to the
2 Chapter 1 | INTRODUCTION
increasing importance of PM practices, numbers of project management methodologies and
standards have been developed since late 1990, by which organisations could improve their
project performance. The Project Management Body of Knowledge (PMBOK) has been
developed by the Project Management Institute (PMI) in late 1990 (Project Management
Institute 2013). In addition, the Office of Government Commerce (OGC) in the UK has
developed PRINCE2 (PRoject IN Controlled Environment) since early 2000 as another PM
methodology (Office of Government Commerce 2005). Both PMBOK and PRINCE2 are being
revised every four years in order to both improve current practices and introduce new best
practices.
After employing project management practices by organisations, studies show that the
numbers of unsuccessful and failed projects have significantly dropped. For instance, the
Standish Group conducted a similar study in 2002 in the same industry to investigate whether
utilising project management practices impacted project performance or not. The study revealed
that the project success rate has been significantly raised to 34 % (from 16% in 1994) while the
failure rate dropped to 16 % (from 31% in 1994) in which both rates indicate more than 100%
improvement (The Standish Group 2003). In other words, the appropriate employment of
project management practices significantly impact on delivering successful projects (Anbari
2005; The Standish Group 2003).
Management of project knowledge has been recognised as an important factor for project
success (Ajmal, et al. 2010). Due to the importance of knowledge management, many studies
have been conducted since the early 1990s, however, few research studies have discussed
knowledge management processes in project environments (Koskinen 2010; Koskinen and
Pihlanto 2008). Since project teams are disbanded or members leave after project completion,
knowledge management in a project-based environment is not similar to functional organisation
(Kasvi, et al. 2003). The temporary nature of projects imposes numbers of issues such as
“reparative activities”, “leaking of project knowledge”, and “reworks” for projects and project-
based organisations (Ajmal, et al. 2010; Koskinen and Pihlanto 2008; Love, et al. 2003).
A Project Management Office (PMO) is a unit or department within an organisation to
centrally facilitate, manage and control organisational projects through developing and
maintaining suitable processes and practices for PM (Kerzner 2009; Ward and Daniel 2013).
According to Santosus (2003) a PMO has a significant role in improving the rate of project
success, which means that it contributes to dropping the rate of project failure through both
establishing appropriate PM practices and, then, assisting project team members with applying
them (Artto, et al. 2011; Ward and Daniel 2013). In other words, the PMO is a unit within
modern organisations to institutionalise PM practices and processes to improve their
Chapter 1 | INTRODUCTION 3
organisational competencies (Dai and Wells 2004; Desouza and Evaristo 2006; Hurt and
Thomas 2009; Müller, et al. 2013).
Project Management Maturity Models (PMMM) have been proposed to address the
development of PMO in organisations through addressing appropriate project management
practices (Andersen and Jessen 2003; Aubry, et al. 2013; Crawford 2012; Yazici 2009). PM
maturity models contribute to the evolvement of PMO from an immature to a mature level
(Kerzner 2005; Kerzner 2013; PRINCE2 Foundation 2008; Project Management Institute
2008b). Despite the usefulness of current PMMMs, there are some challenges yet to be
addressed, which will be discussed in the next section.
PROBLEM STATEMENT 1.2
According to Liu and Yetton (2007), organisations have shown meaningful interest in
establishing and developing PMOs since the early 2000s. By the end of 2003 more than 50 000
US organisations have launched their PMOs and it has been estimated that a considerable
number of companies will establish their PMOs later (Liu and Yetton 2007). It is advisable to
adopt an appropriate PM maturity model to develop a PMO in an organisation (Kerzner 2005;
Project Management Institute 2008b). PM Maturity Models have been developed based upon: 1)
the existing PM methodologies such as PMBOK and PRINCE2, which address PM practices,
and 2) a process management approach that addresses minimum requirements to achieve
various levels of maturity (Kerzner 2005; Kulpa and Johnson 2008). The Organisational Project
Management Maturity Model (OPM3) has been proposed by the PMI to address the
development of PMOs, while OCG has developed a Portfolio, Program, Project Management
Maturity Model (P3M3) for the same reason (PRINCE2 Foundation 2008; Project Management
Institute 2008b). Both OPM3 and P3M3 address the development of a PMO through
progressively implementing and customising PM practices.
Despite the usefulness of current PMMMs, there are some challenges in developing a PMO
such as maturity levels, and type of organisations (Aubry, et al. 2008; Gajic and Riboni 2010).
According to Singh, et al. (2009) there are more than 30 challenges that PMOs deal with during
both their establishment and development stages. This means that the current PMMMs need to
be developed from some aspects to resolve the current challenges.
According to the findings of this study, knowledge management is one of the main
challenges that is yet to be addressed in the current PMMMs. Despite the number of studies that
have been conducted to investigate issues of KM in projects, few studies have considered KM
issues in PMOs. In other words, there is a significant gap in the existing literature to address
knowledge management practices in various maturity levels of PMO. The existing PMMMs
not only do not contribute to assessing the maturity of a PMO from a KM point of view,
4 Chapter 1 | INTRODUCTION
but also they do not address suitable KM processes, procedures or practices for various
maturity levels of a PMO.
With regards to the above mentioned explanation, developing an appropriate framework to
address suitable KM practices at different levels of a PMO, will significantly contribute to both
developing PMMMs from a KM point of view, and also improving the PMOs competencies. In
addition, increasing tendencies among organisations to implement and develop their PMOs,
corroborate the importance of this study, by which some of the challenges of current PMMMs
will be addressed.
RESEARCH AIM AND OBJECTIVE 1.3
The research aim is:
“To investigate KM practices in Project Management Maturity Models”
This research proposes a comprehensive framework to collaborate KM practices in each
level of PMMMs. Moreover, the proposed framework contributes to the existing PMMMs
through both addressing appropriate KM practices for various levels of maturity and assessing
maturity levels of PMO from a KM point of view. In addition, the proposed framework
comprises: 1) appropriate KM practices for each maturity level of PMO, 2) criteria and indices
to assess levels of maturity from a KM perspective, and 3) a suitable roadmap to address the
development of KM in PMOs.
The three following research objectives have been proposed to meet the above mentioned
research aim: 1) to analyse the role of KM practices in various maturity levels of PMO, 2) to
explore the contribution(s) of PMO for managing project knowledge, and 3) to develop a
framework to address KM in various maturity levels of PMO. The achievement of objectives
contributes to develop a theory(s) and/or frameworks to address the recognised research gap.
RESEARCH QUESTIONS 1.4
In order to achieve the research aim and the above-mentioned objectives, three main
questions have been defined as following: 1) to what extent are KM processes and practices
employed in the PMOs, 2) How do KM practices contribute to the maturity level of the PMO,
and 3) How can knowledge be integrated in the PM Maturity Model. The first and second
questions have been answered through case study methods, while the third question was
discussed through both cross-case analysis and developing a comprehensive framework.
RESEARCH APPROACH 1.5
This research is “Exploratory” in nature, and also it is an “Inductive” study since it aims to
propose a theory(s) or hypothesis to address the recognised gap (Gray 2009). Moreover, the
type of the proposed research questions indicate that it is a qualitative research instead of
Chapter 1 | INTRODUCTION 5
quantitative one (Creswell 2009; Gray 2009; Yin 2009). Furthermore, a Constructivism
worldview has been identified as the suitable paradigm for this research because: 1) there is no
theory behind this research; 2) it is an exploratory study ; and 3) it has been aimed to develop a
framework and theory to address the recognised gap(Gray 2009; Guba and Lincoln 1994). Case
Study has been chosen as the research methodology, alongside the four data collection methods;
interview, observation, questionnaire-survey and document analysis. Also, Grounded Theory,
together with the other analytical methods, have been utilised as the analysis techniques
(Creswell 2009; Yin 2009).
THESIS STRUCTURE 1.6
In this research, nine subsequent chapters have been provided to present the study outcomes.
Chapter One discusses the research introduction and the need for the management of project
knowledge in PBOs. In addition, the research questions, objectives, aims and designs have been
succinctly presented in this chapter.
Chapter Two presents a comprehensive literature review in three areas: Project
Management, Knowledge Management, and Knowledge Management in a Project Environment.
The research problems, the significance of the research, the research questions and objectives
have been presented in this chapter. At the end, the benefits of the research for various groups
and organisations have been illustrated.
Chapter Three presents the preliminary research framework which has been derived from
the literature. Also it discusses how research questions have been planned to be answered
through employing the proposed framework.
Chapter Four illustrates the research methodology and design. The data collection methods
have been illustrated to explain how data has been gathered and organised. Also, the data
analysis methods have been discussed, accordingly.
Chapters Five to Seven discuss three case studies outcomes, individually. For each case, one
chapter has been assigned to present them thoroughly; the result of each case has been
presented, in a consistent manner to give clear and insightful information about management of
project knowledge in various levels of maturity.
Chapter Eight presents the cross-case analysis through synthesising the findings from case
studies, and discussing the research findings to refine the preliminary research framework,
proposed in Chapter Four.
Chapter Nine discusses the conclusion of this thesis through discussing the findings against
the research question, and also presenting the research contributions, implications, limitations
and significance. At the end of this chapter, recommendations for future research have been
outlined.
7 Chapter 2 | LITERATURE REVIEW
Chapter 2
LITERATURE REVIEW
INTRODUCTION 2.1
This chapter discusses both Knowledge Management (KM) and Project Management
(PM) from different points of view. Management of human knowledge has been
epistemologically investigated since the classical Greek era (Alavi and Leidner 2001; Aubry,
et al. 2011). In contrast, PM has been recently considered as a modern approach to improve
organisational competencies (Jugdev and Thomas 2002; Stretton 1994). Due to the
importance of both KM and PM, in the last twenty years a plethora of studies have focused
on addressing them in both functional and project-based organisation (Brown and Duguid
1998; Nonaka and Takeuchi 1995; Nonaka and Takeuchi 2011; Peltola, et al. 2002; Wiig
1997b).
This chapter aims to critically investigate current discussions, methodologies, theories
and the substantial findings of both KM and PM, in order to formulate the research problem.
To do so, the four following sections have been provided: first, knowledge management and
its associated literature are presented; second, project management and project-based
organisations are discussed; third, the current discussions of KM in project based
environments are explained; and fourth, the recognised gap and research problem are
formulated.
THE NOTION OF KNOWLEDGE AND KNOWLEDGE MANAGEMENT 2.2
Drucker (1993) believes that “Intellectual property” or “individuals’ knowledge” refers to
the nonphysical and intangible asset of organisations by which competitive advantages could
be significantly improved. Since late 1980s, organisations have changed their strategies from
product-oriented to knowledge-driven, after realisation of knowledge impacts on
organisational performance (Wiig 1997a). It is generally accepted that individuals’
knowledge significantly contributes to the quality of products and, consequently, competitive
advantages (Drucker 2013; Porter 1985; Wiig 1997a).
Knowledge is defined as "a fluid mix of experiences, values, contextual information, and
expert insights that provides a framework for evaluation and incorporating new experiences
and information" (Davenport 2013; Davenport and Prusak 2000). According to Knight and
Howes (2003) knowledge is valuable information which comes from an individual’s mind.
Data and information are two main constituents of knowledge in which "Data is simple
8 Chapter 2 | LITERATURE REVIEW
observation of states of the world" and "Information is data endowed with relevance and
purpose" (Knight and Howes 2003).
According to (Nonaka and Takeuchi (1995); Nonaka and Takeuchi (2011)), knowledge is
subjective, process-relational, and aesthetic, and is created through human being interactions.
Knowledge is an important asset for both individuals and organisations and entails the
following characteristics (Alavi and Leidner 1999; Arora, et al. 2010; Davenport and Prusak
2000; Nonaka 1994):
• Knowledge comes from individual’s mind, belief or values;
• Knowledge is an individual’s ability to generate new knowledge or information from existing information, experience, insight or knowledge; and
• Knowledge creates value for organisations to develop competitive advantages
Knowledge management frameworks 2.2.1
From a process point of view, Nonaka and Teece (2001) define KM as the process to
transform tacit knowledge to explicit knowledge. In order to elaborate the mentioned
transformation, a spiral model was developed which comprises four processes: Socialisation,
Externalisation, Combination, and Internalisation (Nonaka 1994). According Nonaka and
Takeuchi (1995), in SECI model knowledge is created through interacting four processes, as
shown at Figure 2-1. Tacit Knowledge TO Explicit Knowledge
Tacit Knowledge
From Socialisation
Externalization
Explicit Knowledge Internalization Combination
Figure 2-1 Modes of Knowledge Creation (Nonaka and Takeuchi 1995)
Socialisation is the process of converting tacit to tacit knowledge through socialising
between owner of knowledge and learner, while Externalisation is the process of converting
tacit to explicit knowledge through articulation and codification (Nonaka and Takeuchi
1995; von Krogh, et al. 2012). In addition, Combination is the process of converting less
complex explicit knowledge to more complicated, through adding new features to an existing
articulated system or such; in contrast, Internalisation is the process of converting explicit
knowledge to tacit knowledge through utilising explicit knowledge to solve problems and
obtain new experiences i.e. learning by doing.
According to Walker and Christenson (2005) the SECI model both discusses individuals’
interactions to create new tacit knowledge, and addresses similar conversions in different
levels; individuals, groups, organisations and their inter-organisations. This model has been
examined in a number of contexts and it is known as one of the significant frameworks with
which to address knowledge management; however, many factors have not been considered
in this model (Walker and Christenson 2005). For instance, the role of individuals has not
Chapter 2 | LITERATURE REVIEW 9
appropriately discussed, particularly from a social science aspect. This means that some
influential factors such as culture and motivation, which directly impact on individuals’
behaviours, have not been addressed. The SECI model has been proposed in functional
organisations and it has not been properly investigated in the project context (Owen, et al.
2004; Owen and Linger 2011).
Table 2-1 Knowledge perspectives and their definitions (Alavi and Leidner 2001)
View of Knowledge Knowledge Management Definition is to
State of mind (Knowledge is state of knowing and understating )
Enhance individual’s learning and understanding through provision of information
Object (Knowledge is an object to be stored and manipulated) Build and manage knowledge stocks
Process (Knowledge is a process of applying expertise)
Create, share, and distribute knowledge through managing knowledge flows
Access to Information (Knowledge is a condition of access to information)
Organize appropriate access to and retrieval of content
Capability (Knowledge is the potential to influence action)
Build core competencies and understanding strategic know-how
According to Alavi and Leidner (2001), perspectives of knowledge are important factors to
define knowledge management. Five perspectives of knowledge have been proposed : 1) a
state of mind; 2) an object; 3) a process; 4) a condition of having access to proper
information; and 5) a capability by which KM could be defined in various ways (Alavi and
Leidner 2001). As shown at Table 2-2, if knowledge is a process, then KM is defined as
process of creation, sharing, and distribution of knowledge, while if knowledge is a
capability then KM is considered as building of core competencies and understanding
organisational strategic know-how (Alavi and Leidner 2001). In general, the knowledge
management has been defined as “ a systemic and organizationally specified process for
acquiring, organizing and communicating both tacit and explicit knowledge of employees so
that other employees may make use of it to be more effective and productive in their work.”
(Alavi and Leidner 1999) .
Table 2-2 KM processes frameworks (developed for this study)
Proposed Context Authors
Processes and their underpinnings
Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6
Functional Organizations
Nissen et al (2000) Create Organise Formalise Distribute Apply Evolve
Lytras et al. (2002)
Relate/value (Identify, Verify , Filter
&Select )
Acquire (Formalize,
Codify, Represent,
Format &Map)
Organise (Store,
Transform, Classify)
Enable Reuse (Adapt
&Create)
Transfer (Share,
Distribute, forward&
Line to ppl)
Use (Apply,
Integrate & learn)
Project –based Organisation
Owen & Burstein (2005)
Create Capture Transfer Reuse **** ****
Kasvi et al. (2003) Creation Administration Retrieval Utilization **** ****
Davidson Identify Assess Select Execute Operate Conversion
10 Chapter 2 | LITERATURE REVIEW
and Rowe (2009)
define
From a process point of view, Nissen, et al. (2000) conducted a comprehensive study to
investigate the current studies of KM, and eventually, an “amalgamated KM process
framework” was developed to address the KM lifecycle. As depicted in Table 2-3, five
processes were proposed to address KM: create, organise, formalise, distribute, apply and
evolve (Nissen, et al. 2000). Further, a complementary research was undertaken by Lytras et
al. (2002) to examine the mentioned model for developing an applicable and generic KM
process framework for functional organisations, as shown in Table 2-2.
In contrast, one of the first attempts to address KM processes in PBOs was conducted by
Owen and Burstein (2005) where KM processes were defined as: create, capture, transfer,
and reuse. As can be seen in Table 2-2, KM processes for both functional and project based
organisations have been presented to elaborate similarities and differences of KM processes
at the two mentioned contexts. The model proposed by Lytras et al. (2002) has been
employed in a number of research studies and it comprises of underpinning KM processes,
which covers the majority of KM processes. Due to the integrity and validity of this
framework, i.e. Lytras et al. (2002)’s model, it will be adopted to develop the research
framework. Also, the KM process model in Project-based Organisations (PBO), proposed by
Owen and Burstein (2005), will be employed as another premise for this study.
To sum up the above mentioned discussions, following can be mentioned as
characteristics of knowledge management (Alavi and Leidner 2001; Arora, et al. 2010;
Davenport and Prusak 2000; Kasvi, et al. 2003; Koskinen and Pihlanto 2008; Liebowitz and
Megbolugbe 2003; Nonaka and Takeuchi 1995; Wiig 1997b):
• KM is combinations of processes, procedures, practices, applications, and tools to increase organisational competitive advantages,
• KM creates value from organisational intangible assets through engaging individuals in appropriate practices,
• KM is an integrated cycle of knowledge creating, organising, transferring/sharing and using/reusing, and
• KM is the strategy to get right knowledge to the right person in the right time to improve the organisational performance.
In summary, data and information are main constituents of knowledge by which
knowledge is expanded or improved. Knowledge is the state of the mind that is created
through utilising data or information, so it needs to be managed through processes and
procedures. Contemporary organisations keen to manage individual’s knowledge in order to
improve their knowledge-bases and, eventually their competitive advantage.
Chapter 2 | LITERATURE REVIEW 11
THE EVOLUTION OF PROJECT MANAGEMENT 2.3
Today's competitive environment compels organisations to be innovative, knowledge
driven and project oriented (Brown and Duguid 1998; Kerzner 2009; Project Management
Institute 2008a). The need for timely response to market changes, customer needs and
technology improvements leads organisations to develop their competencies (Kotnour 2011;
Kotnour 2000). To do so, a project-oriented approach is being adopted by companies for
improving their agility, efficiency, and eventually competitive advantage (Jugdev and
Thomas 2002; Kloppenborg 2014). PM is defined as the application of knowledge, skills,
tools, and techniques to meet project requirements as well as objectives through employing
appropriate processes as well as methods (Project Management Institute 2008a). There are
five phases in the project lifecycle: initiating; planning; executing; controlling; and closing in
which each stage comprises of methods, procedures and processes to be utilised by project
team members for delivering a quality product or service (Project Management Institute
2013).
There are numbers of PM methodologies or guidelines that exist in the current literature.
The Project Management Body of Knowledge (PMBOK), developed by the Project
Management Institute (PMI), and Project In Controlled Environment (PRINCE2), proposed
by the Office of Government Commerce (OCG) in the UK, are the traditional PM
methodologies which have been established and improved based since 1990 (Office of
Government Commerce 2005; Project Management Institute 2013). In this section of the
literature review, projects, PM and their associated concepts will be discussed, followed by
presentation of numbers of PM methodologies. Then, the project management office (PMO)
will be reviewed, and at the end, PM Maturity Models (PMMM) will be discussed.
Project and Project Management 2.3.1
According to the Project Management Institute (2008a) a project is a temporary
endeavour to create a unique product or service in given periods of time with a determined
budget. In other words, a project is an activity that could not be implemented through
organisational procedures (Kerzner 2009). Project Management (PM) is the application of
knowledge, skills, tools, and techniques to meet project objectives (Project Management
Institute 2008a). PM is integration of skills and experiences to achieve a defined scope
within the given time and budget through utilising appropriate processes, practices and tools
(Office of Government Commerce 2005). A project is successful when it : 1) has met
objectives and project scope, 2) has been finished in planned time, 3) has been managed on
or below the planned budget and cost, and 4) has met the expected quality (Office of
Government Commerce 2005; Project Management Institute 2013).
12 Chapter 2 | LITERATURE REVIEW
Both knowledge and experience of the project manager are crucial factors for project
success (Koskinen 2010; Koskinen 2000; Peltola, et al. 2002). This means that a way of
managing knowledge within in a project was recognised as an important competency for
both project manager and project team members (Ajmal, et al. 2010; Bresnen, et al. 2003;
Kasvi, et al. 2003). Moreover, project success and quality of project are strongly dependent
on project managers’ knowledge of both PM methodologies and associated technical
knowledge (Kotnour 2000). According to Love et al. (2003), KM has a strong influence on
the efficiency of PM, in which poor utilisation of KM practices not only negatively impacts
on project success, but also causes some inefficiency such as overrun cost. As discussed
earlier, there are a number of types of knowledge related to project environment: knowledge
of project management, knowledge of application area, knowledge of other management
science especially human behaviour, knowledge of related tools and applications, and
knowledge of project context (Project Management Institute 2008a). The knowledge of PM
is addressed through appropriate standards and methodologies, such as PMBOK and
PRINCE2. Due to popularity of the mentioned frameworks, they will be succinctly explained
in the next section.
Project In Controlled Environment (PRINCE2) 2.3.2
PRINCE2 has been developed by the British’s Office of Government Commerce, since
1989 (Bentley 2009). The PRINCE2 addresses a generic PM standard, which comprises
numbers of PM practices to be employed in various types of projects (Office of Government
Commerce 2005). The last version of PRINCE2, fifth edition, was published in 2009, and it
consists of three major categories: project processes, project components, and required
techniques, which have been depicted in Figure 2-3 (Bentley 2009). From a project lifecycle
point of view, eight distinctive management processes are proposed in PRINCE2: 1) starting
up a project or SU, 2) directing a project or DP, 3) initiating a project or IP, 4) managing
stage boundaries or SB, 5) controlling a stage or CS, 6) managing product delivery or MP, 7)
closing a Project or CP, and 8) planning or PL (Bentley 2009; PRINCE2 Foundation 2008).
It is advised that the mentioned processes should be implemented in accordance to the
proposed processes detailed in Figure 2-1.
Chapter 2 | LITERATURE REVIEW 13
Figure 2-2 PRINCE2's project lifecycle(adapted from (Bentley 2009))
In addition, there are eight subsequent components in PRINCE2: 1) business case, 2)
organisations, 3) plan, 4) controls, 5) management risk, 6) quality, 7) configuration, and 8)
change control, in which each component entails the required knowledge, which should be
employed during a project lifecycle (PRINCE2 Foundation 2008). As presented in
Figure 2-3, the above mentioned components should be used at various stages of a project,
by which the quality of project management is met (Bentley 2009).
Figure 2-3 PRINCE2’s components (adapted from (Bentley 2009))
Also, three major techniques are advised in PRINCE2: 1) product based planning
techniques, 2) quality review techniques, and 3) change control techniques, which should be
14 Chapter 2 | LITERATURE REVIEW
employed in the whole project lifecycle (Bentley 2009). These techniques and their usages
have been properly addressed in the PRINCE2 as a means to undertake project activities.
Project Management Body of Knowledge (PMBOK) 2.3.3
PMBOK has been developed by the Project Management Institute (PMI) since 1996 as
the main reference for project management in the US (Guide 2004; Project Management
Institute 2008a). As the most influential PM guideline in the globe, PMBOK has been
revised based upon the latest successful best practices in order to both strengthen the method,
and broadly communicate the latest findings of project management (Project Management
Institute 2008a; Project Management Institute 2013). PMBOK proposes five phases for the
project life cycle: 1) initiation, 2) planning, 3) execution, 4) monitoring and controlling, and
5) closing (Project Management Institute 2013). In addition, ten following knowledge areas:
1) integration management 2) scope management, 3) time management, 4) cost management,
5) quality management, 6) human resource management, 7) communications management,
8) risk management, 9) procurement management, 10) stakeholders management, and 9) are
advised to be employed during five project phases (Project Management Institute 2013).
As presented at Table 2-4, each knowledge area has an appropriate correlation and
interactions with five Project Phases. This means that PMBOK addresses what sort of
knowledge areas and their associated practices should be employed at project lifecycle
(Project Management Institute 2013). In other words, knowledge areas were divided into a
number of sub-categories and processes in which forty-eight processes are addressed during
five phases of project lifecycle. These guide project managers to appropriately follow
suitable processes to undertake project activities.
Table 2-3 Knowledge areas and Phases in PMBOK (developed for this research) Project Phase
Initiation Planning Execution Monitoring & Control Closing Knowledge Area
1 Project Integration Management √ √ √ √ √ 2 Project Scope Management √ √ 3 Project Time Management √ √ 4 Project Cost Management √ √ 5 Project Quality Management √ √ √ 6 Project Human Resources Management √ √ 7 Project Communications Management √ √ √ 8 Project Risk Management √ √ 9 Project Procurement Management √ √ √ √ 10 Project Stakeholders Management √ √ √ √
Given the process-based structure of PMBOK, the ten knowledge areas have been made
inter-correlated, by which the output of one knowledge area is used as an input for another
knowledge area. This means that inaccurate or less quality outcomes of a predecessor
knowledge area, in various project phases especially in the initiation and planning stages,
significantly impact on the quality of a successor knowledge area, and ultimately, quality of
Chapter 2 | LITERATURE REVIEW 15
a whole project (Project Management Institute 2013). According to PMI (2008a),
appropriate usage of knowledge areas in each phase is a crucial key to manage a project
successfully. In other words, this methodology gives an applicable roadmap to address
proper tools and applications in order to assist project team members; however, there are
number of factors which should be considered during the employment of this standard. This
framework has been adopted as the research PM methodology and it will be discussed in the
future.
The Project Management Office (PMO) 2.3.4
The Project Management Office (PMO) is a unit or department in matrix and project-
based organisations to institutionalise PM practices through developing and customising PM
methodologies (Kerzner 2009; PRINCE2 Foundation 2008; Project Management Institute
2008b). According to Desouza and Evaristo (2006), PMO is an exercise to customise and
sustain PM practices, methods, techniques and tools in companies. The notion of PMO has
being developed since the 1950s, and it has been continuously improved, especially in the
last ten years, through proposing PMO as an important part of organisational structure in
modern enterprises (Kerzner 2005). In the early 1950s, PMO was considered as an optional
organisational unit to delegate some ordinary tasks and authorities, while since the early
2000s it has become a strategic unit or department in project-based and matrix organisations
to contribute to achieving organisational goals as well as project objectives (Kerzner 2005;
Walker and Christenson 2005).
In order to establish and develop a PMO, numbers of changes should be undertaken in
structure, processes, procedures as well as organisational culture (Kerzner 2005; PRINCE2
Foundation 2008; Project Management Institute 2008a). In other words, PMO not only
should take responsibility of existing PM activities, but also it is accountable to continuously
improve organisational competencies, from a PM point of view (Kerzner 2013). However,
PMO development is not an overnight activity and it needs to be appropriately prepared for
such a mission (Crawford 2006). This means that PMO should be gradually established and
developed in a way that not only its position and responsibility are being accepted by other
organisational units, but also robust and reliable interactions are being developed among
PMO and the whole organisation (Kerzner 2005; Project Management Institute 2008b).
A Project Management Maturity Model (PMMM) has been proposed to address step-by-
step development of a PMO from an immature level to a mature level (Project Management
Institute 2008b). In other words, PMMM is a method to guide the establishment of PMO
through addressing suitable approaches, processes, criteria, and practices for both
institutionalising of a PMO unit within an organisation, and also developing organisational
competencies, from a PM point of view (Kerzner 2005). In addition, PMMM contributes to
16 Chapter 2 | LITERATURE REVIEW
improve organisational readiness as well as a culture for adopting project management as an
approach for enhancing competitive advantages (Crawford 2012; Crawford 2006; Jugdev
and Thomas 2002).
The development of PMO through employing PMMM, is recommended as the best
solution for improving PM practices in organisations (Jugdev and Thomas 2002). Hence,
PMO could possess different levels of maturity in which the higher levels mean a better
PMO performance. According to the current literature, numbers of the following
responsibilities have been mentioned for PMOs, regardless of level of maturity (Artto, et al.
2011; Crawford 2012; Desouza and Evaristo 2006; Hurt and Thomas 2009).
• Aligning projects with organisational strategies,
• developing standards, processes, and methods of PM and improving organisational capacities to employ them,
• Managing all requirements for a project such as staffing, equipment and space in order to optimise organisational resource usage,
• Assessing viability and feasibility of project and its contribution to the business value of organisation,
• Defining and monitoring project success/failure measures,
• Monitoring and controlling organisational project,
• Training project stakeholders especially project team members and project manager,
• Quality assurance of the project,
• Managing organisational projects risks,
• Coordinating communication management across projects, a mentoring platform for project managers,
• Project portfolio management: Multiple project management (simultaneously or
historically) to conduct and manage similar issues in order to compare and
manage them appropriately, and
• One of the main responsibilities of the PMOs could be categorised as: managing
project and team members' knowledge, capturing and utilising lessons learned
and linking project knowledge to organisational knowledge.
There are numbers of PMMMs to address the development and responsibilities of PMO,
which will be discussed in the next section. The Organisational Project Management
Maturity Model (OPM3) is a well-known PMMM which is proposed by PMI to address the
development of PMO as well and PMBOK in organisations (Project Management Institute
2008b). In addition, the Portfolio Program Project Management Maturity Model (P3M3) is
another PMMM published by OCG to develop the PMO from a PRINCE2 perspective
(PRINCE2 Foundation 2008). The above mentioned responsibilities of PMO have been
emphasised by both mentioned PMMMs in a way that not only does PMO not intervene with
Chapter 2 | LITERATURE REVIEW 17
the responsibilities of project managers but also it aims to offer appropriate services and
advice to them (PRINCE2 Foundation 2008). The following have been made by PMI to
clarify the significant role of PMO (Project Management Institute 2008a):
• Project managers pursue specific project’s observations, in contrast the PMO
follows corporate level strategies;
• Responsibility of a project manager is limited to a specific project while the PMO
is responsible for all an enterprises’ projects;
• The focus of a project manager is only on specified project objectives, but the
PMO conducts scope management in the high level of an enterprises’ projects.
• Optimising the use of shared organisational resources across the project is the
responsibility of the PMO but project managers just focus on one project; and
• The project manager manages the scope, schedule, cost and quality of the
products of the work packages, while the PMO manages overall risk, overall
opportunity and all project interdependencies.
According to the existing literature there is a strong agreement among academics and
practitioners about the significant contribution of a PMO for delivering a successful project
(Santosus 2003). In addition, anecdotal evidence reports that organisations have shown
meaningful interest in launching and improving the PMO within their structures. According
to Liu and Yetton (2007), a considerable number of companies established their PMOs in
2003 and it was estimated that another 50 000 US organisations will launch their PMO by
the end of 2003. This means that organisations believe that establishing and developing the
PMO through standard processes enhances the quality of the project management and it is
known as an appropriate resolution for tackling project failure (Andersen, et al. 2007; Dai
and Wells 2004; Desouza and Evaristo 2006).
Given the increasing interests of launching and enhancing a PMO, there are numbers of
challenges during PMO development which need to be looked into. (Kerzner 2005; Kotnour
2011). More than 30 challenges have been discussed by Singh, et al. (2009) through
undertaking the Delphi method, by which some issues such as lack of PMMMs and
knowledge management have been discussed. Despite the usefulness of this study, the
recognised challenges have not clearly been discussed in terms of their rank and importance.
According to researcher investigations, the majority of them could be tackled through
following appropriate implementation of PMO maturity models, however, some of them
need other solutions. However, KM in the PMO is one of the recognised challenges, which
will be investigated as the subject of this research.
18 Chapter 2 | LITERATURE REVIEW
In summary, PMO is a unit in organisation which is responsible for PM activities. The
development of PMO is not the overnight decision and it necessitates an undertaking through
appropriate methods (Kerzner 2005). Since early 2000s, numbers of organisations have
started to establish and develop their PMO through employing in accordance with existing
PMMMs, however, there are some challenges that are yet to be addressed (Aubry, et al.
2008; Grant and Pennypacker 2006; Jugdev and Thomas 2002; Liu and Yetton 2007). Due to
the significant impacts of PMO in an organisational structure, it is preferred to employ
reliable methods that are developed based upon best practices. PMMMs are considered as
valid methodology to address the development of PMO (PRINCE2 Foundation 2008). In the
next section, numerous current PMMMs will be discussed to gain insightful knowledge in
this regard.
Taxonomies of knowledge 2.3.5
Knowledge is a multidimensional phenomenon that could be investigated from different
point of views (Ein-Dor 2008). There are a number of types of knowledge in the literature,
by which knowledge management is defined (Alavi and Leidner 2001). This means that
definition of knowledge management is related to the adopted taxonomy of knowledge. The
first and the most important taxonomy of knowledge is tacit and explicit dimension which
was recognised by Polanyi in the 1970s (Ein-Dor 2008; Polanyi 1983).
According to Polanyi (1983) human beings could not articulate, elaborate or tell
everything he/she knows. In other words, tacit knowledge exists in the individual’s mind,
while explicit knowledge is the articulated knowledge (Anand, et al. 2010; Ein-Dor 2008;
Polanyi 1983). However, how individuals’ implicit knowledge could be transformed to
explicit knowledge has become an important subject for numbers of studies (Davenport and
Prusak 2000; Nonaka and Takeuchi 1995).
Table 2-4 Characteristics of tacit and explicit Knowledge (developed for this research)
Explicit Knowledge Tacit Knowledge
Can be codified or articulated. Difficult to codify or articulate.
Found in documents, forms and inductions. Embedded in individual intuitions and expertise.
Can be explained or elaborated. Difficult to explain or elaborate. Can be exploitable. Difficult to exploit.
Can be schematic and easy to understand. Complex to be understood. Can be sharable, transferable and teachable. Difficult to share, transfer, and teach.
Known as “Know-why”. Known as “Know-how”. Independent from individual’s mind. Dependent to individual’s mind.
The mentioned taxonomy of knowledge was been developed by Nonaka (1994) through
proposing a “knowledge spiral“ model. According to Nonaka (1994) tacit knowledge is the
root of human knowledge and it is embedded in an individual’s mind, beliefs and thoughts,
which cannot be easily codified. In other words, tacit knowledge is the hidden side of
Chapter 2 | LITERATURE REVIEW 19
individual knowledge, deeply rooted in his/her actions, ideals, and commitments (Nonaka
1994). While explicit knowledge is articulated and codified in organisational documents,
forms and instructions, so it is not complex to share, transfer and disseminate through
appropriate and formal systems, processes or procedures (Nonaka 1994). Table 2-1
summarises the characteristics of tacit and explicit knowledge, in the current literature
(Ajmal and Koskinen 2008; Alavi and Leidner 1999; Arora, et al. 2010; Christensen and
Bang 2003; Davenport and Prusak 2000; Kasvi, et al. 2003; Knight and Howes 2003;
Koskinen 2000; Nonaka and Takeuchi 1995).
Tacit knowledge is a critical source to develop organisational competencies (Goffin, et al.
2010; Teerajetgul and Chareonngam 2008). Individuals are owners of tacit knowledge
therefore, organisations should focus on articulating this type of knowledge in order to
enrich the knowledge-bases (Nonaka and Takeuchi 1995). Tacit knowledge can be
transformed to explicit knowledge through articulating and/or documenting methods, which
is a significance challenge (Nonaka and Takeuchi 1995). Tacit knowledge has two
dimensions: cognitive; and technical, where the cognitive dimension relates to the mental
model of an individual, while technical dimension refers to an individual’s concrete know-
how and skills (Nonaka and Takeuchi 2011; von Krogh, et al. 2012). This typology
emphasises the importance of psychology by which a human being’s mental model could be
analysed. In other words, management of tacit knowledge is dependent on individuals’
mental model, and consequently, management of human behaviours as well as organisational
culture (Koskinen and Pihlanto 2008).
To transform the tacit knowledge to explicit knowledge, understanding of both human
behaviour and organisational culture plays a significant role (Koskinen and Pihlanto 2008).
However, the existing solutions have mainly focused on technical or mechanical aspects
rather than individuals’ behaviours (Koskinen 2000). In other words, considering social and
behavioural aspects of a human being is mandatory to encourage individuals to transfer their
knowledge. A study by Walker and Christenson (2005) has discussed social science and
physiology to understand both employees’ behaviour within organisations and their
interactions with co-workers, an organisation and external environments. Similar research
has been conducted to examine the tacit dimension of knowledge against a number of
behaviour factors in order to investigate the social aspect of tacit knowledge within Project-
Based Organisations (Koskinen and Pihlanto 2008). These studies have recognised numbers
of factors such as organisational culture, individual mental mode, and trust, to facilitate
transforming tacit knowledge to explicit knowledge (Ajmal and Koskinen 2008; Koskinen
and Pihlanto 2008; Wiewiora, et al. 2010).
20 Chapter 2 | LITERATURE REVIEW
The context of this study, i.e. Project Management Office (PMO), necessitates focus on
the existing taxonomies of knowledge in project environments. In the current literature, a
few attempts have been undertaken to discuss types of knowledge in PBOs, however, the
taxonomy of knowledge has not been discussed extensively. In other words, there is no
accepted or generic typology of knowledge in PBOs, however, some evidence claims that
this subject is being evolved (Kasvi, et al. 2003; Wiewiora, et al. 2009b). Kasvi et al. (2003)
introduce three types of knowledge in project environments: 1) Technical knowledge which
is related to products, their parts and technologies; 2) Procedural knowledge which concerns
how product should be produced in a project through appropriate procedures; and 3)
Organisational knowledge which is related to communication and collaboration of project.
These types of knowledge will be discussed further in section 2.4. From a tacit and explicit
perspective, it could be concluded that “technical knowledge” could be more of a tacit
knowledge, while procedural and organisational knowledge could be considered as an
explicit type of knowledge. This typology was adopted and developed by some studies in
PBOs. For instance, Wiewiora et al. (2010) have accepted two first types i.e. technical &
procedural knowledge, but they modified the last one, organisational knowledge, to be
“about customer requirement”. This change has been undertaken in accordance to PMBOK
(2008a).
The Project Management Maturity Models 2.3.6
The basic idea of a maturity model is that “you must learn to crawl before you can learn
to walk” (Andersen, et al. 2007). As discussed previously, PMMM is a framework to
construct PMO in an organisation through improving from an immature level, i.e. initial or
ad hoc, to mature level, i.e. optimised or centre of excellence (Jugdev and Thomas 2002;
Kerzner 2005; PRINCE2 Foundation 2008; Project Management Institute 2008b). This
means that PMO should be systematically developed by adopting appropriate PMMM to: 1)
assess and measure the current maturity level, 2) benchmark the current status, 3) plan to
achieve the higher maturity level. According to Andersen, et al. (2007) a process-oriented
approach is the common strategy among the existing PMMM by which PMOs could follow
certain process to achieve their objectives.
Both PMBOK and PRINCE2 address PM through numbers of processes in various
phases. In other words, both PRINCE2 and PMBOK are considered as process-base
methodologies (Bentley 2009; Kerzner 2013). In addition, both PM methods have their
associated PMMMs, OPM3 and P3M3, to address the development of PMO. This means that
OPM3 is a suitable PMMM for those organisations that adopted PMBOK, and similarly,
P3M3 is recommended by PRINCE2 followers to be adopted (Bentley 2009; Kerzner 2013).
Despite some differences from the PM point of view, OPM3 and P3M3 have been developed
Chapter 2 | LITERATURE REVIEW 21
based upon the Capability Maturity Model Integration (CMMI), developed by Carnegie
Mellon University as the valid method to create a mature process model (Grant and
Pennypacker 2006; Jugdev and Thomas 2002; Kulpa and Johnson 2008).
Figure 2-4 OPM3 framework (Project Management Institute 2008b)
OPM3 addresses the development of PMBOK in organisations, through developing PMO
in three categories: project, program, and portfolio at four levels of maturity: 1) standardise;
2) measure, 3) control, and 4) continuously improve (Project Management Institute 2008b).
As shown at Figure 2-4, maturity level of PMO could be improved by following certain steps
(Project Management Institute 2008b).
In a similar manner, P3M3 is a step-by-step framework to address the customisation of
PRINCE2 in three following categories: portfolio, program, and project, at five levels of
maturity: awareness, repeatable, defined, managed, and optimised (PRINCE2 Foundation
2008). As shown in Table 2-5, P3M3 has one more level, in comparison to OPM3 and, also
it follows the CMMI methodology, from a process point-of-view.
As presented in Table 2-5, there are four popular mentioned PMMMs in the current
literature: OPM3, P3M3, Kerzner’s PMMM, and CMMMI-based PMMM. According to this
table, all four PMMMs follow a process-based approach and the majority of them have
adopted CMMI in this regard. It could be concluded that there is no significant difference
22 Chapter 2 | LITERATURE REVIEW
among the mentioned PMMMS except the adopted PM methodology. Hence, adopting
appropriate method is dependent on some factors. For instance, OPM3 is recommended if
the adopted PM methodology is PMBOK, and similarly, P3M3 is suitable for organisations
that choose PRINCE2.
Table 2-5 The comparison of PMMMs (developed for this study) Maturity Level
Level 1 Level 2 Level 3 Level 4 Level 5 Maturity Model
OPM3 Standardize Measure Control Continuously improve ******
P3M3 Awareness Repeatable Defined Managed Optimized
Kerzner’s PMMM Common Language
Common Process
Singular Methodology Benchmarking Continues
Improvement
CMMI- based PMMM Initial Repeatable Refined Managed Optimized
According to Gasik (2011) eight elements should be considered, before choosing a
maturity model: 1) method independency: degree to which a maturity model is aligned to a
PM methodology, 2) public domain: the degree to which a maturity model and maturity
assessment can be applied by anyone besides its owners, 3) publication: the degree to which
a maturity model is issued in publications, 4) industry independency: the degree to which the
application of a maturity model is limited to particular industry sectors, 5) transparency: the
traceability of the calculation of the maturity scores, 6) toolset independency: the degree to
which the usage of a maturity model is bound to a toolset, 7) years of existence: how many
years a maturity model has existed, and 8) ease of use: the degree to which a maturity model
is easy to use in practice. These factors were investigated in more than twenty maturity
models, and eventually, the following have been recommended as the most suitable maturity
models (Gasik 2011):
• Organizational Project Management Maturity Model (OPM3)
• Capability Maturity Model Integration (CMMI-DEV)
• Kerzner Project Management Maturity Model (PMMM)
• Project, Program, Portfolio Management Maturity Model (P3M3)
Since Kerzner’s PMMM has been developed based on PMBOK, and also it has been
adopted by numbers of organisations, it has been adopted as the research PMMM and will be
discussed thoroughly, in the section 3.3.3.
Conclusion 2.3.7
Project management is an important factor to improve organisational competitive
advantage (Aubry, et al. 2011; Grant and Pennypacker 2006). The dramatic increasing
attention to PM necessitates addressing appropriate PM methodologies and structures
(Jugdev and Thomas 2002; Kotnour 2000). The realisation of PM importance, has led
Chapter 2 | LITERATURE REVIEW 23
number of organisations to develop various types of PM methodologies, standards and
solutions such as PMBOK and PRINCE2 (Kerzner 2013; PRINCE2 Foundation 2008;
Project Management Institute 2013). The PMO has been defined as a unit or department to
establish and develop PM methodologies (Kerzner 2013; Project Management Institute
2013). The development of PMOs has been addressed by proposing PM maturity models
(PMMM) (Kerzner 2005). PMMM contributes to both the development of PMOs from
immature levels to a mature level, and enhancement of organisational capabilities from a PM
perspective (PRINCE2 Foundation 2008). According to the current literature, there are
numbers of PMMM such as OPM3, P3M3 and Kerzner’s PMMM. The selection of an
appropriate method depends upon a number of factors that should be considered before any
practical steps (Gasik 2011).
KNOWLEDGE MANAGEMENT IN PROJECT-BASED ORGANISATIONS 2.4
The management of project knowledge is a critical activity for project success (Ajmal, et
al. 2010; Davidson and Jillian 2009; Koskinen and Pihlanto 2008), and managing a
successful project is significantly dependant on project knowledge management (Kotnour
2011; Kotnour 2000). In other words, the ability to identify and utilise appropriate
knowledge contributes to both delivering quality products, and achieving project objectives.
In other words, KM processes and practices play significant roles in delivery of a successful
project.
As discussed earlier, KM has been extensively discussed in functional organisations since
the 1990s, however, it is claimed that current KM practices for those types of enterprise are
not necessarily appropriate for project-based organisations (Polyaninova 2010). According to
Bresnen, et al. (2003), the three following issues are the main constituents of KM challenges
in PBOs: 1) projects are finite and their personnel disband or leave after project termination,
therefore created knowledge might not be utilised in similar projects, 2) there are difficulties
in developing and disseminating knowledge within and between projects -inter and intra
project-, and 3) fragmentation of project team members into different groups, makes the flow
of knowledge difficult among groups.
The temporary nature of projects is recognised as the main reason to emphasise the
importance of necessitating customised KM practices to tackle KM issues in PBOs (Bresnen,
et al. 2003; Newell, et al. 2006; Pemsel and Müller 2012). According to Ajmal and Koskinen
(2008), the temporary nature of projects creates a number of challenges from a KM point of
view, and the diversity of project team members’ expertise for cooperating in a short time
period, also cause KM challenges in PBOs. Given the existence of broad discussions of KM
in the literature, however, a few of them have focused on addressing KM in project
environments (Koskinen, et al. 2003; Ribeiro and Ferreira 2010; Söderlund 2010).
24 Chapter 2 | LITERATURE REVIEW
According to Kasvi et al. (2003) the existing solutions of KM practices in the literature are
not suitable for project contexts and KM is yet be properly addressed. It is generally
accepted that the current KM studies could not cover the recognised challenges of KM in
PBOs such as leaking knowledge, lack of mentoring and timely limited activities (Landaeta
2008; Leseure and Brookes 2003; Wiewiora, et al. 2009b).
According to Desouza and Evaristo (2006) management of project knowledge is one of
the most critical roles of the PMO. Given the importance of KM in the PMO, limited studies
have been undertaken to address this phenomena. Particularly, there is a significant gap in
which to address the KM practices in PMMM. In other words, PMMM have addressed
number of practices for improving the maturity of the PMO from a PM point-of-view,
however, the KM perspective has not been discussed by these models. In this section, major
discussions of KM in PBOs will be presented, in order to have a better understanding of the
current discussions of KM to formulate the research problem.
Type of Knowledge and KM in Project-based Organisations 2.4.1
Project knowledge can be categorised as tacit and explicit, in which tacit knowledge is
critical for project success (Koskinen 2010; Koskinen 2000). According to Koskinen (2000)
transforming tacit knowledge to explicit should be undertaken through consideration of the
social and behavioural aspects of human characteristics. Some behavioural elements of tacit
knowledge such as trust, social influence and culture have been examined in PBOs, and they
are considered as significant factors to managing tacit knowledge (Wiewiora, et al. 2010).
Given the tacit and explicit dimensions of project knowledge, Damm and Schindler (2002)
have discussed the following three types of knowledge: 1) knowledge about project, which is
required before and during the project implementation such as PM methods, 2) knowledge in
project which presents KM during project execution such as KM processes, and 3)
knowledge from project, which deals with KM after the closing phase, for instance lesson
learned, as presented in Table 2-6.
Table 2-6 Knowledge types in Projects (developed for this research)
Authors Type of knowledge in PBOs
Koskinen (Koskinen 2010; 2000)
• Explicit Knowledge • Tacit Knowledge
Kotnour (Kotnour 2011; 2000)
• Intra-project Knowledge • Inter-project knowledge
Damm and Schindler (2002)
• Knowledge about project • Knowledge in project • Knowledge from project
Kasvi et al. (2003) • Technical knowledge • Procedural knowledge • Organizational knowledge
Chapter 2 | LITERATURE REVIEW 25
Wiewiora (2010) • Technical knowledge • Procedural knowledge • Knowledge about customers’ needs
A succinct summary of the existing KM discussion in PBO 2.4.2
From a practical point-of-view, Kasvi, et al. (2003) propose three types of project
knowledge: 1) technical knowledge, which is about technical aspects of project product, 2)
procedural knowledge that focuses on processes of producing product, and 3) organisational
knowledge that focuses on collaborating and integrating knowledge within an organisation.
Similar to the above mentioned type of knowledge, these three types of knowledge could be
investigated from both tacit and explicit perspectives, however, it seems the first and the last
ones are more tacit rather than explicit, while the procedural knowledge is likely of an
explicit nature. A study by Wiewiora et al. (2009a) has adopted accept the first two types of
knowledge, and changed the third one to "knowledge about customer requirements”, in
accordance with PMBOK. Table 2-6 exhibits some of taxonomies of knowledge in the
PBOs.
The importance of tacit knowledge on project success has been initially investigated by
Koskinen and Pihlanto (2008); Koskinen, et al. (2003); Ward and Daniel (2013). Since,
individuals are owners of tacit knowledge, hence, individuals’ behaviours and the social
science aspect of knowledge management were considered (Koskinen, et al. 2003).
According to Koskinen, et al. (2003) three types of competencies are required for managing
individual knowledge in PBOs: 1) explicit knowledge, which could be easily shared and
communicated, 2) tacit knowledge, which hardly can be shared, and 3) personal
characteristics such as stress management and tolerance. In other words, these competencies
are influential factors in transforming tacit knowledge into explicit knowledge (Koskinen
and Pihlanto 2008; Koskinen, et al. 2003).
Apart from the above-mentioned competencies, five types of communication: 1) face to
face, 2) telephone, 3) written personal, 4) written formal, 5) numeric formal have been
adopted as possible connection media among individuals in a project context (Koskinen, et
al. 2003). According to Koskinen, et al. (2003), face-to-face is the best method to transform
tacit knowledge into explicit knowledge, by which knowledge could be codified for transfer
and reuse purposes. A further investigation by Wiewiora et al. (2010), which will be
discussed later, not only confirms the importance of face-to-face communication for
knowledge transfer, but also it claims that informal face-to-face communication is an
effective method for knowledge transfer.
The role of social science is another subject which was considered by Koskinen, et al.
(2003). The numbers of non-technical factors, such as personal characteristics, intuition,
26 Chapter 2 | LITERATURE REVIEW
individual’s mental model, and commitment have been investigated to examine their impact
on managing project knowledge (Koskinen, et al. 2003). All mentioned factors, which are
called Holistic Concepts of Man, could be significantly influential for transforming tacit
knowledge to explicit knowledge, hence, appropriate methods could facilitate the processes
of articulating tacit knowledge (Koskinen and Pihlanto 2008; Koskinen, et al. 2003).
According to Kotnour (2000) the quality of projects could be improved through adopting
the following cycle: Plan-Do-Study-Act or PDSA in which knowledge management and
organisational learning play an important role. In other words, knowledge is created during
“study and plan” phases and should be utilised at “do and act” stages. This means that
quality of projects increases when organisations learn from previous projects and apply this
knowledge accordingly (Kotnour 2000). The PDSA is a customised form of PDCA (Plan-
Do- Check-Act) which was developed by Edward Deming to address the development of a
quality management system (Scherkenbach 1986). The PDSA cycle discusses both inter- and
intra- project knowledge to address how creating and sharing knowledge within a project, i.e.
intra-project, and combining and sharing lessons learned across other projects, i.e. inter-
project, will contribute to the quality of the projects (Kotnour 2000). The significance of
Kotnour’s research is to introduce the relation between project performance and appropriate
knowledge management as well as organisational learning. The PDSA cycle and its
associated processes have been adopted, and then developed later on, for addressing
knowledge flow in project lifecycle (Owen, et al. 2004; Wiewiora, et al. 2010).
From a processes point-of-view, Kasvi, et al. (2003) propose four KM processes to
address KM activities in PBOs: 1) knowledge creation, 2) administration, 3) dissemination,
and 4) utilisation. As discussed earlier, numbers of models have been proposed to address
KM processes in functional organisations, as presented at Table 2-3. A comparison between
those models and the above mentioned KM processes reveals that they have some
similarities, however, “knowledge transfer” is the missing process which has not been
properly discussed by Kasvi, et al. (2003). In fact, knowledge transfer/share has been argued
as the most critical process of KM in functional organisations and, in particular, it is
recognised as the most important challenges in PBOs (Koskinen, et al. 2003; Owen, et al.
2004; Wiewiora, et al. 2010).
Due to the importance of knowledge transferring, the above mentioned KM processes
were developed by Owen, et al. (2004), in which four KM processes were proposed: 1)
creation, 2) capture, 3) transferring, and 4) reusing. In addition, these processes were
examined through employing Kotnour’s PDSA cycle in which PDSA was modified to PDSO
(Plan-Do-Study-Orient) and OODA (Observe-Orient-Decide-Act) (Owen, et al. 2004).
According to Owen, et al. (2004) the PDSO cycle addresses KM creation within a project,
Chapter 2 | LITERATURE REVIEW 27
while OODA cycle discusses knowledge integration at the organisational level. In other
words, PDSO deals with capture and creation of knowledge at operational level, i.e. projects;
in contrast, OODA discusses knowledge transfer from project to organisational level, i.e.
PMO or Project-base structure (Owen, et al. 2004). This model has been examined in
numbers of cases, and it has been adopted as one of the research premises, as discussed in
section 3.2.2 (Owen and Burstein 2005; Owen, et al. 2004).
From a KM practice point of view, knowledge transferring was investigated by
Wiewiora, et al. (2010) in which numbers of techniques and practices were examined, intra-
and inter- projects. According to Wiewiora, et al. (2010) informal face-to-face interactions
are the first KM practices to share knowledge in PBOs. The second and third KM practices
for knowledge transferring, are formal face-to-face interactions, and email (Wiewiora, et al.
2010). This study is the one of the latest studies that has considered project-based
organisations instead of functional organisation. However, knowledge transfer was the main
focus of their study and other KM processes have not been discussed by Wiewiora, et al.
(2010). This PhD project aims to cover this gap through discussing other KM practices, i.e.
creation, capturing, and reusing.
From a system point-of-view, a system theory approach has been discussed to address
the KM in a project environment (Davidson and Jillian 2009). According to Davidson and
Jillian (2009) the three following levels: operational, tactical, and strategic, should be
considered to develop appropriate KM processes and practices. It is obvious that processes
are not necessarily similar at each level, which indicates that various processes could be
developed at each level (Davidson and Jillian 2009). At an operational level, KM processes
should manage issues such as lessons learned, while in other levels, specifically the strategic
level, knowledge management most likely deals with integration of lower levels through
systematic interactions (Davidson and Jillian 2009). According to Davidson and Jillian
(2009) system theory has a significant role to facilitate the enrichment of knowledge
management within PBOs.
Table 2-7 KM initiatives and barriers in PMO (developed for this research)
Enablers of KM in the Project –base organizations
Barriers of KM in the Project –base organizations
Familiarity with KM Inappropriate Technology Appropriate Coordination Less management support
Incentives for knowledge efforts Weak contents of knowledge Appropriate systems for handling KM Project Management
Cultural support Cultural issues
As depicted in Table 2-7, there are numbers of initiatives and barriers of knowledge
management in PBO, which have been discussed in the current literature (Ajmal, et al.
28 Chapter 2 | LITERATURE REVIEW
2010). According to Ajmal, et al. (2010) knowledge management is an influential factor for
developing organisational competitive advantage, hence, it is important to recognise KM
initiatives, enablers and barriers in PBOs. This contributes to develop a reliable KM system,
by which PBOs could manage their project knowledge, and eventually improve their
competitive advantages.
According to Ajmal, et al. (2010) “incentives” and “appropriate KM system” have been
proposed as the most significant enablers of KM in PBOs, while “lack of proper
coordination” and “cultural issues” are known as the most important barriers. This means
that an appropriate KM system, which comprises processes, procedures, and technology,
significantly improves the management of project knowledge. In addition, improving
organisational culture and developing incentives, alongside management support, contribute
to the enhancement of project knowledge management (Ajmal, et al. 2010; Ajmal and
Koskinen 2008).
Challenges of knowledge management in project environments 2.4.3
As discussed earlier, KM in functional organisations is not similar to project-based
organisations (Koskinen and Pihlanto 2008). Hence, KM in PBOs should be investigated to
address appropriate practices to resolve the current challenges of KM projects (Bresnen, et
al. 2003; Koskinen and Pihlanto 2008; Owen, et al. 2004). In order to investigate KM in
project environments, initial attempts have focused on studying KM in single project, but
later on project environments and PBOs have chosen as the main context (Koskinen and
Pihlanto 2008; Kotnour 2000). The majority of the prior studies have strongly emphasised on
challenges of PBOs and projects from KM perspectives. Given the importance of knowledge
for project success, it is generally accepted that KM should be the major subject for research,
in order to address the current challenges of managing project knowledge (Koskinen and
Pihlanto 2008; Srikantaiah, et al. 2010). Following are some of recognised challenges and
issues of KM in project based organisations, which have been recognised in the current
literature:
• Knowledge leakiness & stickiness in projects (Brown and Duguid 1998), • Lack of KM initiatives in projects (Liebowitz and Megbolugbe 2003), • Difficulties of articulating individual knowledge (Koskinen, et al. 2003), • Lack of appropriate knowledge sharing and acquisition systems (Koskinen, et al.
2003), • Repetitive works or rework because of lack of effective knowledge reuse and
transferring system (Desouza and Evaristo 2006; Love, et al. 2003; Owen, et al. 2004),
• Lack of knowledge social networks as knowledge transfer initiatives (Walker and Christenson 2005),
Chapter 2 | LITERATURE REVIEW 29
• Lack of wisdom in projects because of inappropriate knowledge management systems in the project environment (Walker and Christenson 2005),
• Lack of learning and organisational learning in project environment (Kotnour 2000; Newell, et al. 2006),
• Poor system of collecting and assimilating lessons learned between and within projects (Goffin, et al. 2010; Newell, et al. 2006), and
• Lack of collaboration because of unsystematic KM in the project environment (Davidson and Jillian 2009).
As is can be inferred from the mentioned KM issues, there are numbers of recognised
gaps in the existing literature, from a KM point-of-view. As discussed earlier, PM maturity
models address the development of PBOs, however, KM has not been addressed in this
framework. In other words, PMMMs, as methodology for developing PBOs and PMOs,
should provide appropriate practices for developing PMOs from a KM point of view. In fact,
not only the existing PMMMs do not discuss the maturity from KM perspectives, but also,
they have just focused on development of PM practices. This gap will be discussed in the
next section to formulate the research problem.
THE RESEARCH PROBLEM 2.5
Problem Definition 2.5.1
According to Love et al. (2003) the cost of rework in Australian construction projects has
been about 35% of total cost, and 50% of total overrun cost. Poor knowledge management
has been recognised as one of the major causes for project inefficiency and/or failure (Love,
et al. 2003). This means that KM is an influential factor, which contributes to both reduce
project costs and improve project performance (Love, et al. 2003). In a consistent manner,
Owen, et al. (2004) emphasise the importance of project KM in project environments as the
critical factor to successfully fulfil the project’ objectives.
30 Chapter 2 | LITERATURE REVIEW
Figure 2-5 The development of PM and KM (developed for this research)
Both KM and PM were developed separately until 2000s. Since the late 1950s,
knowledge management studies have concentrated on addressing issues of managing
knowledge in functional organisations (Alavi and Leidner 1999; Schacht and Mädche 2013;
von Krogh, et al. 2012), while PM has been considered as an important approach in the last
three decades. Figure 2-5 presents a glimpse of PM and KM development in the last 50
years, and also it describes the recognised gap in the literature. As shown in the mentioned
figure, since the late 1990s the evolution of the PMO has been considered as one of the latest
developments of PM by which organisation could improve their competencies. According to
Liu and Yetton (2007), more than 50,000 organisations in the US have established or
developed their PMO since 2002 and they predict that in the near future the PMO will be an
inevitable part of organisational structure. PM Maturity Models (PMMM) have been recently
proposed to address both the development of PMO and, also, some of existing challenges
during PMO establishment (Kerzner 2013). In other words, PM maturity models contribute
to improve the maturity levels of PMO through recommending proper PM processes and
practices (Kerzner 2013; PRINCE2 Foundation 2008; Project Management Institute 2013).
KM has been broadly discussed, in functional organisations, to address appropriate
practices for developing organisational competencies. According to (Julian (2008); Kidwell,
et al. (2000); Pemsel and Müller 2012) there is a significant interest in applying knowledge
practices in the project environment, by which enterprise project management could be
developed, however, Leseure and Brookes (2003) believe that KM systems are a critical
1950s
1990s
2000s
1970s
Chapter 2 | LITERATURE REVIEW 31
challenge for the development of project environments. This has been discussed by a number
of authors to address various aspects of project knowledge management (Bakker, et al. 2011;
Julian 2008; Lindner and Wald 2011; Pemsel and Wiewiora 2013; Rose 2013; Schacht and
Mädche 2013). Anecdotal data indicates that since 2003, numbers of studies have been
conducted to discuss the management of project knowledge to both discuss the crucial role
of KM in projects, and accentuate addressing KM in the project environment (Arora, et al.
2010; Aubry, et al. 2007; Bresnen, et al. 2003; Koskinen and Pihlanto 2008; Liu and Yetton
2007).
As mentioned is section 2.3.4, the PMO is responsible for coordinating all project
activities within organisations, specifically managing the inter/intra project activities
(Kerzner 2009). Despite the fact that some of the PMO’s issues have been discussed in the
literature, however, there is still some obvious lack of studies to address gaps in PMOs
(Aubry, et al. 2011; Aubry, et al. 2010). In other words, the PMO and proposed maturity
models (PMMM) have not been critically investigated to address the current challenges in
the existing literature. On the other hand, knowledge is an important factor for project
success (Koskinen and Pihlanto 2008). This means that addressing project knowledge
management is an inevitable part of the PMO’s responsibility. In other words, PMO should
address “the integration and management of project knowledge during five phases of
project life cycle: Initiation; Planning; Executing; Controlling & Monitoring; and
Closing”. However, the current PM maturity models are yet to address project KM in
various levels of maturity.
To the best of this researcher’s knowledge, few studies have investigated the role of KM
practices in the PMO. Particularly, the existing PMMMs have not addressed the maturity of
the PMO from a KM point of view. In addition, there appears to be no criterion or measure
to examine the maturity level of PMO from KM perspectives. The research problem is:
“The absence of knowledge management processes and practices in various
maturity levels of the PMO”
The Research Aim 2.5.2
The aim of this study is “To Integrate KM practices in each maturity level of the
Project Management Office”. This aim will be fulfilled through developing and proposing
a comprehensive framework by which KM processes and practices are addressed in various
maturity levels of PMO. This framework will address appropriate KM practices to assist
project stakeholders during the project lifecycle. In addition, this framework will expedite
knowledge flows between project and organisation in order to enrich organisational
knowledge-bases. Moreover, the proposed framework will address some of the current issues
in the PMO, such as lessons learned and knowledge leak.
32 Chapter 2 | LITERATURE REVIEW
The Significance of Research 2.5.3
As discussed, the existing PM maturity models do not address the maturity of PMO from
KM point of view. This research aims to address this gap through developing a
comprehensive KM framework. It is anticipated that this framework will address the
required KM practices/processes for each level of the PMO and integrate the KM in the
various levels of PMO. In addition, this framework shall propose numbers of criteria for
assessing the PMO maturity from a KM point of view, as shown at Figure 2-6. The research
contributions are:
• Developing a framework to address KM practices in the current PMMM, and
• Proposing new criteria to assess the maturity of the PMO from a KM point of
view.
Previous attempts to develop the PMO maturity
model
The research contributions
Figure 2-6 The significance of this Research (developed for this research)
The findings of this research shall contribute to improving the efficiency of organisational
project management, and ultimately the organisations’ competitive advantage. Also, this
research shall provide original insights about the role of KM in the PMO to improve
performance and the Project Management Office (PMO).
The Research Questions 2.5.4
According to Yin (2003), defining the research question(s) is one of the most important
steps in the research projects. In fact, the research questions determine the research
objectives, the research design, and also data collection methods (Yin 2009). In order to
The PMO Maturity
Model
Organizational Structures
Project Management
Methods
Maturity Model Approach
Process-based model
Lack of KM Practices
Proposing new Criteria to assess the maturity of the
PMO from KM point of view
Developing a framework to address KM practices for each maturity level of the
PMO
Chapter 2 | LITERATURE REVIEW 33
achieve the research aim, and the above-mentioned contributions, three main questions have
been defined, alongside their associated sub-questions as follows:
1) To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from a KM perspective?
1.2. What types of knowledge are required at each phase of project lifecycle?
1.3. What kinds of KM practices are utilised in each maturity level of PMO?
2) How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project?
2.2. How PMO can contribute to managing the project Knowledge?
3) How can knowledge be integrated in the PM Maturity Model? 3.1. How is knowledge created, captured, transferred and reused in PMOs?
3.2. How can KM practices be employed in each maturity level of the PMO?
The first and second questions will be answered through a case study method, while the
third question will be responded to through both cross-case analysis and development of a
comprehensive framework.
The Research Objectives 2.5.5
Three research objectives have been proposed to make appropriate links between research
questions and the research aim, as follows:
• To analyse the role of KM practices in various maturity levels of PMO To explore challenges of KM in project base organisations (PBOs)
To recognise the required types of knowledge at each level of maturity
To analyse the utilisation of KM practices in the PMO
• To explore the contribution(s) of PMO for managing project knowledge To understand the characteristics of utilised KM practices in various levels of the PMO
To explore the importance of KM processes and practices in the PMO
To analyse the contribution of the PMO from a KM perspective
• To develop a framework to address KM in various maturity levels of PMO To define the required KM practices for each level of the PMO maturity
To integrate KM processes/practices in each level of the PMO maturity
To develop a theory(s) and framework for addressing KM practices in PMMM
To propose appropriate criteria for each level of the PMO from a KM perspective
It is anticipated that achievement of the above-mentioned objectives will contribute to the
development of a theoretical framework.
The Research limitations 2.5.6
The focus of this research is to investigate KM in PMOs where the PMO is considered as
a unit or department in the organisational structure. However, the interactions of PMO with
34 Chapter 2 | LITERATURE REVIEW
other business units, in terms of KM activities, will not be considered during the course of
this investigation. In addition, PMBOK has been adopted as the PM methodology in this
study, alongside Kerzner’s model as a PMO maturity model. This means that the findings of
this research might be useful for those selected frameworks mentioned. Furthermore, the
outcomes of this research will address KM practices in PMOs, however, they could be more
likely applicable for other project environments such as single project or Project Based
Organisations (PBO). Also, this research aims to study KM activities from a process point-
of-view rather than from technical and IT perspectives. This means that the IT aspect of KM
will not be discussed in this study and it could be considered for further research.
The Research Purposes 2.5.7
The research will investigate KM practices for each level of PMO maturity, and identify
multiple criteria to assess the PMO maturity from a KM perspective. The research findings
will be useful for a numbers of organisations and individuals, as shown in Table 2-8:
Table 2-8 The benefits of study findings (developed for this research) Targets for research
benefits Contributions from research
Functional Organizations that
intend to establish their PMO
Understanding the role of KM in their PMO development; Implementing and developing the PMO by considering new KM practices;
and Utilising proposed KM practices for each level of the PMO maturity.
Project-based Organisations
Employing appropriate KM practices for their organisations; Understanding the role of KM in their environment; and
Developing their PMO and customising proposed KM practices.
The established/developed
PMOs that seek improvement
Assessing the existing level of PMO from a KM perceptive; Improving the maturity level of PMO and employing appropriate KM
practices for each level; Developing performance of PMO by integrating and collaborating KM
practices.
The PMO and PM consultants
Developing and Assessing the existing level of PMO from a KM perspective,
Employing appropriate KM practices to respond the gap of poor KM practices in PMO; and
Understanding the role of KM in the PMO to develop the road map from a Km point-of-view.
The proposed framework will contribute to improve knowledge management in PBOs at
all levels of PMO maturity.
CONCLUSION 2.6
Both knowledge management and project management are recognised as crucial factors
for developing organisational competitive advantages (Alavi and Leidner 2001; Kerzner
2009). These two disciplines were separately developed until knowledge management was
recognised as a promoter of project success (Koskinen 2000). The convergence of PM and
KM has become more important, when both were identified as critical organisational
competencies. In addition, the evolution of PMO, as a reliable approach for institutionalising
Chapter 2 | LITERATURE REVIEW 35
PM methodologies within an organization, has led to the development of maturity models to
address PMO’s improvement. This research recognised that current PM maturity models are
yet to be addressed from KM perspectives, and this important gap was chosen as the subject
of this study.
In order to find solutions for the recognised gap, research problem, questions and
objectives, alongside the contribution and significance of this study, have been defined
accordingly. To fulfil the proposed objectives, a framework is required to support the process
of exploring KM in PMOs. In other words, this framework should create a scaffold for the
investigation, by which the collected data should be analysed. In the next chapter, the
proposed framework will be discussed in detail.
36 Chapter 3 | The Conceptual Framework
Chapter 3
THE CONCEPTUAL FRAMEWORK
INTRODUCTION 3.1
This chapter presents the proposed research framework through a discussion of underlying
premises, components, and ultimately, the rationale for developing this framework. The
preliminary framework will be utilised as a guide for gathering and organising data then it shall
be refined and revised after analysing the collected data.
First, a succinct presentation of current discussions will be followed by a theoretical
foundation of the preliminary framework. Second, the framework’s premises, key terms, and
definitions will be presented. Third, the developed framework will be discussed through
elaborating the theoretical and/or empirical underpinning of the proposed relationships among
its components. Finally, concluding remarks will be presented.
THEORETICAL BACKGROUND 3.2
Knowledge management processes in project environments 3.2.1
People, technology and process are three core components of KM at both functional and
project-based organisations (Davenport 2013; Davenport and Prusak 2000). From a process
point of view, KM is defined as “a systemic and organizationally specified process for
acquiring, organizing and communicating both tacit and explicit knowledge of employees so
that other employees may make use of it to be more effective and productive in their work”
(Alavi and Leidner 1999). Knowledge Management (KM) has been recognised as a critical
factor for both organisational performance and project success (Bakker, et al. 2011; Koskinen
and Pihlanto 2008; Kotnour 2011; Kotnour 2000; Nonaka and Takeuchi 2011). KM in
functional organisations is not similar to project-based organisations since projects are
temporary and teams are disbanded or members leave after project completion (Eriksson 2013;
Gasik 2011; Kasvi, et al. 2003; Schacht and Mädche 2013). In other words, the temporary
nature of projects imposes some issues such as “reparative activities”, “leaking of project
knowledge”, and “reworks” for projects and project-based organisations (Ajmal, et al. 2010;
Desouza and Evaristo 2006; Koskinen and Pihlanto 2008; Love, et al. 2003).
From a process point-of-view, KM is defined as a systematic process of acquiring, capturing,
communicating, and transferring the knowledge of employees to increase their productivity and
organisational competencies (Alavi and Leidner 2001; Gajic and Riboni 2010; Kasten 2010). A
model proposed by Newman and Conrad (2000) introduces four major processes for KM as
Chapter 3 | The Conceptual Framework 37
knowledge creation; retention; transfer; and utilisation, and called this model the “General
Knowledge Model (GKM)”. This model was adopted and developed by Owen and Burstein
(2005) in the project environment context through four KM processes: Creating; Capturing;
Transfer/Sharing; and Reusing (Owen and Burstein 2005). In their study, knowledge
“Retention” and “Utilisation” have been changed, respectively, to knowledge “Capturing” and
“Reusing” and they have kept both “Creation” and “Transferring” in their proposed KM
framework, as depicted at Figure 3-1 (Owen and Burstein 2005). This knowledge process model
has been examined in a number of studies at various project management contexts and it is
claimed that it is valid enough to be considered in any project environments (Morales-Arroyo, et
al. 2010).
Figure 3-1 KM process at project-based organisation (Owen, et al. 2004)
The mentioned framework comprises four KM processes that are interconnected to one
another (Owen and Burstein 2005). According to this model, knowledge is created through
knowledge transferring, while knowledge is transferred by utilising the captured knowledge. In
addition, knowledge is captured from two processes: reusing and creation. This means that after
creating knowledge, a robust system is required to capture that knowledge in order to transfer it.
Moreover, this model addresses the fact that knowledge reusing is dependent on knowledge
transferring and, ultimately, knowledge capturing. In other words, if the knowledge capturing is
not robust, then, knowledge cannot be properly transferred and reused. Also, transferring
knowledge directly impacts on knowledge creation. This knowledge process model has been
examined in a number of studies in various project management contexts and it is claimed that it
is valid enough to be considered in any project environments (Morales-Arroyo, et al. 2010).
Also, this model is the only KM process model that has been developed and examined in a
project environment. Due to the validity of this model, it was adopted as one of the research
premises.
Knowledge management processes in project lifecycle 3.2.2
Project knowledge should be managed during project phases (Eriksson 2013; Owen and
Burstein 2005; Wiewiora, et al. 2009b). According to Owen and Burstein (2005) the most
important knowledge management activities should be undertaken at initiation, planning, and
execution and monitoring phases, while at the closing phase only knowledge capturing is
38 Chapter 3 | The Conceptual Framework
required. In other words, in the three mentioned phases, i.e. initiation; planning; and execution
& monitoring, all KM processes should be utilised, however, at the closing phase only the
knowledge capturing process should be managed. Table 2-4 illustrates the mentioned discussion
to clarify where KM resides in various phases of project. This model has been employed and
validated by numbers of studies in project management contexts, so it has been adopted as
another premise of the research framework.
Table 3-1 Project phases and KM Processes Adapted from (Owen and Burstein 2005)
Initiation Planning Execution & monitoring Closing
Knowledge Creation √ √ √ Knowledge Capturing √ √ √ √
Knowledge Transferring √ √ √ Knowledge Reuse √ √ √
Tacit and explicit dimensions of knowledge at project environment 3.2.3
Tacit knowledge is a crucial factor for project success and resides in a project’s stakeholders’
minds, while explicit knowledge refers to the codified and articulated knowledge that exists in
project documents and databases (Goffin, et al. 2010; Koskinen and Pihlanto 2008; Srikantaiah,
et al. 2010; Teerajetgul and Chareonngam 2008). Knowledge is created in projects but the
challenge is to capture it, and then make it reusable for various purposes, such as applying to
similar projects and transferring to project team members (Kasvi, et al. 2003). One of the aims
of KM is to provide a comprehensive system for transforming tacit knowledge to the explicit in
which it could be transferred and then utilised for various purposes (Alavi and Leidner 2001;
Nonaka and Takeuchi 1995; von Krogh, et al. 2012). Since tacit knowledge exists in
individuals’ mind, organisations try to employ appropriate KM systems for transforming it to
explicit knowledge. In order to cope with individuals’ resistance, organisations manage this
issue through numbers of ways, such as improving organisational culture and developing proper
systems to change human behaviour (Kasvi, et al. 2003).
In the project context, tacit and explicit knowledge exist in numbers of formats or states such
as; technical knowledge, costing knowledge, and knowledge about clients (Anand, et al. 2010;
Anbari 2005; Arora, et al. 2010; Christensen and Bang 2003). These types of knowledge are
mainly owned by project team members, who rarely aim to share with others, therefore such
knowledge could be lost when project teams are disbanded (Koskinen and Pihlanto 2008).
“Knowledge leakiness and stickiness” has been recognised as one of the major challenges for
PBOs (Love, et al. 2005). According to Love et al. (2005; 2003) poor KM is the main cause of
more than fifty percent of the “cost of rework”, in selected Australian major projects. According
to the current literature, lack of appropriate KM practices to transform tacit knowledge to
explicit knowledge is a major challenge for PBOs (Ajmal and Koskinen 2008; Koskinen and
Chapter 3 | The Conceptual Framework 39
Pihlanto 2008). The development of a KM system in a project environment could contribute to
the address of some of the current issues, such as reworks.
PMBOK and knowledge management 3.2.4
From a PM point of view, there are two types of knowledge in project-based environments:
1) project management knowledge of (KPM) and 2) knowledge of application area or domain
DM) knowledge (Kasvi, et al. 2003; Project Management Institute 2013). According to
PMBOK (2013) PM practices address the required knowledge to manage projects activities,
while the domain knowledge pertains to the required technical knowledge necessary for
carrying out the project. The PM knowledge is addressed by PM standards and methodologies
such as PMBOK, and PRINCE2, by which numbers of practices and processes are advised to be
utilised during the project life cycle. Domain knowledge is the incorporation of specific
technical knowledge to accomplish project activities (Kasvi, et al. 2003). The knowledge and/or
experience of the integrating of both PMK and DK are important factors in delivering a
successful project (Kasvi, et al. 2003; Koskinen and Pihlanto 2008; Project Management
Institute 2013). In fact, project managers are responsible for the integration of PMK and KM,
through which the success of project is increased (PRINCE2 Foundation 2008; Project
Management Institute 2013).
Table 3-2 KM objects of PMBOK (Reich and Wee 2006)
Type Count Explanation
Total processes 44 The 4th edition of PMBOK comprises of 44 processes which
contains 70 unique inputs and outputs.(Recently in the 5th edition 4 more processes have been included)
Knowledge objects 48 48 Out of 70 input/outputs deal with knowledge management
Explicit/Tacit knowledge 47/1 Majority of knowledge objects are explicit There is only one
object, Enterprise Environmental Factor, contain tacit knowledge
Processes deal with Tacit KM 19 19 out of 44 processes are related to tacit KM and they are
mainly referring to “expert judgment”
As discussed in section 2.3.3, PMBOK is the adopted PM methodology for this research and
it is reviewed and developed every four years. In the latest version of PMBOK 5th five phases
and 10 knowledge areas have been addressed, as shown in Table 2-3. In fact, it guides what
processes should be used at what project phase. For instance, at the initiation phase, PMBOK
recommends two processes: 1) developing the project charter, and 2) Identifying stakeholders.
In PMBOK, knowledge is created from the initial steps of the project to the closing phase
(Reich & Wee, 2006). From a KM point of view, a study was conducted to investigate all
processes and practices in PMBOK 3rd, in order to examine tacit and explicit dimensions of the
existing knowledge objects (Reich & Wee, 2006). According to Reich and Wee (2006) in
PMBOK 47 out of 48 knowledge objects deal with explicit knowledge, while only one object
discusses management of tacit knowledge, as depicted in Table 3-2. This means that PMBOK
40 Chapter 3 | The Conceptual Framework
has a strong bias toward explicit knowledge through some recommendations for documentation
of project knowledge. In other words, KM practices and specifically, the management of tacit
knowledge, are yet to be addressed in PMBOK (Reich and Wee 2006).
Methods of transforming Tacit to Explicit knowledge 3.2.5
Appropriate utilisation of tacit knowledge is the key for project success (Goffin, et al. 2010;
Koskinen and Pihlanto 2008; Teerajetgul and Chareonngam 2008). Therefore, the
transformation of tacit knowledge to explicit knowledge is a crucial process during a project
lifecycle. In order to develop a system to manage the mentioned transformation, both PM and
organisational cultures play an important role (Ajmal and Koskinen 2008; Davidson and Jillian
2009). This means that two major factors should be considered to develop a KM system: 1) The
maturity PM maturity level organisations, and 2) the culture of organisation from a KM
perspective. Understanding the characteristics of tacit and explicit knowledge is an important
factor for establishing effective practices to transform tacit knowledge to explicit knowledge
(Goffin, et al. 2010). According to Srikantaiah, et al. (2010), various formats and states of both
tacit and explicit knowledge in PBOs, could be categorised as shown in Table 3-3.
Table 3-3 Knowledge types in project context (Srikantaiah, et al. 2010) Tacit knowledge
exists in Explicit knowledge
resides in Methods of transforming Tacit
knowledge to explicit • Face to face
communication - formal and/or informal
• Telephone Conversation - formal and/or informal
• Virtual communication& meetings
• Presentations& video conferences
• Mentoring and Coaching • Study tours • Training • Client knowledge • Best Practices
• Publications and books
• Internal records • Sound/video
recording • Map &graphical
material • Data Warehouses • E-mails • Internet • Intranet • Self-study materials • Newsletters • Groupware
• Formal & informal meetings, networking
• Developing community of practices • Interviews and videotaping • Subject matter experts directories
and/or yellow page • Knowledge /information
repositories • After action review/ project
milestone review • Mentoring programs • Knowledge maps • Requiring strategies • Retention strategies
In order to implement and develop these practices, different levels of capability are required
(Srikantaiah, et al. 2010). In other words, the development of proposed KM practices depends
on a number of factors such as organisational culture, individuals’ behaviour, the existing
systems and processes, and existing information technology infrastructure (Christensen and
Bang 2003; Desouza 2006; Diakoulakis, et al. 2004; Leidner, et al. 2008). This means that
organisational readiness is a critical factor for successfully implementing such a KM system
(Davidson and Jillian 2009). These practices will be used to develop the KM process models, as
discussed in section 3.5.2.
Chapter 3 | The Conceptual Framework 41
Project management maturity model 3.2.6
Project Management (PM) is an application of knowledge, skills, tools, and techniques to
meet project objectives (Project Management Institute 2008a). The Project Management Office
(PMO) is a relatively new function in organisations, to develop, oversee and maintain project
management activities (Project Management Institute 2013; Spalek 2012). PM Maturity Models
(PMMM) have been proposed to address the development of PMOs (Hsieh, et al. 2009;
Kankanhalli and Pee 2009; Kerzner 2005). A number of PMMMs have been developed to
address associated practices to establish the PMO, such as, Organizational Project Management
Maturity Model (OPM3), Portfolio Program Project Management Maturity Model (P3M3), and
3) Kerzner’s PMMM, as discussed in the section 2.3.5. The Kerzner’s PMMM has been utilised
by many organisations and it’s known as one of the more reliable PMMMs, which could be
used with most of the PM methodologies. As explained, Kerzner’s PMMM has been adopted as
other premises of this research, and it will be discussed in the next section.
Kerzner’s Maturity Model 3.2.6.1
The Kerzner’s PMMM (K-PMMM) proposes a step-by-step methodology to address the
specific processes and procedure at each level of maturity. It addresses the development of
PMBOK in PBOs in five levels of maturity: 1) common language, 2) common process, 3)
singular methodology, 4) benchmarking, and 5) continuous improvement (Kerzner 2005;
Kerzner 2013). As shown at Figure 3-2, the first level of maturity, which is called “common
language”, the importance of PM has been raised and, also, the need for developing a common
language for PM among project team members is becoming apparent. In other words, not only
do project team members not use the same jargon, so as to be understood by others, but also
there is no PM methodology in place to address basic processes of managing projects. This
means that projects: 1) are hero driven, 2) do not follow a certain method, and 3) are faced with
numbers of challenges (Kerzner 2013)
Figure 3-2 Kerzners’ Maturity Level (2005)
After implementing and developing basic PM processes, which are utilised by project team
members as a common language, the maturity of PBO is elevated to level two or “Common
Continuous Improvement
Common processes
Singular methodology
Benchmarking
Common Language
Level of Maturity
Com
petitive advantages
Level 5
Level 4
Level 3
Level 2
Level 1
42 Chapter 3 | The Conceptual Framework
Process”. At this level, there are some basic processes to address fundamental PM practices,
such as time and cost management, for managing project activities. Also, senior managers have
realized the importance of PM so they support the development of the PMO to reach the upper
levels of maturity (Kerzner 2005).
At the third maturity level, a comprehensive PM methodology should be utilised as the
“Singular Methodology” among all project team members. This means that the PMO has
developed the previous PM standard to the level at which both basic and some of the advanced
PM practices have been properly addressed. In other words, PBOs has gone to the level that: 1)
all utilised PM practices have been integrated at one PM standard, 2) all various PM
methodologies have been combined in one organisational-wide PM methodology, 3) Project
team members actively adhere to the developed PM standard (Kerzner 2005).
At the “Benchmarking” stage, the fourth level, the focus is to both improve the current PM
processes and, ultimately, address all knowledge areas of PMBOK. This means that PBOs have
been achieved to a level in which all PM processes have been integrated at an organisational
level and, therefore, projects could be interrelated to organisational strategies (Kerzner, 2005).
And eventually, the fifth level is called “Continuous Improvement” in which the PM
methodology is continuously improved through “benchmarking information” and the main
focus of this is to enhance the organisational competitive advantages (Kerzner 2005).
In summary, K-PMMM addresses various PM practices at different levels of maturity by
which PBOs could both develop the basic requirements for the specific level, and prepare
prerequisites to achieve the next level of maturity. It also comprises a number of criteria to
dynamically assess the quality of PM. The aim of utilising the K-PMMM is to develop the
organisational capabilities and culture in order to incorporate PM practices in organisational
processes and procedures (Kerzner 2005). In addition, it is a road map to address practices,
based upon the status of PM functionality, for enhancing organisational competencies from a
project management point of view. However, this framework, similar to other PMMMs, is yet to
be addressed from a KM perceptive.
Knowledge Management Maturity Model 3.2.7
Similar to PMMM, a KM Maturity Model (KMMM) is an accepted framework to
progressively develop a KM system in organisation (Feng 2006; Kankanhalli and Pee 2009).
KMMM contributes to the improvement of KM activities through both formulating the
development of a KM system, and assessing the effectiveness of the existing KM activities
(Feng 2006). There are numbers of proposed KMMMs in the existing literature to adopt and
follow for undertaking the journey of KM system development (Desouza 2006; Feng 2006;
Hsieh, et al. 2009). A study was conducted by Feng (2006) to investigate the current KMMMs
and then develop a comprehensive KMMM. At its conclusion, this study advised the three
Chapter 3 | The Conceptual Framework 43
following criteria to select appropriate KMMMs:1) objectives to be attained at each maturity
level, 2) KM practices and processes, and 3) KM enablers. This means that there are three
practices that are recommended to be considered before adopting any KMMM. At first, the
objective of developing such as KM system, should be defined as the ultimate aim to be reached
at each level of maturity. Second, a set of processes and practices are required for satisfying
determined criteria. KM processes comprise a number of practices by which inputs, such as tacit
or explicit knowledge, create some outputs, such as explicit knowledge, through utilising some
tools and techniques. Third, the enablers are those tools, technologies or systems which both
facilitate the KM processes and contribute to objective satisfaction.
In addition, an integrated KMMM was developed by Feng (2006) to address the
development of a KM system in five levels of maturity, as shown in Table 3-4. In the proposed
framework, four KM processes: Creation, Storage, Sharing and Application, have been
discussed at five levels of maturity. This model discusses the improvement of this KM system
through: 1) defining the objective for each level of maturity and expectations from a KM point
of view, 2) proposing appropriate KM practices that should satisfy associated processes, 3)
addressing proper tools and enablers that support each of the KM processes, 4) illustrating the
required structure at each level of maturity, 5) proposing criteria to assess the maturity level
(Feng 2006).
In the mentioned model, two types of enablers are discussed, i.e. structure, and science and
technology. Organisational structure plays an important role for managing knowledge, hence,
certain requirements should be met to achieve each level of maturity. For instance, at the third
level of maturity it is recommended to develop a KM unit within the organisational structure for
taking on the responsibilities of KM. Also science and technology are introduced as crucial
enablers for KM systems, specifically at upper levels, by which KM is facilitated and elevated
(Feng 2006). In this framework, the first three levels of maturity are the most important stages
for preparing a robust KM system, while the fourth and fifth levels focus on both improving and
maintaining previous levels’ achievements through developing some systems and practices for
auditing and measuring the performance of the KM system.
44 Chapter 3 | The Conceptual Framework
Table 3-4 KM maturity model, proposed by Feng (F-KMMM) (Feng 2006)
KK Maturity
KM Processes Creation Storage Sharing Application
First level • At this stage required preparation works are undertaken and KM processes and practices should be defined and planned
Initial activities
• SWOT analysis, Feasibility study and requirements analysis • KM concepts definition, Challenges against KM, KM evaluation for organisation
Second level
• Valuing knowledge creation
• Respecting to the originality of K.
• Developing K. documentation
• Developing repository systems
• Facilitating informal communication
• Developing process to reuse existing knowledge
Enablers and tools
• Learning tool • Plot assistant design • Simulation Software • Brain and thinking
support systems
• Electronic notice board
• Document edit S/W
• Database
• Electronic notice board • Video Conference
meeting • Email and Chat room
• Interface design S/W
Common initiatives and
tools
• Defining the concept of KM in practice • Developing Internet, Intranet and any types of networks in organisation • Developing community of practices
Third level
• Developing K. creation strategies
• Establishing formal K. creation
• Developing processes for refining K.
• K. conformity check
• Storing K. in suitable place
• Establishing and developing formal channels for sharing K.
• Education and Training • Enhancing the security
of K. sharing
• Developing systems to support K. application
• Dividing the work areas to related functions
Enablers and tools
• Data mining • Documentation
Search • Knowledge detection
tools • Idea implement
assistant tools • Case-based reasoning
systems • Pattern simulation • Concurrence
filtration systems
• Data Repository • Data storage • File management
systems • Case-based
reasoning systems • FAQ • Work process
systems • Expert systems
• Search engine • Knowledge list • Knowledge map • Content-based original
search • Online learning systems • Expert yellow page • Expert training systems • Regular seminar and
workshops
• Expert systems • Work process
systems • Online prompt
analysis • Decision support
systems
Common initiatives and
tools
• Establishing a unit to take the responsibility and accountability of KM • Systematically Supporting KM • Establishing and developing standard for KM • Developing KM sub processes
Fourth level of KMM
• Developing the K. creating sub-processes
• Developing the K. storage sub-processes
• Developing the K. sharing sub-processes
• Developing K. app. sub-processes
Enablers and tools
• Measuring the K. creating success
• Measuring the K. storage success
• Measuring the K. sharing success
• Measuring K. application success
Common initiatives and
tools
• Measuring the success of KM through indexes and Critical success factor (CSF) • Measuring the success of KM sub-processes • Putting control in place for all KM processes and activities • Developing an Audit unit for measuring the KM
Fifth level of KMM
• Continuously improving the KM processes and procedures • Developing the KM control and audit systems and unit • Integrating the KM processes and procedures
Enablers and tools
• Developing and research Unit in the KM department • Developing a Decision making unit in the KM department
45 Chapter 3 | The Conceptual Framework
The F-KMMM has been examined and then refined by Feng (2006) in a couple of
organisations, such as a commercial bank and a governmental organisation. It is believed that
this model could be utilised as a reliable benchmark for developing an organisational KM
system (Feng 2006). However, to the best of this researcher’s knowledge, F-KMMM has not
been investigated in any PBOs, specifically in the PMO. Since F-KMMM has not been
examined in the PBOs, in the next step it is compared to other existing KMMMs to make sure
that it is valid enough to be utilised in the research framework. One of the latest KMMMs,
which is valid enough to use at all types of organisations, is General KMMM or G-KMMM
(Kankanhalli and Pee 2009). According to Kankanhalli and Pee (2009), G-KMMM could be
adopted by both functional and PBOs to improve KM through the following level of maturity:
1) Initial, 2) Aware, 3) Defined, 4) Managed, and 5) Optimising, as illustrated in Table 3-5. The
G-KMMM comprises three KM players: People, Process, and Technology to address the
following:
• What are the expectations at each level of maturity,
• How should process and technology be implemented at each level of maturity,
• How should organisations prepare the people side of KM at each level,
• How should KM processes be integrated with organisational processes, and
• How should KM players be collaborated?
Despite the fact G-KMMM does not discusses proper KM practices at each level of maturity,
it provides useful indications to address expectations from each level. Also, it covers the people
side of KM, which is not the scope of this study. This means that this research aims to focus on
“Process” and to some extent “Technology” sides of KM players, therefore, “People” will not
be covered in this research.
According to Kankanhalli and Pee (2009) their proposed framework, G-KMMM, has been
examined in a number of organisations and they have concluded that it could be adopted by any
types of organisations in order to develop the KM system. In addition, an assessment method
has been developed in this framework to evaluate both the existing KM system and the
effectiveness of implementing KM practices. In general, it is claimed that G-KMMM is robust
and comprehensive enough to be employed by any organisations in improving their KM
practices (Kankanhalli and Pee 2009).
Generally speaking, G-KMMM is more comprehensive since it addresses all KM players,
but F-KMMM mainly focuses on the processes of KM in various levels of maturity. Also,
research findings confirm that not only there is no major difference between these two
frameworks, but also, they could be utilised as complementary methods. For instance, it was
realised that G-KMMM KM practices have not been specifically addressed, while in F-KMMM
46 Chapter 3 | The Conceptual Framework
it is the opposite. Therefore, the amalgamation of both models could create a comprehensive
KMMM.
Chapter 3 | The Conceptual Framework 47
Table 3-5 General KMMM (Kankanhalli and Pee 2009)
Maturity Level
General Description
KM Players People Process Technology
Initial
• Little/ no intention to formally manage Organizational K.
• Organization and employees are not aware of the need to formally manage knowledge
• No formal processes to manage organizational knowledge(K)
• No specific KM technology or infrastructure in place
Aware
• Organization has the intention to manage its organizational knowledge
• Management is aware of the need for formal KM
• K. is indispensable for performing routine task is documented
• Pilot KM projects are initiated, but not necessarily by Management (Mgmt.)
Defined
• A basic Infrastructure to support KM has been put in place
• Mgmt. is aware of its role in encouraging KM
• Providing training on KM • Developing KM strategy • Defining Individual KM
roles • Developing incentive
system
• Formalising processes of content info. Mgmt.
• Measuring the KM utilisation on organisational productivity
• Basic KM Infrastructure in place (e.g. single point of access)
• Some enterprise-level KM projects are put in place
Managed
• KM initiatives are well established in the organization
• Common strategy & standardised approaches towards KM
• Incorporating KM into organizational strategy
• More advanced KM training
• Quantitative measurement of KM processes (i.e., use of metrics)
• Enterprise-wide KM systems are in place
• Usage of KM systems is at a reasonable level
• Seamless integration of tech. architecture
Optimizing
• KM is integrated into organization & is continually improving
• It is an automatic component in any organizational processes
• Culture of sharing is institutionalized
• KM processes are constantly improved
• Existing KM processes are adapted to meet new business req.
• KM procedures are an integral part of the organization
• Existing KM infrastructure is continually improved
To the best of this researcher’s knowledge both G-KMMM and F-KMMM have not been
examined in any PBOs and, consequently not in PMOs. In other words, incorporation of KM
maturity models in PBOs is yet to be discussed in the current literature. Hence, KM is the
missing part in project environments and needs to be appropriately discussed.
CONCEPTUAL FRAMEWORK PREMISES 3.3
This section aims to clearly present the research domains, theories and assumptions to build
up the research framework. This framework was developed based on the above mentioned
discussions and comprises some adopted models or assumptions.
Types of the required knowledge 3.3.1
After thoroughly studying the current literature, eight types of knowledge have been chosen
in the research framework, as depicted in Table 3-6. This classification of knowledge is part of
the theoretical framework, which is being examined in selected case studies in order to analyse
the importance of each type of knowledge at various maturity levels of PMOs. In addition, it
48 Chapter 3 | The Conceptual Framework
was assumed that all forms of knowledge could have tacit or explicit dimensions. Table 3-6
depicts this classification and illustrates them from tacit and explicit points of view.
Table 3-6 Types of knowledge in research framework (developed for this research)
Types of knowledge Tacit or Explicit knowledge Project Management
Knowledge PMK are addressed in standard (explicit) also, exist in PM’s experience
(tacit ) so It could be both tacit and explicit Knowledge about
Processes/procedures Procedures and processes generally are addressed through instructions
and manual, so, it is more explicit than tacit
Technical Knowledge Technical knowledge could explicit , however, their application is
important which reside in people’s mind, so it is assumed that it is more tacit knowledge
Knowledge about Clients This type of knowledge is more tacit since it is not easy to codify all of relations with clients.
Costing Knowledge Costing happens through documents but this type of knowledge is more explicit.
Legal and Statutory Knowledge
Documentation of laws and regulation is essential, therefore, this knowledge is more explicit knowledge and obtained through
documents. Knowledge about Supplier Similar to knowledge about client, it has a tacit nature of knowledge
Knowledge of Who Knows What
If organization has a good system to recognize and capture address knowledge owners it could be explicit, otherwise it is tacit
Knowledge Management Processes in PMOs 3.3.2
From a process point-of-view, the proposed KM processes by Owen et al. (2004) have been
adopted in the research framework. As shown at Figure 3-3, it is assumed that there are four
processes for managing knowledge: 1) creation; 2) capturing; 3) transferring; and 4) reusing. In
addition, it is assumed that knowledge is generally created in PMOs but the first priority is to
capture the current knowledge. This means that without proper knowledge capturing,
knowledge reusing and transferring will be problematic. Also, it is assumed that there is a strong
relationship between knowledge transferring and reusing. In the research framework, knowledge
reusing will not properly conducted without appropriate knowledge transferring. And finally,
new knowledge is created through proper knowledge transferring.
Figure 3-3 The research KM processes model (developed for this study)
KM practices are defined as methods, tools or activities to support and facilitate the KM
processes (Ajmal, et al. 2010; Alavi and Leidner 2001; Bredillet 2008). Since KM practices
have various functionalities, KM sub-processes were defined to inter-relate KM practices to KM
Chapter 3 | The Conceptual Framework 49
process, as shown in Figure 3-3 and Figure 3-4. In other words, the KM sub process connects
similar KM practices to KM processes. Consequently, for each KM process, specific practices
were adopted, through which KM is facilitated and applied accordingly.
Figure 3-4 KM process and practices model (developed for this research)
In the research framework, each KM process entails some sub-processes by which KM
practices are correlated to the KM process. For instance, knowledge capturing comprises four
sub processes: Identification, Storing, Classification and Selection. In addition, knowledge
identification has numbers of practices such as expert locator, as shown in following tables. As
could be seen, the similar functionality of the mentioned three KM practices convinced us to put
them in the same sub-process. It should be mentioned that development of this classification has
been initiated through scrutinising some of the proposed models by (Kasten (2010); Lytras and
Pouloudi (2003); Ribeiro and Ferreira (2010)); (Barclay and Osei-Bryson (2010); Newell, et al.
(2006); Nissen, et al. (2000)). In the following sections each of the four processes and their
associated sub- processes will be correlated to proposed KM practices.
According to Nonaka and Takeuchi (1995; Nonaka and Takeuchi 2011), knowledge is
created through four processes, Socialisation, Externalization, Combination and Internalization,
which are called SECI. In order to develop the knowledge creation framework, the SECI model
was employed alongside the proposed KM practices by Feng (2006) and Kankanhalli & Pee
(2009). In total, more thirteen KM practices, which could be utilised for knowledge creation
purposes, were recognised in the literature, as shown in Table 3-7 (Carrillo 2005; Love, et al.
2003; Newell, et al. 2006; Nonaka and Takeuchi 2011).
Table 3-7 Knwoledge Creation pratices in project enviroments (developed for this research)
Knowledge Creation Sub Processes
Practices for Knowledge Creation
Socialisation • Formal and informal event • Workshops & seminar • Community of practices
Externalization • Workshops & seminar • Deductive & Inductive
thinking
• Experts system • Experience Report • Community of practices
Combination • Community of practices • Best Practice Cases
• Knowledge Broker • Data mining • Documentation search
Internalization • Research services • Simulation
• Experimentation
KM Process
KM Sub-process
KM Practices
50 Chapter 3 | The Conceptual Framework
For instance, externalisation is a sub-process to transform tacit to explicit knowledge. As
Table 3-7 depicts, in total, five practices have been proposed to support the externalisation sub
process. These practices are practical methods or tools to elicit an individual’s mind (Alavi and
Leidner 2001; Caniëls and Bakens 2012; Hoegl and Schulze 2005; Kasvi, et al. 2003;
Kloppenborg 2014; Owen and Linger 2011). The proposed practices are being examined in the
selected case studies to explore: 1) what KM practices are utilised at PMOs, 2) how they have
been employed and developed, and 3) what are challenges of utilising them.
Table 3-8 Knowledge capturing practices in project environment (developed for this research)
Knowledge Capturing Sub Processes
Practices for Knowledge Capturing
Knowledge Identification
• Expert locator • Knowledge repositories
• Knowledge detection tools • Formal and informal event
Knowledge Storing • Data base • Formal and informal event
• Document Management System (DMS)
Knowledge Classification
• DMS • Frequently ask questions
(FAQ) • File management system
• Management information system (MIS)
• Intranet
Knowledge Selection • Knowledge inquiry system • Data base • Frequently ask questions (FAQ)
According to the research framework, knowledge capturing comprises four sub-processes,
as presented in Table 3-8. The recognised practices to support knowledge capturing were
classified in four sub- processes: identification, storing, classification and sec lection (Alavi and
Leidner 2001; Barclay and Osei-Bryson 2010; Caniëls and Bakens 2012; Lytras, et al. 2002;
Owen and Burstein 2005; Tan, et al. 2007). As presented in Table 3-8, in total, eleven practices
were adopted to support knowledge capturing, and its associated sub processes. These practices
could be used for both measuring the maturity of PMO from a KM point of view, and also,
could be a guide to employing the appropriate process, with regards to level of maturity.
Table 3-9 Knowledge transferring pratcices in project enviroment (developed for this research) Knowledge Transferring
Sub Processes
Practices for Knowledge Transferring
Knowledge Distribution and
forwarding
• Project bulletin and reports
• Communication channels • Knowledge list
• Video and Tele Conference meeting • Yellow page • Intranet • Data base
Knowledge Sharing • Knowledge map • Formal and informal
events
• Training • Mentoring
In the research framework, two main sub processes i.e. knowledge distribution &
forwarding, and knowledge sharing, have been defined for knowledge transferring. In total,
eleven practices have been adopted as practices to facilitate both the mentioned sub-processes
and, ultimately, knowledge transfer, as shown in Table 3-9 (Ajmal and Koskinen 2008; Bakker,
Chapter 3 | The Conceptual Framework 51
et al. 2011; Feng 2006; Kankanhalli and Pee 2009; Kasvi, et al. 2003; Landaeta 2008; Lytras
and Pouloudi 2003; Wiewiora, et al. 2010).
For the knowledge reusing process, three sub-processes have been defined: Adapting,
Applying and Integrating, in which each one comprises numbers of practices. In total, eleven
practices have been adopted in the research framework by which knowledge reusing is
facilitated (Bell 2010; Feng 2006; Kamara, et al. 2003; Lytras and Pouloudi 2003; Morales-
Arroyo, et al. 2010; Tan, et al. 2007). As could be seen in Table 3-10, some of the practices are
similar to the practices that exist in knowledge transferring or capturing processes. This means
that some of the recognised practices could contribute to more than one knowledge process,
such as data bases, and Intranet.
Table 3-10 Knowledge reusing practices in project environment (developed for this research) Knowledge Reusing
Sub Processes Practices for
Knowledge Reusing
Knowledge Adapting
• Electronic notice board • Documents management
system (DMS) • Intranet
• Data base • Yellow page • Knowledge detection tools • Formal or informal events
Knowledge Applying • Expert systems • DMS
Knowledge Integrating • Knowledge map • Data mining
In summary, the KM framework comprises four KM processes that have been classified to
thirteen sub-processes, in which they are supported by numbers of KM practices. This
framework, as shown at Figure 3-3, represents assumed relationships among KM practices, sub-
processes and processes. All mentioned processes, sub processes and their associated practices
have been defined in a tree format and, then, it has been used to fit in with Nvivo’s requirement
for nodes and categories.
Project management maturity model 3.3.3
As discussed, the developed research framework will be examined in various maturity levels
of PMOs. The level of maturity should be determined through current PM maturity models
(PMMMs). To do so, the Kerzner’s PMMM (2005; Kerzner 2013) has been adopted to assess
the maturity level of selected cases. As discussed is section 3.2.6.1, K-PMMM has been
proposed based upon the PMBOK, and it comprises of five levels of maturity (Kerzner 2005).
K-PMMM has been adopted to fulfil following purposes:
1) To determine the maturity level of case studies, from a PM point of view,
2) To develop the research framework based upon research findings.
To do so, firstly the maturity of case studies is assessed by K-PMMM, then a research KM
framework will be utilised to collect data from selected cases. Ultimately, it is expected that the
research framework shall be developed alongside a number of propositions aimed at addressing
original research questions.
52 Chapter 3 | The Conceptual Framework
Knowledge management maturity model 3.3.4
As discussed earlier there are numbers of KMMMs in the literature. In this investigation, the
two following KMMMs were discussed: F-KMMM and G-KMMM. The research KM
framework (R-KMMM) has been developed through amalgamating these frameworks, as shown
in Table 3-11. The developed R-KMMM has two major contributions in this research: 1) It was
used to develop the KM framework, and 2) It will be employed to investigate the selected case
studies from a KM point of view. This preliminary framework will be refined through analysing
the research findings.
CONCLUSION 3.4
In this chapter, after a succinct review of associated literature, the research framework was
developed under the following premises: 1) KM processes, sub processes, and practices, 2)
PMMM as a method to both assess the maturity level of PMO and develop the research
framework, 3) PMBOK as project management methodology, and 4) R-KMMM as the method
to address proper KM practices at various maturity levels of PMO. In the next step this
framework should be examined by utilising the collected data from cases. This means that an
appropriate research methodology is required to facilitate both collecting accurate and reliable
data, and analysing the gathered information in order to test the preliminary research
framework. The next chapter has been assigned to thoroughly discuss the research design and
methodology.
Chapter 3 | The Conceptual Framework 53
Table 3-11 The customised KM Maturity Model or R-KMMM (developed for this research)
Level of Maturity Conditions
KM Processes
Knowledge Creation Knowledge Capturing Knowledge Transferring Knowledge Reusing
First Level, Initiating KM in
PMO
In general • There is little or no intention to formally manage project knowledge. • PMO and projects team members are not properly aware of the need to formally manage knowledge.
• There is no specific KM technology or infrastructure in place. • There is no formal process to manage project knowledge.
Initial activities
and/or enablers
• Firstly, SWOT analysis, Feasibility study and requirements analysis should be undertaken to initiate developing KM system at the PMO. • Initial definition of KM concepts as well as undertaking current KM challenges in the PMO, are required at this level. • At this stage both required preparation works and planning for KM processes and practices should be undertaken. • Some of basic practices might be conducted to manage knowledge capturing and creation. • There is no or limited practices support knowledge reusing and transferring.
Second level, Increasing KM awareness and
developing basic PM
processes in the PMO
In general • PMO management and top managers have realised the importance of project KM. • Management is aware of the need for formal KM system. • The concept of KM and has been defined and understood by projects team members. • Knowledge capturing improves through developing documentation and repository systems • There is no one or unit for being responsible of KM
• Knowledge capturing and creation should be improved in compare to previous. • There are some practices in place to support knowledge transferring and reusing. • Internet, Intranet and any types of networks in PMO contribute to KM • Informal communications are facilitated to help knowledge creation and transferring
Knowledge
management
practices
• More practices in place in comparison to previous level
• Integration with other KM practices has not been undertaken yet
• More practices in place in comparison to previous level
• Integration with other KM practices has not been undertaken yet
• Proper KM practices have been developed to support knowledge transferring
• At least one practice, specifically , is in place to support knowledge reusing
Third level, Developing proper KM
system in the PMO
In general
• There is a basic Infrastructure in place to support KM. • PMO and top managers are aware of their role in encouraging KM. • There is a unit or person to take the responsibility and accountability of KM. • KM is systematically supported through proper systems and established standards. • There are some training courses to instruct KM in the PMO. • KM strategies have been developed in line with PMO and, ultimately organisational strategies.
• There are numbers of integrated processes and procedures to be followed. • Basic KM Infrastructures have put in place and are being utilised. • There are some incentive systems to encourage project team members to follow KM procedures • Some KM practices are integrated at enterprise-level KM. • Individual roles for managing knowledge have been defined.
Knowledge
management
practices
• Knowledge creation strategies have been developed and translated into KM practices.
• Formal knowledge creation system should be established.
• Proper KM practices have been developed to create knowledge through transferring
• The integration with other KM processes has been undertaken.
• Knowledge capturing strategies have been developed and translated into KM practices.
• Proper KM practices to support knowledge selection and classification have been developed.
• Proper systems to capturing knowledge have been developed and collaborated.
• The integration with other KM processes has been undertaken.
• Knowledge transferring strategies have been developed and translated into KM practices.
• Proper KM practices have been developed to prepare formal channels for sharing Knowledge
• Education and Training are been conducted properly • Robust system should be in place to ensure the security of
Knowledge transferring. • The integration with other KM processes has been
undertaken.
• Knowledge reusing strategies have been developed and translated into KM practices.
• Robust systems and practices are in place to support applying Knowledge.
• Decision support systems and expert systems should be developed.
• The integration with other KM processes has been undertaken.
Fourth level, Managing projects’
knowledge in the PMO and
integrating project KM
with organisational
KM
In general
• Project KM and organisational strategies have been collaborated. • The role of project KM to improve organisational competitive advantages has been realised. • PMO KM practices and processes have been integrated with organisational KM activities. • KM initiatives have been properly established in the PMO. • PMO KM standards have been integrated with PM standards • Advance trainings and workshops to improve the KM are being conducted
• Existing KM unit in PMO have been integrated with organisational KM department • All KM systems have been integrated • Measuring the KM utilisation on project productivity is being conducted • Everybody is responsible for managing project knowledge. • Numbers of quantitative index, critical success factors (CSF), and metrics have been developed to measure
the effectiveness of KM processes.
Knowledge
management
practices
• Knowledge is properly created through all sub-processes(SECI): Socialisation, Externalisation, Combination and internalisation
• The integration with other KM processes has been conducted at organisational level.
• Success of Knowledge creation processes is being measured.
• Knowledge is properly captured through its sub-processes: Identification, Storing, Classification, and Selection.
• The integration with other KM processes has been conducted at organisational level.
• Success of Knowledge capturing processes is being measured.
• Knowledge is properly transferred through its sub-processes: Sharing, and Distributing & Forwarding
• The integration with other KM processes has been conducted at organisational level.
• Success of Knowledge transferring processes is being measured.
• Knowledge is properly reused through its sub-processes: Adapting, Applying and Integrating
• The integration with other KM processes has been conducted at organisational level.
• Reusing through transferring is well-managed. • Success of Knowledge reusing processes is
being measured.
Fifth level, Optimising the KM system in
the PMO
In general • Culture of sharing and knowledge transferring has been institutionalized. • Both organisation and PMO utilises an integrated KM system. • An audit unit should be developed for measuring the KM. • KM is integrated into organisation and it is continually improving.
• KM procedures are an integral part of the PM methodology as well as organisational process asset. • The existing KM infrastructure is continually improved to support all KM improvements • All KM processes have an automatic component in place. • Project KM and competitive advantages have been collaborated to support organisational strategies
Advance
Improvements • A research unit should be developed in KM department for supporting the optimization of the KM in both PMO and organisation. • Development of a decision making unit in the KM department will contribute to enhancing organisational competitive advantages
Chapter 4 | Research Design 55
Chapter 4
RESEARCH DESIGN
INTRODUCTION 4.1
This chapter aims to present the research design, data collection methods, and analysis
approaches in order to illuminate the proposed research questions. This approach allows the
researcher to investigate the phenomena and, also, examine a preliminary framework in order to
explore the current activities of PMOs from a KM point of view. It is expected that the preliminary
framework shall be refined through research findings and, ultimately, numbers of propositions and
recommendations will be developed to answer research questions and propose the final framework.
Chapter four comprises the following sections. First, the research flow has been presented in
section 4.2 to review the research questions, followed by section 4.3 to discuss the epistemological
and philosophical position of this research. Second, in sections 4.4 and 4.4 4.5, the research design
and selection of research methodology will be discussed to explain the appropriateness of employing
a case study. Third, the research implementation method and data collection techniques have been
discussed in 4.6 and 4.7. In sections 4.8, and 4.9, data analysis and the research quality have been
explained, followed by the conclusion in section 4.10.
A SNAPSHOT OF RESEARCH FLOW 4.2
The lack of addressing KM practices in the various maturity levels of PMO has been recognised
as the main research gap. This research was conducted to address the recognised gap through
answering following research questions:
1) To what extent are KM processes and practices employed in the PMOs?
2) How do KM practices contribute to the maturity level of the PMO?
3) How can knowledge be integrated in the PM Maturity Model?
As presented in Chapters 2 and 3, the current literature does not address the above mentioned
questions. In Chapter 4, a preliminary framework was developed based upon current literature. This
framework will be examined through appropriate research methods. As will be discussed later, 1)
this research follows the constructivism paradigm, 2) it is inductive and has an exploratory nature,
and 3) case study is the best research method with which to achieve the research objectives.
EPISTEMOLOGICAL AND PHILOSOPHICAL POSITION OF THIS RESEARCH 4.3
It is necessary to have a good understating of the philosophical and epistemological position of
research before conducting any further steps or actions (Creswell 2009; Gray 2009; Guba and
56 Chapter 4 | Research Design
Lincoln 1994). The research paradigm is “A basic set of beliefs that guide actions”, by which the
steps of research could be properly defined through adopting a suitable worldview (Creswell 2009).
According to Guba and Lincoln (1994) there are four paradigms or worldviews for designing a
research study: Positivism, Post-Positivism, Critical Theory, and Constructivism. Positivism and
post-positivism paradigms assume that the reality exists and it could be critically measured through
quantitative research methodologies; in contrast, constructivist perspective resides where there are
many realities with no single truth in the existing complex world (Guba and Lincoln 1994).
According to Creswell (2009) a constructivism paradigm has an inductive approach by which
numbers of theories could be developed through investigating the phenomena. In addition, a
constructivism worldview is a suitable approach for both exploratory and qualitative research
(Creswell 2009). In other words, this paradigm follows the inductive approach to comprehend the
existing reality of the subject under study, through exploring views/thoughts of multiple participants.
This researcher believes this study: 1) has an exploratory nature, 2) is an inductive research, 3) aims
to develop a number of propositions and hypotheses to address research questions, 4) deals with
participants’ thoughts and follows the qualitative approach for data inquiry to explore under-study
phenomena, 5) does not aim to verify of falsify the existing theory, 6) aims to construct and propose
a framework through qualitative methods in order to address knowledge management practices in the
project management office, and therefore 7) follows the constructivism paradigm.
Research design is “a logical plan for getting from here to there”, in which “here” refers to
research questions and “there” directs the research results (Yin 2009). According to Creswell (2009)
research design is a combination of plans and procedures to explain how research questions are
answered through spanning broad decisions to methods of data collection and analysis. There are
three popular research designs or methodologies: Qualitative, Quantitative, and Mixed method in
which qualitative design entails open-ended question(s) with an inductive approach and uses
“words”, while, quantitative research involves closed-ended question(s) with a deductive approach
and uses “numbers”, and mixed method is the combination of both (Creswell 2009).
This research follows a qualitative approach because of the following reasons:
• The research aims to answer questions through using “words” rather than “numbers”,
• The nature of research is exploratory and aims to understand the existing phenomena,
• The main aim is to develop a theory and framework, hence it follows inductive approach
rather than deductive (see section 4.3), and
• This research will be undertaken in the real world, through conducting case studies.
With regards to inductive approach and the explorative nature of this research, appropriate data
collection methods as well as analysis techniques should be employed to achieve research objectives.
Accurate data and information is crucial to undertake proper analysis for providing quality outcomes
Chapter 4 | Research Design 57
(Corbin and Strauss 2008; Gray 2009; Yin 2009). The triangulation approach is the highly
recommended strategy to obtain reliable data to understand what happens in reality (Creswell 2009;
Yin 2009). It contributes to provide credible and quality data by which phenomena are being
investigated from various perspectives (Yin 2009).
RESEARCH METHOD 4.4
The case study method has been selected as the main methodology. This method has been
recommended as one of the popular approaches to investigate under-study phenomena in the fields
of social science, management and information systems (Creswell 2009; Gray 2009; Yin 2009).
According to Yin (2009), a case study is an in-depth study of a subject in a real life context, by
which researchers have the opportunity of observing phenomenon, where the phenomenon is
influenced by or impacts on other entities and components.
Figure 4-1 Research methods and data inquiry techniques (developed for this research)
In order to gather proper data and information from the selected case studies, four data collection
methods and techniques, Interview, Direct observation, Questionnaire, and Document analysis, have
been employed, as shown at Figure 4-1. Also, Grounded theory was chosen as the research analysis
method. In the next sections, the reasons for choosing case study have been discussed.
The Rationale for selection of case study 4.4.1
According to Yin (2009), there are four major research methods: Experiment; Case study;
Survey; and Archival analysis. One of the most important factors to adopt an appropriate research
method is the “type of research question”. Table 4-1 illustrates the type of research questions and
their suitable research method. According to Yin (2009) if the research questions contain “how and
why” statements, then “case study” and “experiment” are recommended as suitable research
methods. In a consistent manner, Creswell (2009), advocates the suitability of case study for
qualitative research, especially, where it deals with “why and how” questions.
With regards to existing discussions in the literature, experiment is mainly utilised for
quantitative studies, while case study is advised for qualitative research during the specific time
without considering their frequencies (Creswell 2009; Yin 2009). In addition, experiment is
appropriate in which a researcher needs to control the under-study subject; in contrast, the aim of
Research Method
Case Study
Interview Observation Questionnaire Document Analysis
58 Chapter 4 | Research Design
employing case study is to study the subject as it is, without having any control over them (Yin
2009).
Table 4-1 Different methods with their relevant situation (Yin , 2009, p. 8)
Method Form of research question Requires control of behavioral events?
Focuses on contemporary events
Experiment How, Why Yes Yes
Survey Who, What, Where, How many , How much No Yes
Case study How, Why No Yes
Archival analysis
Who, What, Where, How many, How much No Yes/ No
This research question mainly contains “how”, which indicates that experiment or case study are
more suitable for this research, however, there are two main reasons to choose case study as the
research method: 1) case study is employed when researchers prefer to see the real operation without
having control on “behavioural events” but if a researcher needs to have control on “behavioural
events” then the experiment should be used, and 2) case study is suitable for qualitative research,
while experiment is used for quantitative studies (Creswell 2009; Yin 2009).
RESEARCH DESIGN 4.5
According to Yin (2009) research design is a systematic plan to investigate an understudy
problem through consideration of the four following components: 1) Research question, 2) Research
proposition, 3) The unit of research, 4) the logic linking of data to proposition. Given the qualitative,
inductive, constructivist, and exploratory nature of this research, the mentioned components have
been illustrated as following:
1) The research questions, which are discussed in section 4.2
2) The research proposition
The exploratory research does not need to have a proposition (Creswell 2009; Gray
2009; Yin 2009). This is consistent with the qualitative and constructivism nature of this
research, in which there is no aim to accept or reject a proposition; instead, numbers of
propositions will be developed at the end of this study.
3) The unit(s) of analysis
The unit of analysis is the level to which collected data is aggregated and analysed and
it could be individuals, groups of people, divisions, departments, organisations, industries
or even countries (Aita and McIlvain 1999; Yin 2009). Since this study aims to explore
the KM practices in the PMO, thus the unit of analysis is the Project Management Office.
4) The logic linking of data to proposition
Chapter 4 | Research Design 59
As discussed, Grounded theory, as a powerful approach to create theory from collected
data, has been selected to create logic links between data, research questions, proposed
theories, and framework.
The structure of the research design 4.5.1
As discussed, a research plan is one of the important components of research design by which
logical steps of study are presented. This research comprises of three major phases: 1)
Comprehension phase, 2) Exploration phase, 3) Framework development and Write up phase. As
Figure 4-2 illustrates, the followings stages have been conducted in this study:
• Comprehension Phase
An extensive literature review has been undertaken during comprehension phases in order
to meet the following objectives:
To deeply understand the current associated literature of PM and KM,
To formulate the research gap and propose research questions, and
To develop the research framework.
• Exploration Phase
Three cases have been selected to be studied and investigated to meet the following
objectives:
To identify and analyse the existing KM practices, and
To answer the first and second research questions.
• Framework Development and Write up Phase
At this phase Grounded theory and other appropriate analysis techniques has been utilised
to achieve the ultimate aims of this research, “To Integrate KM practices into Project
Management Office maturity levels”:
To analyse obtained data,
To propose propositions and frameworks based, and
To develop a framework to address KM practices in the PMO maturity model for
answering the third question.
60 Chapter Chapter 4 | Research Design
Figure 4-2 Research Design (developed for this research)
Chapter 4 | Research Design 61
RESEARCH METHOD IMPLEMENTATION 4.6
Case study is used as “an empirical inquiry that investigates a contemporary phenomenon in
depth and within its real-life context especially when the boundaries between phenomenon and
context are not clearly evident” (Yin, 2009, p. 18). A single case study contributes to provision
of in-depth understanding of the subject under study, while multiple case studies provide a
robust and reliable base to build and develop theories (Eisenhardt & Graebner, 2007; Perry,
1998; Yin, 2009). In other words, choosing multiple case studies strongly contributes to theory
development in which is more accurate, generalisable, and reliable, in comparison to a single
case study outcome (Eisenhardt & Graebner, 2007). In total, three cases have been selected for
this study. Both exploratory and explanatory approaches have been considered during the
implementation of three case studies, in which from an exploratory perspective, all relationships
between research framework and associated entities have been examined, while through an
explanatory approach, relationships among entities and components have been explained.
Selection of Case studies 4.6.1
Replication logic “refers to two or more cases in the same study where the investigator is
looking for congruence that indicates increased confidence in the overall findings” (Aita &
McIlvain, 1999, p. 258). According to Yin (2003, 2009), following the “replication logic
approach” contributes to the external validity of research. As discussed, project management
office has been adopted as the “unit of analysis” in which a multiple case studies approach will
be followed to strengthen the result of this study (Yin, 2009, p. 50).
In order to identify and select suitable case studies, four conditions have been defined:
1) The organisation should have an office, centre or unit to manage projects,
2) The organisation should have a project management methodology in place for
managing projects which could be an abstract or comprehensive,
3) The PMO maturity model for improving the quality of PMO functionality should be
adopted or followed, If there is none, assessment will be implemented, and
4) The PM unit or office is supported by top managers.
Theoretically, five PMOs are required to address the research gap in five levels of maturity,
however, three cases have been investigated due to subsequent limitations: 1) The PMO and
PMO maturity models are relatively new therefore, finding the PMO with the maturity levels of
four or five in Australia was difficult, and 2) the time limitation of this research was another
barrier. Three case studies were selected with PMOs at various levels of maturity. The selected
cases are well-known organisations from different industries. Since QUT’s ethical agreement
has been followed, there is obligation to not disclose the names of the selected organisations for
62 Chapter 4 | Research Design
confidentiality purposes. Therefore, the organisations have given a title to indicate their context
as followings:
• SCIENCO is a research organisation,
• GOVCO is a governmental organisation, and
• MINCO is a mining organisation.
Case study protocol 4.6.2
The case study protocol increases reliability and quality of the case study through providing
a suitable ground to establish appropriate communications (Yin, 2009). This protocol comprises
the required instrument and procedure to undertake the case studies and four data collection
methods. As could be seen in Appendix A, a case study protocol was developed in this research
and it was used as the main protocol between researcher and organisations under study. A copy
of the provided case study protocol, which has been approved by QUT’s Ethics office, was
given to the nominated liaison person from each case study. This contributes to the development
of a reliable relationship between researcher and participants.
DATA COLLECTION IMPLEMENTATION 4.7
Prior to conducting data collection, appropriate arrangements such as negotiation
communication were being made with participants and the liaison person. A consent form as
part of Ethical clearance (Ethic Number: 1100001424), which was approved by QUT’s Ethic
office, has been signed by participants to get their formal agreement to take part in our
investigation. The Appendices B depicts a sample of the issued consent form. In the first step, a
questionnaire was given to every individual to assess the maturity of the PMO. After collecting
all responses, the questionnaires were analysed to determine the maturity level of PMO. It
should be mentioned that some of selected case studies have already assessed their maturity,
however, a common method was required to assess them with the same approach.
Interviews 4.7.1
Interviews are one the most important sources of the case study’s evidence (Yin 2009).
There are three types of interview: structured, semi-structured, and unstructured interview. The
structured interview is a set of structured questions with the same stimulus, while an
unstructured interview is the opposite (Berg 2004). This means that unstructured interviews do
not comprise standard questions in which questions could be evolved during the course of
interview. A semi structured interview is comprised of predetermined questions that
respondents are being asked in a systematic manner, however, it gives the interviewer the
flexibility to ask unstructured questions, if required (Berg 2004).
The semi-structured interview questions were selected for this research because on the one
hand, there are numbers of pre-determined questions based on the research questions, on the
Chapter 4 | Research Design 63
other hand, researchers are keen to ask other questions if it is required during the interview
courses. Through following the recommended advice for providing reliable interview questions,
the numbers of questions as well as survey-questionnaires were developed, as shown in
Figure 4-3 and Appendix B (Leedy and Ormrod 2001; Yin 2009).
Interviews were conducted through the following case study protocol, in which at the
beginning of every interview, an introduction was provided after getting the participant’s
consent. Then, a succinct definition of terms and concepts was provided to prepare the
respondent for answering the questions. Afterward, briefly the interviewee’s background was
presented to initiate the demographic section in which interviewees’ background was
questioned. When the interviewer realised the interviewee was ready, then the main research
questions were asked accordingly. Eventually, at the end, four survey questions were answered
by each participant.
According to Yin (2009) and Creswell (2009), interviews should be continued until the
researcher is encountered with repetitive and redundant answers. In other words, when an
investigator feels that saturation of data has happened, this means that the investigation either
could be finished or another data collection should be employed. In SCIENCO and GOVCO,
the redundancy of data was realised after six interviews, while in MINCO redundancy occurred
after five interviews.
Figure 4-3 Interview and survey questions tree (developed for this research)
64 Chapter 4 | Research Design
Survey questionnaire 4.7.2
In the current literature, two types of questionnaire have been discussed: Self-Administered;
and Interviewer-Administrated (Gray 2009). With regards to the inductive and exploratory
nature of this research, the researcher aims to explore the opinions of respondents about the KM
practices in the PMO. In addition, triangulation of the data was another reason for conducting a
questionnaire in this case study (Yin, 2009). Two survey-questionnaires were developed for this
research and the same target. One was for assessing the PMO maturity level, and another for
ranking the importance of knowledge processes as well as knowledge types. In fact, the second
questionnaire was investigated at the end of the interview, as depicted in Figure 4-3
In order to analyse the outcomes of the survey, AHP (Analytic Hierarchy Process) was
employed by which the obtained data were weighted properly for analysis purposes. According
to Stam and Silva (1997), AHP is a popular structured technique for ranking and analysing
under study phenomena or decision making through utilising mathematics.
Direct observation 4.7.3
This is another data collection method, which is recommended to conduct during the case
study implementation to observe and record the existing activities of a case study, related to a
research problem (Creswell 2009; Gray 2009; Yin 2009). Direct observation, also contributes to
quality of collected data through the following triangulation strategy. At least three days were
arranged for each case, to observe the current PM related activities, processes, procedures and
applications. Direct observation sessions were conducted before and after interviews in order to
understand interviewees’ explanations when they were talking about an application or process.
Participating in the project meetings, and formal and informal discussion among projects was
also part of direct observation to observe the existing activities related to project knowledge
management.
Documentations analysis 4.7.4
Organisational documents such as procedures, standards, forms and manuals contribute to
provide specific details for supporting data and evidence from other data collection methods
(Yin 2009). Also, this is the only codified source of evidence which contains explicit knowledge
within the PMO, by which researchers could obtain insightful information about under-study
subjects. The main reasons to employ this source of evidence during the investigation are to
gain:
• Insightful information about organisations’ goals, objectives, strategic plan,
structure, and, also a road map for developing the PMOs,
• Information about current PM methodologies and processes, and
• Information about current instructions to understand the developed PM practices.
Chapter 4 | Research Design 65
DATA ANALYSIS 4.8
According to Yin (2003), qualitative data analysis comprises of examining, categorising,
tabulating, testing, and/or recombining qualitative and quantitative evidence to both address the
initial inquiries of the study and, also, identify new relationships or concepts. The importance of
data analysis in the research project necessitates developing the appropriate strategy(s).
According to Yin (2009) the four following strategies contribute to both analysing the collected
data and quality of research: 1) Relying on theoretical proposition; 2) Developing a case
description; 3) Using both qualitative and quantitative data; and 4) Examining rival
explanations. With regards to research questions, which are “how” and “what” types of
question, the first strategy and second strategies have been suitable since they led researchers to
provide a data collection plan in order to find related data and ignore the information which is
not associated with the scope of this research. The third and fourth strategies, also, were
followed by those robust and reliable outcomes that were developed through data analysis (Yin
2009). Both the research framework (R-KMMM) and research questions have been very helpful
during the data collection and analysis stages. During the data analysis, all of the framework
components as well as elements were investigated against the collected evidence, also including
rival analysis. In addition, both qualitative and quantitative data assisted to make strong and
robust analysis.
Grounded theory as inductive theory building method 4.8.1
According to Corbin and Strauss (2008) the aim of exploratory studies is to obtain clearer
understanding of under-investigated problems or questions in order to both collect data and
make appropriate relations among them through building theories or hypotheses. Eisenhardt and
Graebner (2007) advocate that Grounded Theory is one of the best methods to develop theory(s)
based upon obtained data from case studies. Grounded theory has been extensively used in both
organizational and management studies since late 2000, which shows the increasing importance
of this method (Gray 2009).
Technically, “analysis” is the process of breaking down a subject to have better
understanding of it (Lindner and Wald 2011). Also, data analysis is defined as the examination
and investigation of the subject and its associated data through appropriate techniques or tools
for revealing their functionality, characteristics and properties in order to make new knowledge
and inferences (Corbin and Strauss 2008). This means that information analysis gives meaning
to data and provides a vehicle to transform data to knowledge.
Given the exploratory, inductive and constructivism nature of this study, Grounded theory
has been adopted as the main analytical approach in order to develop numbers of propositions
for addressing the research problem. Having said that, this approach has been selected for the
following purposes: 1) To analysis and classify the collected data, 2) To discover and identify
66 Chapter 4 | Research Design
relationships among the obtained data; 3) To propose theory(s) to answer research questions in
order to develop the preliminary framework for addressing the KM practices in the PMO
maturity levels.
Data analysis processes 4.8.2
According to Lindner and Wald (2011) data analysis comprises of the following three stages:
1) reducing the amount of data in a way that could be understandable, 2) displaying the
processed data through developing groups/categories and as such, and 3) drawing conclusions
by which the under-study phenomena are addressed. This approach was adopted and then
customised by defining three stages for this research: 1) data organisations, 2) data display, and
3) conclusion and theory development, in which each stage consists of numbers of processes.
Figure 4-4 Data analysis processes (developed for this research) depict the proposed analysis
stages and processes.
Figure 4-4 Data analysis processes (developed for this research)
Data organisation 4.8.3
At this stage, four processes were conducted in order to make data ready for the next stage.
After conducting interviews and surveys, the provided notes and comments were integrated with
each interview. Then, recorded interviews were transcribed into MS Word documents and at the
same time, associated comments and notes were attached to and integrated with each one. At the
end, all interviews had the same format with the same order of contents to be entered into our
analysis application. In addition, for organising the server results, they were collected, and then
entered into MS Excel sheets in an organised manner, to be used by the adopted analysis tools.
Chapter 4 | Research Design 67
Data display 4.8.4
In this stage, all organised interviews were uploaded to Nvivo 10, as the main application for
data analysis and coding purposes. According to Lindner and Wald (2011) “Coding” in Nvivo
is the process of storing passages of information or comments in various nodes and tree nodes,
in which sources always remain intact. This means that coding consists of assigning passages to
specific terms which is shorter in a way that the main resource still remains unchanged.
As discussed earlier, grounded theory was employed as our main analytical method, by
which coding in the Nvivo was conducted. According to Corbin and Strauss (1990), processes’
grounded theory should be designed to develop a “well integrated concept” by which the
phenomena under study have been thoroughly investigated by proposing a theoretical
framework. Coding is the critical part of constructing and employing grounded theory, by which
an analytic process is facilitated (Corbin and Strauss 1990; Corbin and Strauss 2008; Gray
2009). In other words, the bones of analysis processes are made by coding and theoretical
integration constructs a skeleton by assembling the bones (Charmaz 2014). In doing so, the
following three stages have been designed to undertake this analytical technique. Figure 4-5
depicts a sample of coding used for this research.
Open Coding 4.8.4.1
The interpretive process of analytically breaking down and disaggregating the data into units
is known as Open coding (Charmaz 2014). Since this research aimed to explore the KM
practices in the PMOs, hence, KM Practices and associated processes were used as a base for
open coding, in conjunction with preliminary research framework, for developing appropriate
codes, concepts and categories. The preliminary coding is managed through Nvivo and a
manual coding technique. In addition, the conceptual framework and additional nodes were
created when the concepts emerged from the data. At the end of the open coding process,
numbers of codes were developed but they were broad, in which no proper and reliable
inference was possible. Therefore, appropriate integration among the created nodes and
categories was required to give more meaning for analysis purposes.
Axial coding 4.8.4.2
Once codes were defined, the next step was undertaken to examine the relationship among
categories and sub-categories. In other words, Axial coding is the process of scrutinising the
validity of codes and relations of the categories in order to build a skeleton of the categories
through making appropriate links among them (Corbin and Strauss 1990; Corbin and Strauss
2008). To do so, firstly hypotheses were developed through testing codes and categories by
collected data, then, possible propositions were developed to construct relations between
categories. This means that categories of KM practices in the PMO were examined through the
obtained data. Then, categories were refined through examining codes and their relations, in
68 Chapter 4 | Research Design
which weak categories were edited or removed. In this step, well-grounded hypotheses as well
as categories were recognised to make researchers ready for the next step.
Complementary analytical techniques 4.8.5
According to Yin (2009) there are numbers of analytical techniques such as pattern
matching, explanation bundling, and numerical count analysis. Pattern matching is used to
compare findings of the empirical study to predict one in which, if they confirm each other, then
internal validity of study findings is reliable (Yin 2009). This method was employed in both
within-case and cross-case analysis by which the research findings were compared to both the
research KM maturity model (discussed in chapter 3), and to each other. In addition,
explanation building is another form of pattern matching by which an appropriate pattern is
developed through analysing obtained data (Yin 2009). This means that, based on gathered data
in each case, a pattern might be developed to address common behaviour among research
components. This technique was used in the course of this research specifically during the
“cross-case analysis”.
The importance and frequency of understudy components could be estimated through a
“numerical counts analysis” technique in which the importance of an issue is determined
through counting either numbers of occurrences or raised by participants and people (Lindner
and Wald 2011). This technique was frequently used in this research for assessing the
importance of KM practices as well as processes. Also, it was employed during the survey
outcomes analysis.
Chapter 4 | Research Design 69
Figure 4-5 Sample of Coding (developed for this research)
Within-case analysis 4.8.5.1
According to Yin (2009) “within-case” analysis aims to scrutinise each case as a standalone
entity, by which a researcher could be intimately familiar with case study and its current
operations and activities. In addition, this process contributes to properly interpret rich as well
as complex data in the way that research objectives could be met (Creswell 2009; Yin 2009). At
this stage, each case was thoroughly scrutinised by employing related components of the
research framework in order to address the research gap in every case. The explanations and
outcomes of employing analysis techniques, tools, and applications such as Grounded theory,
Pattern matching and Nvivo have been presented in each case study report, which can be found
in Chapters 5, 6, and 7.
70 Chapter 4 | Research Design
Cross-case analysis 4.8.5.2
The aim of “Cross-case analysis” is to strengthen the research findings from a previous stage
i.e. “within case analysis”, to develop robust propositions and theories (Yin 2003). One of the
aims of undertaking such a method was to compare and analyse the similarities and differences
of research framework’s components in three different case studies. Tables were developed by
which each component was analysed in different contexts. For instance, knowledge creation and
its associated practices were examined in three maturity levels of PMO to find in what levels
creation of knowledge was stronger, therefore, some propositions were developed based on
findings for addressing research questions. Also Nvivo, alongside the other analytical
techniques such as pattern matching and explanation building, is employed to enrich the
developed theories of this research. In Chapter 8, cross-case analysis is presented.
THE QUALITY OF RESEARCH 4.9
According to Yin (2009), the quality and validity of qualitative research depends on four
factors: construct validity, internal validity, external validity, and reliability. For quality
purposes, this approach was adapted alongside the process-oriented quality tactic. In other
words, numbers of processes and procedures were developed in order to make sure that all four
above-mentioned quality factors were followed and satisfied. Table 4-2 illustrates the
mentioned quality factors and their associated tactics.
Construct Validity 4.9.1.1
The process of establishing suitable operational measures to ensure the constructs of data
collection and analysis, is called construct validity (Yin 2009). According to Yin (2009) three
factors should be considered to improve “construct validity” of qualitative research: 1) using
multiple sources of evidences, 2) establishing a suitable chain of evidence, and 3) developing
an appropriate data base for obtained data.
Using multiple sources of evidences 4.9.1.2
One of the most recommended and popular techniques for using multiple sources of
evidence is “triangulation”, by which a researcher uses more than one source of data to
improve the data collection and construct validity (Lindner and Wald 2011; Yin 2009). In other
words, this approach contributes to rigours and integration of study by which outcomes of
research are more reliable and generalisable (Yin 2009). Two types of triangulation have been
mentioned in the literature: data and methodology triangulation in which data triangulation
addresses using multiple sources of data such as project manager or PMO staff, while
methodology triangulation deals with the way the data is collected, such as interview and direct
observation (Yin 2003). In this research, both types of triangulation were employed through
choosing different roles in the project management office, and also four data collection
Chapter 4 | Research Design 71
methods: interview, survey questionnaire, documents analysis, and observation. In addition, in
the case study protocol, general processes and procedure were defined to ensure the quality of
data collection.
Table 4-2 The proposed quality tactics (Yin 2009) Quality Factor Appropriate Tactics
Construct Validity
• Developing a conceptual model for KM practice • Followings data triangulation approach by using multiple sources of evidence
Following methodological triangulation through employing multiple techniques such as interview, observation and document analysis
• Establishing the appropriate chains among the sources and techniques • Developing proper database for collected data through using Nvivo and Ms Excel
Internal Validity
• Employing analytical analysis techniques such as pattern modelling and explanation building alongside the Grounded theory
• Utilizing logic models for analysis such as program level logic model External validity • Choosing replicable logic for multiple case studies and Grounded theory
Reliability • Preparing and employing an appropriate case study protocol • Developing an appropriate data base
Establishing suitable chain of evidence 4.9.1.3
The chain of evidence is developed to follow any change in evidence from the initial
research questions to the final conclusion, by which the researcher is able to study the
phenomenon in different situations (Yin 2009). In this study, the three following tactics were
implemented to create a chain of evidences: 1) a data base was created to help researchers
collecting related data, 2) the sequence of each case was narratively provided to clearly
represent the structure of events and their associated sequences, and 3) the case study protocol
was developed for systematic data collection and data analysis purposes.
Developing appropriate database for obtained data 4.9.1.4
The Nvivo 10 was used as the main database, alongside the MS Excel, to record and capture
obtained data from interviews and surveys. Also, Nvivo was employed for analysis purposes in
which all created queries, relationships and memos have been recorded accordingly. Three types
of queries were run during the course of research: Matrix, Text search, and Annotation, by
which data analysis was conducted. Also, all created nodes and categories as well as models
were developed and recorded in the Nvivo for analysis proposes as well as improving the
construct validity of research data.
Internal validity 4.9.2
Internal validity is maximised when researchers aim to explain and justify reasons of
relationships among various components (Yin 2009). In other words, justification and
explanation of the research components such as KM practices and processes should follow a
logical way in order to be internally valid. Yin (2003) recommends a careful use of proper
72 Chapter 4 | Research Design
analytical methods, such as pattern matching or explanation building, to ensure the internal
validity of this research.
External validity 4.9.3
Generalisability of research findings confirms the external validity of case study research
(Yin 2009). Since theory development is one of the research’s aims, so generalisability was an
important factor to improve the quality of research outcomes. To do so, replication logic was
conducted, by which findings of the first case study were replicated in second and third case
studies to ensure that validity of relationships among research components is emerged (Yin
2009). In other words, during cross-case analysis, the “replication logic” was used to confirm
that research findings are valid and generalisable. According to Corbin and Strauss (2008)
grounded theory provides appropriate processes to develop a theory that could be valid to be
generalised. In other words, embedded processes of this theory develop a reliable and valid
theory.
Reliability 4.9.4
Reliability discusses the credibility and consistency of research outcomes in which biases
and errors of research have been removed or minimised; therefore, the same outcomes will be
obtained if the research is conducted again (Yin 2009). Among existing recommended
approaches to obtain reliable outcomes, four were employed in this study. 1) A case study
protocol was developed to address the unique method of data collection as well as analysis, 2)
an appropriate database was provided to collect and record data from the beginning in order to
minimise any loss of data, 3) data and methodology triangulation tactics were followed to make
sure that both data and their sources are more than one, and 4) the same questions, which were
derived from research questions, were asked during the course of study to prevent any bias from
the researcher side (Aita and McIlvain 1999; Berg 2004; Creswell 2009; Yin 2009).
CONCLUSION 4.10
This research follows an inductive, exploratory and constructive approach. The case study
method has been chosen as the research methodology, alongside the Grounded theory as the
data analysis methods. A number of strategies and tactics were presented to be used for
improving the quality of the research. In addition, triangulation of data was used to collect the
quality and rigorous data. Moreover, a case study protocol was developed to both make
effective communication with organisations, and increases the quality of research. Also,
appropriate applications, namely Nvivo 10, will be utilised for data analysis purposes.
In the following chapters, i.e. 5, 6, 7, the within-case study analysis for three case studies
will be presented through use of the research methodology and design. In Chapter 8, the cross
Chapter 4 | Research Design 73
case analysis will be discussed to compare the selected cases, and also to develop the
preliminary research framework.
74 Chapter 5 | Case Study Analysis: SCIENCO
Chapter 5
CASE STUDY ANALYSIS: SCIENCO
INTRODUCTION 5.1
In the previous chapter, the research methodology presented the selected methods for
gathering the research information, analysing, and interpreting the collected data. As discussed,
the case study method was chosen as the research methodology, and the grounded theory
alongside the other analytic techniques, such as pattern matching, was adopted as the research
data analysis method.
In the next three chapters, i.e. 5, 6, and 7, the three selected case studies will be examined
against the research framework, in order to answer the research questions. To do so, the
research methodology was employed from data collection stage to data analysis phase, and each
stage has been thoroughly followed and presented accordingly. In this chapter, SCIENCO’s
PMO was investigated to explore the project knowledge management in a research organisation
in order to discuss the two first research questions (RQ1. How are KM practices and processes
employed in the PMOs, and RQ2. How do KM practices contribute to improve maturity level of
the PMO?). First, the organisation’s background will be explained, followed by data collection
procedures. Second, the PMO’s maturity level will be discussed alongside the current PM
systems. Third, data analysis will be undertaken to discuss the current status of SCIENCO’s
PMO from a KM perspective. Finally, concluding remarks and the research findings will be
summarised.
SCIENCO’S BACKGROUND 5.2
SCIENCO was formed in the early 1920s as an organisation to carry out scientific research
to develop three major industries: mining, farming, and manufacturing. Since then, SCIENCO
has expanded its research activities to various fields such as environment, human nutrition,
urban and rural planning, water, and astronomy, to become one of the largest and most diverse
research agencies in the world (Müller, et al. 2013). As an internationally known organization,
SCIENCO defined its mission as: “to deliver innovative solutions for industry, society and the
environment”. In addition, SCIENCO’s stated vision is: “using science to make a profound and
positive impact for the future of humanity” (Müller, et al. 2013).
In order to manage more than 6500 employees, SCIENCO has adopted the matrix structure
approach, in which thirteen divisions have been developed as business units to manage all
research areas (nationally or internationally), and ten flagships has been defined to focus on
Chapter 5 | Case Study Analysis: SCIENCO 75
current national challenges. The majority of SCIENCO’s divisions and flagships undertake a
number of projects, programs or portfolios. Projects are research based, in which they are either
sponsored by clients or undertaken for strategic and technological advancement purposes.
Figure 5-1 A snapshot of SCIENCO's structure (from SCIENCO’s organisational chart)
As shown in Figure 5-1, division and/or flagship managers have the ultimate responsibility
for project success/failure and they are accountable for initiating, planning, implementing and
closing assigned projects. In addition, there is an enterprise supportive function, Program and
Performance Department (PPD), which is responsible to provide processes, procedures, and
methodology to unify and integrate all project-related activities within SCIENCO. Functionality
of PPD is similar to a classic PMO, which has been developed in the last three years.
As a research organisation, SCIENCO uses various approaches to develop appropriate
solutions for diverse industries. Applicability and novelty of solutions are the most significant
contributions of SCIENCO to the body of knowledge. This entails either creating knowledge
that is new to the world or the industry, or developing current knowledge to propose a new
solution for addressing the recognised challenge. In other words, SCIENCO is a company that
creates knowledge through both operational activities and project implementation. Since this
study aims to focus on KM in projects, SCIENCO is an interesting case study to be investigated.
On one hand, knowledge creation is embedded in research and operational activities which
should be captured and reused. On the other hand, SCIENCO’s PMO facilitates organisational
projects so it has the responsibility of managing projects’ knowledge. This means that in
scientific projects with the aim of creating new knowledge, different KM practices may be used,
in comparison to other types of organisations. Therefore, the outcomes of this investigation may
generate some new light on revealing new aspects of project KM in research organisations.
RESEARCH OBJECTIVES AND QUESTIONS 5.3
As discussed in Chapters 1 and 2, this research aims to explore the management of project
knowledge in the PMOs. To do so, three objectives have been defined for this study: Research
Objective (RO) 1) to analyse the role of KM practices in various maturity levels of PMO, RO2)
to explore the contribution(s) of PMO for managing project knowledge, and RO3) to develop a
CEO/Board
Executive Team Member
Flagships Divison
Enterprise Functional Support
Program and Performance
76 Chapter 5 | Case Study Analysis: SCIENCO
framework to address KM in various maturity levels of the PMO. In order to achieve the
mentioned research objectives, a case study method was adopted with the following in which
each case should: 1) manage projects in organisations, 2) have a PM methodology, and 3) have
a PMO in place.
Table 5-1 The Research Questions (developed for this research)
1. To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from KM perspective?
1.2. What types of knowledge are required at each phase of project lifecycle?
1.3. What kinds of KM practices are utilised in each maturity level of PMO?
2. How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project? 2.2. How can PMO contribute to managing the project Knowledge?
3. How can knowledge be integrated in the PM maturity model? 3.1. How is knowledge created, captured, transferred and reused in PMOs?
3.2. How can KM practices be employed in each maturity level of PMO?
In order to satisfy the mentioned research objectives, three research questions were defined:
RQ1) to what extent are KM processes and practices employed in the PMO, RQ2) how do KM
practices contribute to maturity level of the PMO, and RQ3) how can knowledge be integrated
in the PM Maturity Model, in which each research question entails some sub-questions, as
presented in Table 5-1. These questions were examined in SCIENCO through following the
research methodology, and are discussed in the next sections.
DATA COLLECTION PROCEDURES 5.4
According to the research methodology, case study protocol should be followed to
communicate with the selected case study, as shown in Appendix A. The case study protocol
was used to facilitate the following: 1) initiating contacts with authorities, 2) planning for data
collection methods, 3) assessing the maturity of organisation from a PM point of view, 4)
conducting the interviews and survey, 5) undertaking complementary interviews, 6) analysing
the data, 7) preparing the case study report. In addition, the proposed research methodology was
followed for data collection and analysis purposes, as depicted Figure 4-4
The data collection schedule 5.4.1
The PPD division in SCIENCO was selected to undertake three data collection methods, i.e.
interview, document analysis and direct observation. To do so, a liaison person was appointed
from SCIENCO to assist with arranging suitable dates for conducting interviews, as well as
direct observation. In addition, she facilitated the access to organisational documents and the
Chapter 5 | Case Study Analysis: SCIENCO 77
current PM applications and tools. As shown in Table 5-2, seven interviewees were chosen in
SCIENCO: PPD’s senior manager, PMO manager or coordinator, one program manager, two
project managers, and two project team members. In some cases, interviews were conducted
two times, as researchers needed more clarifications. For confidentiality purposes, interviewees’
names were replaced by a selected code as can be seen in the following Table.
Table 5-2 Interviewees’ list and schedule in SCIENCO (developed for this research)
Interviewee Position Location 1st interview 2nd interview
Researcher’s Comments
In.Sc.1 Senior Manager in Brisbane
28/03/2012 (face to face)
20/04/2012 (on the phone)
Attached in Appendix D
In.Sc.2 Business Development
manager ( project Manager)
28/03/2012 (face to face)
19/04/2012 (face to face) NA
In.Sc.3 PPD reps in Sydney 5/04/2012 (on the phone)
25/04/2012 (on the phone) NA
In.Sc.4 Program Manager Brisbane
30/03/2012 (face to face)
31/05/2012 (face to face) NA
In.Sc.5 Project Manager Brisbane 30/03/2012 (face to face)
(31/05/2012 (face to face) NA
In.Sc.6 Project team member in Brisbane
30/03/2012 (face to face)
31/05/2012 (face to face) NA
In.Sc.7 PM coordinator in Brisbane
28/03/2012 (face to face) NA NA
All interviews were electronically recorded and the majority of data collection activities
were undertaken at SCIENCO’s site in Brisbane, from late March 2012 to late May 2012. Also,
five days were spent to directly observe the current PM activities in SCIENCO. In addition, it
took two days to study the utilised software and systems in the SCIENCO’s PMO. After
finishing the data collection phase, the collected interviews were fully transcribed into the MS
Word format in order to prepare them for uploading in Nvivo, as the analysis applications. In
total, this process took three months, and more than 160 pages of interviews transcriptions were
provided to be used in Nvivo.
The data collection methods 5.4.2
According to the research methodology, three forms of data collection were employed: 1)
semi-structured interviews alongside the two types of questionnaires, one for assessing the PMO
maturity level and another for assessing the importance of KM processes, 2) direct observation,
and 3) document analysis. The first questionnaire was developed to assess the maturity level of
project management activities and was given before interview questions. The second
questionnaire asked about KM practices, after finishing the interview questions. In addition,
direct observation and document analysis were employed for gathering complementary
information from this case. Both mentioned methods were used to investigate SCIENCO’s
activities from a PM as well as a KM point of view. The data collection activities were
78 Chapter 5 | Case Study Analysis: SCIENCO
conducted in accordance with the case study protocol, also by getting assistance from an
assigned employee, as SCIENCO’s liaison. Table 5-3 represents the utilised data collection
methods in SCIENCO.
Table 5-3 The Data collection methods (developed for this research)
Data Collection Method Location Facilitator Date
Interviews and Questionnaires
SCIENCO’s Site in Brisbane Researcher
Mentioned in the Table 5-2
Documents Review SCIENCO’S site in Brisbane and QUT
Researcher and SCIENCO’s liaison
person
12/04/2012 till 31/05/2012
Direct Observation SCIENCO Site in Brisbane
Researcher and SCIENCO’s liaison
person
16/04/2012 and 23/04/2012
In addition, the triangulation of data collection methods was adopted in order to ensure the
quality of gathered data (Singh, et al. 2009).
THE DATA ANALYSIS 5.5
After data collection, the process of data analysis was conducted to investigate SCIENCO’s
PMO from a PM and KM point of view, and to ultimately answer the research questions. At the
first step, the maturity level of the PMO was assessed, and then KM challenges were discussed,
and followed by analysing the required types of knowledge during project lifecycle. At the end,
the importance of four KM processes: Creation, Capturing, Transferring, and Reusing were
analysed, and then examined against the explored KM challenges to investigate the relation
between KM process and KM issues in the SCIENCO’s PMO. In fact, the first and second
research questions (RQ1- How are KM practices and processes employed in the PMOs, RQ2) How
do KM practices contribute to improve maturity level of the PMO) will be answered at the end of
this section.
The level of maturity for SCIENCO’s Project Management Office 5.5.1
According to the research methodology, the assessment of a PMO’s maturity level is the
initial step to manage the process of data analysis. The designed assessment model is a
questionnaire survey which comprises 13 questions to cover the examination of nine PMBOK’s
knowledge areas during the project life cycle. This assessment model is the customised form of
PM assessment method, suggested by Kerzner (2013) which has been simplified to meet the
research scope and objectives.
This questionnaire was distributed among numbers of employees in SCIENCO, by which
participants were asked to rate each question from 0 (lowest) to 10 (highest) in which they
should choose “0-1” for poor, “2-3” for weak, and eventually “8-10” for world standard
quality. Ten questionnaires were distributed among respondents and, eventually seven of them
were returned and all the answers entered in MS Excel 2010.
Chapter 5 | Case Study Analysis: SCIENCO 79
According to the research framework and (Kerzner (2005); Kerzner (2013)), the level of
maturity for a PMO could be any number from 1 to 5, in which number 1 represents the lowest
level of maturity (ML), while number 5 claims the optimum maturity level (OL). In other
words, maturity level is defined at five levels in which the lowest maturity level, i.e. ML=1,
indicates that PMO is in its initial steps to improve the quality of project management, in
contrast the highest maturity level, i.e. ML=5, means that PMO has developed and customised a
robust and advanced project management system to support organisational projects (Project
Management Institute 2008b).
Table 5-4 PMO’ ML from PM knowledge perspective (developed for this research)
PMBOK’s Knowledge area Maturity level Average ML Project Scope management 0.58
1.47
Project Cost management 2.57 Project Time management 1.64
Human Resource management 1.36 Project Quality Management 0.93
Project Risk management 2.43 Project Communication management 1.00
Project Procurement management 1.50 Project Integration management 1.29
At first, the maturity level (ML) for nine knowledge areas of PMBOK was analysed, and as
Table 5-4 as well as Figure 5-2 illustrate, project risk and cost management received the highest
ranking PM practices, while the other seven knowledge areas were rated less than 2. This means
that current respondents have given low numbers to these practices, which means that the
current PM practices for supporting those seven areas have not met the expected quality from
respondents’ point of view (Project Management Institute 2008b). In other words, from
participants’ perspective only risk and cost management, to some extent, are supported through
the current PM practices, while other knowledge areas are yet to be improved. The research
analysis revealed that the weighted average maturity level for SCIECNO’s PMO is 1.47. From
PMBOK’s knowledge perspective, this means that SCIENCO’s PMO should be classified as the
PMO with first level of maturity (Desouza 2006; Kerzner 2005; Project Management Institute
2008b).
80 Chapter 5 | Case Study Analysis: SCIENCO
Figure 5-2 PMO’s ML from PMBOK's knowledge areas perceptive (developed for this study)
In the next step, maturity level was analysed from a project lifecycle point of view, so as
Figure 5-3, and Table 5-4 depicts, respondents have rated the “Planning Phase” at more than 2,
while the other three phases were rated less than 2. This means respondents are more satisfied
with the planning phase in SCIENCO in comparison to other project phases (Kerzner 2005;
Project Management Institute 2008b). As will be discussed later, respondents mentioned that the
current PM processes do not significantly help them during the project lifecycle so projects are
faced with number of issues in this regard. This is consistent with the assessed level of maturity,
i.e. ML=1, which means that the PMO has not developed the required PM practices to facilitate
organisational project management (Kerzner 2013).
Table 5-5 PMO’ ML from project lifecycle perspective (developed for this research) Project Phases Maturity level(ML) Average ML
Initiation 0.64
1.43 Planning 2.14
Execution and monitoring 1.71 Closing 1.21
As Table 5-5 represents, the average maturity level (AML) for a project life cycle has been
assessed as 1.43. This result supports previous evidence and it both strengthens the quality of
data collection method and shows that respondents answered questions. As shown at Figure 5-2
and Figure 5-3, PMO’s ML from two different points-of-view has been analysed and assessed,
in which both determined the first level of maturity for SCIENCO’ PMO (ML= Maturity Level,
OL=Optimum Level).
0.58
2.57
1.64
1.36 0.93
2.43
1.00
1.50
1.29
0.000.501.001.502.002.503.003.504.004.505.00
Project Scope
Project Cost
Project Time
HR management
Project QualityProject Risk
ProjectCommunication
Project Procurement
Project Integration
ML OL
Chapter 5 | Case Study Analysis: SCIENCO 81
Figure 5-3 SCIENCO’s Maturity level from PLC perceptive (developed for this research)
The research analysis revealed that SCIENCO’s PMO has ML=1.47 from a project
knowledge point-of-view, and ML=1.43 from a project lifecycle perceptive. According to the
current literature and the research framework, SCIENCO’s PMO could be technically
categorised as a PMO with first level of maturity (Grant and Pennypacker 2006; Kerzner 2005;
Project Management Institute 2008b). This means that the PMO has developed some basic
practices of project management, however, the majority of required PM practices are yet to be
addressed at this level of maturity, as presented in Table 5-4. In other words, at the first level of
maturity, the awareness for project management has been raised in the organisation in which
the PMO is responsible for developing PM competencies by addressing reliable and practical
PM practices (Project Management Institute 2008b)
According to (Kerzner (2005); Kerzner (2013)) the first level of maturity is called common
language, which means that the need for project management in an organisation as well as a PM
framework as a common language among project team members has been raised at this level of
maturity. The current literature has defined the following characteristics for the PMO with the
first level of maturity which means that they could be generally recognised in any PMO with a
low level of maturity (Crawford 2006; Kerzner 2005; Kerzner 2013; Project Management
Institute 2008b):
• In the PMO with a first level of maturity, there is no unique project management framework, however, attempts to develop it have been initiated,
• There is an observed lack of addressing project management tool/techniques in place,
• There are limited services to assist project managers, and they have to manage with different methods,
0.64
2.14
1.71
1.21 0.000.501.001.502.002.503.003.504.004.505.00Initiation
Planning
Execution&monitoring
Closing
ML OL
82 Chapter 5 | Case Study Analysis: SCIENCO
• In PMOs with a low level of maturity, the self-interest of project managers comes before organisational best interest, and
• There is an observed lack of investment for conducting PM trainings in the organisation. Table 5-6 Participants’ quotes in SCIENCO’s PMO (developed for this research)
Subject Associated participants’ comments
Current PM methodologies
“…I don’t think that.. there is any particular methodologies across our organisation…” quoted by In.Sc.1
“...in general there’s not a formal methodology that’s been outlined…” quoted by In.Sc.2 “…Not really. No. there is some kind of risk assessment in place but it’s not I’m not aware of
any formal project management process…” quoted by In.Sc.5 “…In terms of an organisational arrangement there isn’t anything specific that we follow but
we are planning to develop such a thing …” quoted by In.Sc.3
Lack of service
to project manager
“…So once you get to this point it really does become more about the project leader managing that in a you know in a more personal way, sort of an ad hoc way…” quoted by In.Sc.4 “… apart from that there’s not really a structured approach to providing support for the
ongoing project management…” quoted by In.Sc.4 “…I’m not aware of anything in terms of time management, skills, no just general advice. But
as I said project support officer doesn’t get involved in…” quoted by In.Sc.5
According to the research findings, the mentioned criteria have been observed in the
SCIENCO’s PMO, which will discussed later. This means that both the maturity assessment
method and the existing situation of SCIENCO have consistently revealed that the selected
PMO has the first level of maturity in which: 1) the current PM methodology is still under
development, so project managers have to use their own methods to manage their project, and 2)
PM trainings need to be improved to increase the knowledge or project management as well as
PM competencies. In addition, the collected data from interviews confirm that the above
mentioned criteria for first level of maturity have been pointed out by participants, of which
some of their most common were presented in Table 5-6.
According to the current literature, the importance of PM methodology for managing
projects is raised at the first level of maturity (Kerzner 2005; Project Management Institute
2008b). In other words, at this level of maturity the existence of a common language among
employees and project managers becomes an important priority for organisations (Kulpa and
Johnson 2008). Therefore the initial steps should be undertaken at the first level of maturity, in
order to address the major issues of PM through developing a reliable PM framework (Crawford
2002; Kerzner 2013; Project Management Institute 2008b). During the process of document
analysis, a PM framework was in the SCIENCO. In the next section, this framework has been
analysed in order to shed more light on the current PM methodology in SCIENCO.
Project Management methodology in SCIENCO 5.5.1.1
As discussed earlier, the majority of SCIENCO’s participants believe that there is not any
PM methodology in place, however, there is a document which has been developed by PPD
(herein after it will be called PMO) and it is a single set of “One-SCIENCO” project
methodology to be used by project managers. From a respondent point-of-view, the existing PM
Chapter 5 | Case Study Analysis: SCIENCO 83
methodology has not been appropriately announced or trained. The current PM framework
consists of nine pages, by which the PM life cycle has been addressed in the five following
phases, and it is advised that is be followed across the whole enterprise:
• Identification phase: to identify problem, issue or request,
• Selection phase: to analyse alternative solutions and initiate primary steps,
• Definition phase: to plan all required activities, resource and requirements,
• Execution phase: to implement the proposed plan,
• Transition & Close out phase: to hand over the developed product/service These five phases are similar to the current PM methodologies, especially the waterfall
method, and it follows logical steps from initiating to terminating a project (Larmer and
Mergendoller 2010; Project Management Institute 2013). However, the existing PM standard is
not comprehensive, as it just addresses the management of a project in less than 10 pages with
limited supporting documents. Further analysis revealed the following about this framework: 1)
It is an abstract document in which just three out of nine pages discusses whole PM
methodology, and other pages explain some basic definition of PM, 2) the recognised three
pages just succinctly discuss high level steps of project management, while there are many
activities that are yet to be addressed by this framework, 3) there are limited supporting
documents, workflows, templates, forms and systems in order to facilitate the project
management, 4) There is a significant lack of clear explanation of using proper tools,
application or methods to support project managers, and 5) this abstract framework not only has
not been collaborated with the current processes and procedures, but also it has not been
appropriately trained or communicated to SCIENCO’s employees; the majority of them are
unaware of such a framework existing in SCIENCO.
In the next level of investigation, participants’ comments in regards to their thoughts about
the current PM methodology were analysed. The research findings revealed that the majority of
participants not only have not been trained or taught to use this standard but also are not familiar
with it at all. In addition, during the interviews, participants were asked that “what kind of PM
methodology is used at SCIENCO”. The outcomes of analysis for this question have been
represented in Figure 5-4 and it shows that the majority of respondents believe that there is “no
specific PM methodology” in place, which means that the current PM framework has not been
recognised by most of the participants, as for instance one of them explains that “…I don’t think
that. There is any particular methodologies across our organisation…” quoted by In.Sc.1. In
addition, participants believe that since there is limited PM framework in place, project
managers mostly use their own ways to manage organisational projects. In fact both of these
findings confirm that SCIENCO’s PMO has the first level of maturity (Kerzner 2005; Project
Management Institute 2008b).
84 Chapter 5 | Case Study Analysis: SCIENCO
After discussing these findings with the SCIENCO PMO coordinator, In.Sc.3, she explained
that they have commenced a project to both improve the current PM framework, and also
develop a comprehensive PM methodology to be used across the organisation. This statement
confirms another criterion of PMO with first level of maturity, in which the PM awareness is
raised at this level (Kerzner 2013). Also, it reveals that the need for a common language among
project team members across the SCIENCO has been accepted by an organisational senior
manager. Therefore the current PM standard could be considered as a tool to make common
language among SCIENCO’S project team members before introducing the new one.
Figure 5-4 PM Methodologies in SCIENCO (developed for this study)
As discussed, participants believe that there is lack of existence of a reliable PM standard in
SCIENCO. This is one of the reasons that SCIENCO’s managers use different methods or their
own ways to undertake their projects. This is another criterion of PMO with first level of
maturity in which project managers do not have access to any specific PM method, so they have
to use their own method (Kerzner 2013). In other words, the success of a project is very
dependent on project managers and how he/she leads the project to the end, as In.Sc.2 asserts
“…in SCIENCO that I’m aware of which basically means that a project will run on an
individual basis…”. This means that projects are more “hero driven” instead of “system driven”
which is expectable because of PMO’s low level of maturity (Kerzner 2005).
In summary, the research findings indicate that SCIENCO has initiated the development of
its PMO as well as an organisational-wide PM framework. The PMO assessment model and
data analysis consistently confirm PMO has the first level of maturity in which: 1) the
importance of PM has been raised, 2) however, there is no unique PM framework, 3) project
managers utilise their own method to manage a project, and 4) PM training courses are not
SCIENCO’s priority. According to Kerzner (2013) at the first level of maturity, PM systems
and tools have not been appropriately developed, so they need to be considered at a higher
maturity level. In the next section, the current PM systems and application will be investigated
to examine against Kerzner (2013)’s statement.
Current SCIENCO PM standard
No Specific PM methodology
PMBOK
PRINCE2
Project Manager do their own way to manageproject
0 2 4 6 8 10
Frequency, 4
Chapter 5 | Case Study Analysis: SCIENCO 85
Project management systems and tools in SCIENCO’s PMO 5.5.1.2
In order to obtain adequate information in SCIENCO, the combination of all three data
collection methods, i.e. triangulation, was utilised (Yin 2009). On one hand, interviews have
disclosed both participants’ thoughts about the current PM systems, and how they have been
utilised. On the other hand, direct observation and document review technique have provided
insightful and practical information about the current PM tools. These findings are in line with a
similar study, undertaken in SCIENCO’s PMO, in which both confirm the usage of the same
tools and application for project management in SCIENCO (Wiewiora, et al. 2009a). Table 5-7
depicts the research findings in this regard and shows the current systems and tools which are
employed by project stakeholders during the project lifecycle.
As shown in Table 5-7, numbers of systems were recognised in SCIENCO which are used
during the project lifecycle. For instance, SCIENCO utilises SAP as the total system to
collaborate all organisational and project costs and revenue information. According to Kerzner
(2013) at the highest level of maturity for PMO a fully integrated project management system is
expected in which all project information and data across the organisation are coordinated
through this system. The research analysis shows that SAP is just used for integrating project
cost and revenue in SCIENCO, so it does not integrate all project activities. This is consistent
with the research framework, since SCIENCO’s PMO has first level of maturity, so it is not
logical expect to find a fully integrated PM system in SCIENCO.
Table 5-7 The current systems and tools in SCIENCO’s PMO (developed for this research)
Application Propose of use
SAP To integrate cost and revenue of projects across SCIENCO Enterprise Opportunity
Pipeline (EOP) A system for managing new business leads and proposals, tracking
progress of contracts from draft to the end Wiki A system to find a person, information, solution or other required data Trim Document repository to capture the project activities
Gemma A system to spread information among groups and project team members
MS SharePoint Server To manage project information, report and activities as well as activity collaboration.
Off System Tools Suits Used the entire Project Life Cycle Process from Brief to Closing as
common tools for dialogue with clients, customers and all stakeholders
Common Costing Framework (CCF)
To manage, control and integrate all projects costs, individually and/or comprehensively.
Numerous systems such as Trim, Wiki, and the intranet are employed during the project
lifecycle, as depicted in Table 5-7, however, these systems have not just been developed for
project management purposes. Further investigations have disclosed that employees have been
faced with some issues in this regard and following are their comments:
“…I understand that there are tools available that can be used, but I haven’t actively
used them myself yet...”, quoted by In.Sc.4
86 Chapter 5 | Case Study Analysis: SCIENCO
“…It’s not an enforced system and then the thing is it is not necessarily public
available so the access to certain areas and regions can be restricted to a number of
people...”, quoted by In.Sc.3
“…We do have that…the Wikipedia system or we have folder structure where we can
put stuff in there. I think the trouble is that it is A. not used. Coherence through the entire
organisation and B. most of the time the access is restricted…”, quoted by In.Sc.4
As it could be inferred, these comments show that despite the existence of numbers of
systems in SCIENCO, participants believe that they face some issues, which need to be
addressed. In some comments, respondents directly have mentioned their challenges, as In.Sc.3
explained the issue of system integration in SCIENCO “…at the moment is that we’re doing
this trying to develop our PMO but their current systems are not integrated…”. This means that
the current systems need to be collaborated as participants complain about lack of integration.
Access to the current information is another issue that respondents are faced with. In other
words they believe that current systems do not provide appropriate access for them to capture
their required knowledge, For instance In.Sc.2 has commented: “…Sometimes you go back to it
when you really need to, somebody who was working on the project let’s say five years ago is
still here and there are people that are here for a long time. But there are some people there
you know that have never left. So if you want to you have to go back into like the Trim system
and so on and try to find some reports and you know some interactions and sometimes that’s
very difficult…”. This means that the current systems such as Trim need to be improved from an
accessing point-of-view.
From a knowledge management point of view, the majority of participants have mentioned
that the current system does not significantly support project knowledge management. In other
words, when respondents were asked to explain their thoughts about the contribution of current
tools as systems to support KM, they have not positively responded in this regard. For instance,
In.Sc.3 and In.Sc.4 have quoted followings to explain their thoughts in this regard: “…So when
you look at the system I don’t think we have a very good system implementation of capturing
this type of knowledge…”, “…But there is no such a thing to manage project knowledge from
beginning to closing…”.
In summary, there are numbers of systems and tools in place to facilitate project
management in SCIENCO, as shown at Table 5.7. The research findings revealed there are
some issues with the current systems, such as lack of integration and inappropriate access. In
addition, SCIENCO’s employees believe that the current systems should be improved in order
to significantly contribute to management of project knowledge. These findings are consistent
with a similar study at SCIENCO as it was revealed that the current systems do not significantly
facilitate the process of knowledge transferring (Wiewiora, et al. 2010). In the next section, the
Chapter 5 | Case Study Analysis: SCIENCO 87
issues of SCIENCO’s PMO will be discussed from a KM point-of-view to get insightful
information about the existing KM challenges of PMO with first level of maturity.
Knowledge Management challenges in SCIENCO 5.5.1.3
In order to recognise the issues of PMO from KM perspective interview, data was used as
the main source of research information for data analysis. To do so, the research framework was
followed in which interviews’ transcriptions were uploaded to the Nvivo, as data analysis
software. Then, the process of coding, both open coding and axial coding, was managed as is
advised by similar qualitative research (Charmaz 2014; Corbin and Strauss 2008; Wiewiora, et
al. 2010). In the first stage of the open coding process, more than 60 nodes were developed in
the Nvivo. These codes or comments have directly or indirectly mentioned the current
challenges from a KM point of view. Following are some of the examples of the coded
comments:
“…Just the PMO itself I’d say really it doesn’t really do it at all in terms of the identifying,
even re-identifying sort of stage of the knowledge as…”, quoted by In.Sc.4.
“… KM it is a huge challenge and actually I think it’s in general one of the biggest
challenges nowadays and the challenge is actually growth in a non-linear way with the size
of the organisation…”, quoted by In.Sc.1.
In the next level of analysis some of the Nvivo’s functions, such as queries and
classification, were utilised to find the relation among the current coded information.
Eventually, after running numbers of model five categories, the research axial codes were
developed as the major challenges of SCIENCO’s PMO. In other words, all sixty coded
comments, in regards to KM challenges, have been classified in five major categories through
following research methodology (Corbin and Strauss 2008). This means that each category, or
axial code, represents a number of associated issues of KM in the SCIENCO’s PMO. In other
words, the following KM challenges have been recognised through employing both “theory
making” and “Grounded theory” techniques, advised by qualitative research experts as methods
to make theory from similar data (Charmaz 2014; Corbin and Strauss 2008; Eisenhardt and
Graebner 2007):
1) Lack of KM practices and processes during project life cycle
2) Lack of appropriate systems to support project KM
3) Issue of locating and accessing right information and/or right expert
4) Difficulties of searching and detecting required knowledge
5) Issue of appropriate access to the existing systems
Table 5-8 is an example to present how participants’ quotes were related to open codes, and
also, how axial codes were developed accordingly.
88 Chapter 5 | Case Study Analysis: SCIENCO
Table 5-8 Example of using Axial &Open coding in SCIENCO (developed for this study)
Axial coding Open coding Quote’s samples
Difficulties of searching and detecting required
knowledge
Detecting proper knowledge "...Interestingly Google is the first place that if I want to look for something about SCIENCO…" "...However for finding knowledge we should, informally, find the right person. For instance, I know person X
is working here for twenty years so I can ask him but there is certainly not a system..." "...In a big organisation like this it is very hard to get the information across from one group to another or to
another site and to learn from the experience that the other people had..." "...So if a group sets up a project for a client X and they think oh that might be confidential it might be that only people within this group get access to that area in this Wikipedia system. And say two years later there’s another
group talking to client X again they won't have any knowledge about that previous history..."
Difficulties of searching in current DB Difficulty of locating right information
Searching outside DBs to find information Issue of filtering required knowledge
Lack of best practices What knowledge works what doesn't Where to find what I’m looking for
Issue of locating and accessing right information
and/or right expert
Difficulties to find an expert within organisation "...might know vaguely that this person has experience. But it would be a lot easier if I knew that there are three people who have had specific experience with this type of technology ..."
"...But it’s still umm there is still a specific need I think to be able to search through a PMO to identify or individuals or identify the particular individuals that have worked with a particular type of technology..."
"...I found it very difficult when I came in, on board to the SCIENCO because I was trying to actually find in the system what people’s capabilities were but I couldn’t find it..."
Finding right person to obtain knowledge Finding who works on what
knowledge about employees capabilities Researchers are protective on their knowledge
Lack of KM practices and processes during project life
cycle
Knowledge is getting accessible through managers "...But the new people don’t have access to knowledge and it’s difficult to go and ask questions constantly…"
"...if I need some knowledge/information, I would talk to stream leader or the team manager…" "...So it would be very difficult for me to follow what they have written in the lab book unless they were guiding
me through So again I would have to ask this particular person what is the knowledge..."
No integrity among current system to access knowledge No proper access of knowledge for new team members
Person's network is more important The more people you know the more access you have
Issue of appropriate access to the existing systems
Current system does not properly support KM "...At the moment we are learning a lot during the project, the team is learning a lot during the project. There is no formal requirement or any requirements to do reflections of what the project, what they learn and so on…"
"...So there is no system, there is just person that’s right, Or somebody else knows that I go to and asks that person, so it’s not really a system..."
"...So there are forms and I suppose the post project review would be a process but as I say it’s not one that’s
Lack of complementary proper systems Lack of incentive to use current systems
They are not generally user friendly They are not properly integrated with organisational tools
Lack of appropriate systems to support project
knowledge management
Capturing is more about to publishing "...You might have to do something again several times and it might take longer than what you’d planned to do…"
"... often we find ourselves working on thing, then finding out these guys have done something similar..." "...there are no formal mechanisms for it at all. In fact it’s probably one of our the greatest challenges ..." "...it would be important to make the system so that people could put the information in without having to
rewrite their publications or do you know do things along those line..." "...Capturing that is the purpose of the post project review and as I said we traditionally although there is a form
and structure for doing some kind of post project review, that hasn’t typically been used a lot..." "...the challenge certainly is as you know umm distributing that generated knowledge within the group and later
on passing it on to other people..." "...I don’t think there is high level of trust between them [to share knowledge]..."
Challenges of capturing lesson learnt Project meeting Challenges with Post Project review
Current knowledge are not properly reused Informality of KM activities
Knowledge is not logged or organised No reflection of previous knowledge on current project
Transferring is a significant challenge Capturing intangible knowledge is challenge
KM is undervalued and needs to get more attention
Chapter 5 | Case Study Analysis: SCIENCO 89
Figure 5-5 The exsisting KM challenges in SCIENCO’s PMO (developed for this study)
According to research methodology, the frequency of each phenomenon should be used to
analyse its importance. After running numbers of matrix queries in Nvivo, the obtained data was
transferred to Ms Excel for further analysis. As presented at Figure 5-5, the “lack of KM
practices and process during project life cycle” was recognised as the most frequent-mentioned
KM challenge, 34%, in SCIENCO’S PMO. In other words, more than thirty percent of the
existing issues are related to the lack of processes or procedures to address KM practices. Also,
participants believe the current PM practices need to be improved. Since SCIENCO’s PMO has
the first level of maturity, it faces the undeveloped PM practices. On the other hand, it could be
expected that in SCIENCO, as a research organisation, there are numbers of KM practices in
place by which research activities could be appropriately managed. However, participants
believe that the existing current KM practices do not meet their expectations, as they have
mentioned numbers of issues in this regard, which will be discussed later. For instance
Wiewiora, et al. (2009a) have investigated the knowledge transferring process in SCIENCO and
they found that this process is yet to be appropriately developed.
The second most frequent-mentioned challenge with 27 %, relates to the current systems in
the SCIENCO. The research findings revealed that participants believe the systems’
contribution to management of project knowledge needs to be improved. In other words, despite
the existence of some systems and tools in place, these are not adequate enough to satisfy
current requirements. According to Alavi and Leidner (2001) KM has three main components:
people, process, and technology. The KM system is the combination of processes and
technology to address how people should employ a system for managing knowledge
(Davenport, 1997). The issue with the current system implies that integration between KM
processes and existing technology as well as applications is an issue in SCIENCO. This means
that SCIENCO should not only develop new tools and applications, but also it needs to integrate
all systems, in order to address the lack of appropriate systems.
8%
27%
34%
17%
14% Issue of appropriate access to the existingsystems
Lack of appropriate systems to supportproject knowledge management
Lack of KM practices and processes duringproject life cycle
Issue of locating and accessing rightinformation and/or right expert
Difficulties of searching and detectingrequired knowledge
90 Chapter 5 | Case Study Analysis: SCIENCO
The third most frequent challenge is the way of locating or finding right expert or
information. As could be logically inferred, creating knowledge is the main objective of a
research organisation (Byounggu and Heeseok 2002; Nonaka 1994). SCIENCO as a research
organisation with numbers of branches and offices around Australia and Globe, manages a wide
range of activities to create knowledge for various purposes. In addition, SCIENCO’S experts
and scientists have been located in different places to undertake their projects. This might create
some issues such as parallel works in which employees are not appropriately informed of
similar works conducted by another, as following comments describes their concerns:
"... too often we find ourselves looking at or working on things and then finding out
you know these guys have done something similar...", quoted by In.Sc.4
"...I found it very difficult when I came in, on board to the SCIENCO because I was
trying to actually find in the system what people’s capabilities were but I couldn’t find
it...", In.Sc.1
The issue of locating information or person impact on managing organisational knowledge,
specifically, knowledge reusing and transferring (Goffin, et al. 2010; Nonaka and Takeuchi
1995; Wiewiora, et al. 2009a). As will be discussed later, both the areas of knowledge reusing
and transferring are not satisfactory. This means that addressing the above mentioned challenge
will contribute to improve knowledge transferring and reusing, and eventually project
knowledge management.
The fourth most-frequent challenge is the issue of searching and detecting required
information. According to the collected data, all of participants have mentioned some problems
to explain their concerns about searching and finding current knowledge. They have pointed out
numbers of concerns such as: filtering current information; lack of best practices; and detecting
proper knowledge. For instance, one of the SCIENCO’s senior managers interestingly quoted
that: "...Google is the first place that if I want to look for something about SCIENCO…".
According to the current literature, access to right information impacts on KM in general,
specifically knowledge capturing and reusing (Koskinen and Pihlanto 2008; Senaratne and
Sexton 2009; Yuan and Yang 2009). This means that difficulties of finding the required
information impact on capturing and reusing project knowledge, therefore this issue needs to be
addressed to improve the status of KM in the SCIENCO.
Access to current systems and knowledge is the fifth most frequent mentioned issue in the
SCIENCO’s PMO. According to respondents’ comments, people’s networks play an important
factor to access to the current information in the SCIENCO. In addition, they believe that
knowledge is normally accessible through their managers, as one of the interviewees quotes:
"...if I need some knowledge or information, I would talk to stream leader or the team
manager…". According to existing literature, appropriate access to knowledge plays a strong
Chapter 5 | Case Study Analysis: SCIENCO 91
role in creating and reusing knowledge (Alavi and Leidner 2001; Nonaka and Teece 2001). This
means that SCIENCO could face some issues in regards to knowledge creation and reusing. As
it has been discussed, knowledge reusing is the less developed KM process among other KM
processes. In other words, addressing the above mentioned issue will improve both knowledge
reusing, and eventually quality of project knowledge management.
In summary, five challenges have been recognised in SCIENCO’s PMO, from a KM point of
view. As discussed, the mentioned challenges were examined through employing the research
framework as well as the current literature, in order to investigate their relations with four KM
processes. It was revealed that all KM processes have been impacted by these issues, especially
knowledge reusing. This means that the current status of project knowledge management needs
to be developed. In this section, the primary parts of first question (RQ1- How are KM practices
and processes employed in the PMOs?) have been discussed to explore KM issues in
SCIENCO. In the next section, the second part of the first research question, the required types
of knowledge at project lifecycle, will be discussed to find the importance of knowledge types
during the project life cycle.
The required types of knowledge at project life cycle 5.5.1.4
The main reason for investigating required knowledge is to understand the importance of
each type of knowledge for, ultimately, answering another part of the first research question.
According to the research framework, eight types of knowledge are critical in project
environments: Project Management Knowledge; Knowledge about Procedures; Technical
Knowledge; Knowledge about Clients, Costing Knowledge; Legal and Statutory Knowledge;
Knowledge about suppliers; and Knowledge of who knows what. In order to rate the importance
of each knowledge type, survey forms were distributed among the eight participants and,
eventually, seven completed forms were returned (about 85 % response rate). In the survey,
respondents were asked to rank the above mentioned types of knowledge from 1, the least, to 8,
the most important knowledge during four phases of a project life cycle.
After collecting data and entering to MS Excel sheets, an Analytical Hierarchy Process
(AHP) was employed to analyse survey responses. This technique is a process that uses
hierarchical decomposition through a weighted matrix to analyse complex information in multi-
criterion decision (Ghodsypour and O'brien 1998). It is a highly recommended technique for
ranking the importance of competing factors in operational management (Lindner and Wald
2011; Stam and Silva 1997). This technique was employed and the advised processes were
followed to rank the importance of types of knowledge in SCIENCO’s PMO, as shown at
Figure 5-6.
92 Chapter 5 | Case Study Analysis: SCIENCO
Figure 5-6 Types of required knowledge in SCIENCO (developed for this research)
The research analysis revealed that “knowledge about customers” and “costing knowledge”
are the most important types of required knowledge at the initiation phase. According to
PMBOK (2012) the client’s expectations and their related costs are very important to initiate
projects, which is consistent with this finding. In contrary, “Technical knowledge” and
“Knowledge about procedures” have been mentioned as less important types of knowledge at
initiation phase. The main objective of the initiation phase is to conduct high level activity for
preparing projects, therefore, technical knowledge and/or procedural knowledge, which are
mostly used for planning purposes, do not have high priority at this stage (Kerzner, 2013).
The main aim of the planning stage is obtain details of client expectations in order to plan
for meeting all of them (Project Management Institute, 2012). Interestingly, research findings
are in line with mentioned theory in which “knowledge of who knows what” and “Knowledge
about client” were indicated as the most important types of knowledge, while respondents state
that “legal knowledge” and “procedural knowledge” are less likely to be required at this stage.
Moreover, “technical knowledge” has become more important at this stage, compared to the
initiation phase, which is quite logical since it is used to provide project plans and resource
allocation.
4
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6 Initation
4
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Execution 7
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Closing
Chapter 5 | Case Study Analysis: SCIENCO 93
“Knowledge about client” has still remained as the most important required knowledge at
the execution phase. The second most important knowledge at this stage is “Project
Management Knowledge”, which climbed from 4th level to 7th. At this stage the project
manager and the team play a crucial role to put everything together to follow the project plan
and, ultimately, meet client’s expectations (Project Management Institute, 2012). On the other
hand, existence of an appropriate “technical knowledge” is major requirement to undertake the
assigned activities, and has been ranked as the third most important knowledge. The fifth place
has been assigned by respondents to “Legal knowledge”, which was the least important at
planning stage. It is generally accepted that all legal and standard requirements should be mostly
followed and met at execution phase that is wisely pointed out by participants.
The purpose of the closing phase is to confirm the completion of project deliverables to
satisfy project stakeholders’ expectations (Project Management Institute, 2012). Participants
mentioned “knowledge of project management” and “knowledge about client” as the most
important types of knowledge among others at closing phase, while they believe that “technical
knowledge” and “legal knowledge” are not very important at this stage. According to project
management best practices, a project could not be properly closed without meeting the client’s
expectation, and, this could not be appropriately undertaken without good understanding of
project management tools and techniques. In addition, “technical knowledge” and “knowledge
about suppliers” are mainly used during planning and execution phase, since closing is all about
handing out the deliverable.
After analysing the rank of each type of knowledge at various phases, another level of
investigation was carried out to determine the overall rank of eight types of knowledge,
regardless of project lifecycle phases. Similarly, the AHP technique was used to assign
appropriate weights for each entity, then, their weighted percentages were calculated and
ranked, as depicted in Table 5-8.
Table 5-9 Types of required knowledge in SCIENCO (developed for this research)
Types of Knowledge \ Project Phase
Individual Rank Total weighted Rank
Initiation Planning Execution Closing Rank Percentage Project Management Knowledge 4 4 7 7 6 14.86%
Knowledge about Procedures 2 2 1 8 3 8.78% Technical Knowledge 1 5 6 1 3 8.78%
Knowledge about Clients 8 7 8 5 8 18.92% Costing Knowledge 7 6 4 3 5 13.51%
Legal and statutory Knowledge 4 1 5 3 3 8.78% Knowledge about suppliers 5 4 3 4 4 10.81%
Knowledge of who knows what 6 8 3 6 7 15.54%
The research analysis revealed that, from SCIENCO’s employees’ point of view,
“knowledge about client”, “Knowledge of who knows what”, and “project management
knowledge” are the most critical types of knowledge, while “technical knowledge” and “Legal
94 Chapter 5 | Case Study Analysis: SCIENCO
knowledge” are the less important ones. There might be a number of reasons for this ranking: 1)
those types of knowledge with lowest levels, could indicate that employees are happy with
them, and it is reasonable because SCIENCO is research company and its employees possess
good technical knowledge as well as legal knowledge, 2) while higher ranked knowledge might
be the indication of employees’ expectation to improve the provision of them.
These findings could be a useful indication for PMO with the low level of maturity, in order
to improve their KM system. In other words, it could be inferred that the first three types of
knowledge are the most important ones to be improved if the PMO has low maturity levels.
Figure 5-7 The required types of knowledge in SCIENCO (developed for this research)
From the PM point of view, interestingly, the first three types of knowledge are very
important knowledge to initiate and undertake the project (Project Management Institute, 2012).
The maturity level for SCIENCO’s PMO is one which means that there are numbers of
challenges to be solved at PMO, one of which is KM. Previously, challenges of KM at PMO
were discussed and, then, it was concluded that not only current systems need to be improved
but also there are limited systems or procedures in place to support project knowledge
management. Therefore, the provided ranking could be a significant implication of required
types of knowledge when a PMO has the first level of maturity. In other words, PMOs with
similar level maturity could focus on improving their system through using the above mentioned
ranking as a practical best practice.
In summary, eight types of knowledge were examined in SCIENCO to explore the
importance of them during project lifecycle. In addition, the general ranking has been analysed
to find the importance of knowledge types at first level maturity, in which the following ranking
was revealed: 1) Knowledge about Clients, 2) Knowledge of who knows what, 3) Project
Management Knowledge, 4) Costing Knowledge, 5) Knowledge about suppliers, 6) Knowledge
about Procedures, 7) Technical Knowledge, 8) Legal and statutory Knowledge. So far, the first
two sub-questions have been discussed to answer the first research question (RQ1- How are KM
Initation Planning Execution Closing
4 4
7 7
2 2
1
8
1
5
6
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8
7
8
5
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Project Management Knowledge Knowledge about Procedures Technical KnowledgeKnowledge about Clients Costing Knowledge Legal and statutory KnowledgeKnowledge about suppliers Knowledge of who knows what
Chapter 5 | Case Study Analysis: SCIENCO 95
practices and processes employed in the PMOs?). The next section aims to completely answer
the first research question as well as the second research question (RQ2- How do KM practices
contribute to improve maturity level of the PMO?), through discussing four knowledge
management processes and their subsequent KM practices.
Knowledge management practices and processes in SCIENCO 5.5.2
As discussed in the Chapter 3, the research framework, four KM processes were adopted in
which each process has numbers of KM practices. Also, it was assumed that all four KM
processes are employed throughout the project lifecycle (PLC) except the closing phase, as
depicted in Table 5-10. This means that all KM processes should be utilised during the PLC,
however, knowledge capturing is the only KM process which should be used at closing phase.
This assumption will be examined during the case study analysis.
Table 5-10 KM processes and PLC (adopted from Owen and Burstein (2005))
Initiation Planning Execution
& monitoring
Closing
Knowledge Creation √ √ √ Knowledge Capturing √ √ √ √
Knowledge Transferring √ √ √ Knowledge Reuse √ √ √
In this section, the second research question (RQ2- How do KM practices contribute to
improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so the
following steps will be carried out: 1) investigating the utilisation of KM practices and KM
processes at four phase of PLC, 2) examining the above-mentioned assumption about KM
processes at project lifecycle, and 3) ranking the importance of four KM practices at each phase
of the project lifecycle.
All collected data through interviews, questionnaires, direct observation, and document
analysis were used to improve the quality and accuracy of research outcomes (Creswell 2009;
Yin 2009). Nvivo and MS Excel and other appropriate tools have been employed to analyse the
collected data, as they have been advised to be used for qualitative research (Bakker, et al. 2011;
Lindner and Wald 2011). According to the research framework, numbers of practices have been
assigned to each KM process by which knowledge management is supported in a project, as
shown in Table 5-11. These KM practices were used to develop numbers of nodes in the Nvivo
through employing open and axial coding techniques (Bakker, et al. 2011; Corbin and Strauss
2008). In addition, the advised procedures to code interviews’ data have been followed to
develop associated codes in this regard, as depicted at Figure 5-8. At the final stage of analysis,
the research framework was employed to integrate all codes for developing final axial codes.
These steps will be followed in this section to discuss the utilisation of KM practices in the
SCIENCO, and ultimately answer the second research question.
96 Chapter 5 | Case Study Analysis: SCIENCO
In the first stage, analysing KM practices during the project lifecycle has been carried out
through examining the collected data from interviews and direct observation. The open coding
technique was utilised to understand and, then, categorise respondent’s quotes. During this
stage, a regular activity was undertaken to compare the coded commonest and the research
framework in order to improve the quality of the developed categories (Julian 2008). Therefore,
all of interviews’ comments and quotes, related to KM, were associated to one or more KM
practices and consequently, KM processes. In other words, for each KM process and practice, a
number was obtained which shows the frequency of an associated phenomenon. This frequency
number was created through using the matrix query function in the Nvivo and it has been
utilised as one of the research data to analyse KM in the SCIENCO (Lindner and Wald 2011).
Figure 5-8 presents a snapshot of Nvivo as an example of how KM processes are related to KM
practices in this study.
Table 5-11 KM processes and their associated KM practices (developed for this research) Practices for
Knowledge Capturing • Expert locator • Frequently ask questions
(FAQ) • Knowledge repositories • Data base • Document Management
System (DMS)
• File management system • Management information
system(MIS) • Knowledge detection tools • Formal and informal event • Intranet • Knowledge inquiry system
Practices for Knowledge Creation
• Formal and informal event • Workshops & seminar • Community of practices • Best Practice Cases • Research services • Expert system
• Experience Report • Knowledge Broker • Data mining • Documentation search • Deductive & Inductive
thinking
Practices for Knowledge Transferring
• Project bulletin and reports
• Communication channel • Knowledge list • Training &Mentoring • Discussion forums • Data Base
• Video and Tele Conference meeting
• Yellow page • Intranet • Knowledge directories • Formal and informal events
Practices for Knowledge Reusing
• Electronic notice board • Document Management
System (DMS) • Intranet • Expert systems • Data base • Knowledge map
• Yellow page • Knowledge detection too • Lessons learnt • Data mining • Formal or informal event
In order to analyse the collected data, frequency was used as the main criteria to explore the
current status of knowledge management in this case. During the process of coding interviews,
more than one hundred and seventy (170) comments and quotes, which have been directly
mentioned to explain the usage of KM practices, were recognised and then coded accordingly.
After analysing SCIENCO’S employees’ comments, it was revealed that more than forty-four
percent of KM practices are employed at execution and monitoring phase, while only less than
fourteen percent of them are utilised at closing stage, as depicted in Table 5-12. This means that
usage of KM practices at the execution phase is more than for the closing phase. These findings
revealed that the majority of KM practices are managed at execution phase in comparison to
three other phases. This is consistent with the nature of SCIENCO’s business as a research
organisation. In other words, the execution phase at research projects is more about creating and
Chapter 5 | Case Study Analysis: SCIENCO 97
developing a new technology and knowledge, therefore, numbers of KM practices should be
used to contribute for managing project knowledge (Argote et al., 2003).
Figure 5-8 A snapshot of KM process categories in the Nvivo (developed for this research)
From a KM process perspective, more than fifty percent of KM practices are utilised for
knowledge capturing, while only less than three percent are employed for reusing, as shown in
Table 5-12. This means that not only is knowledge capturing fairly stronger than the other KM
processes, but also participants believe the current KM practices mostly support the knowledge
capturing and then knowledge creation. In addition, knowledge reusing is not appropriately
supported by existing KM practices, which is line with the previous research findings in the KM
98 Chapter 5 | Case Study Analysis: SCIENCO
challenges in SCIENCO. In other words, reusing of the knowledge could be of the biggest
challenges from a KM point of view but more evidence is required to make proper conclusions
in this regard, which will be discussed later.
Table 5-12 The usage of KM processes in SCIENCO (developed for this research)
Initiation Planning Execution &
monitoring Closing
26.4% 15.3% 44.4% 13.9% Knowledge Creation 34.2%
Percentage of KM processes Knowledge Capturing 51.3%
Knowledge Transferring 11.8% Knowledge Reuse 2.6%
According to the above mentioned findings, the associated practices to knowledge capturing
and creation have been mentioned as more than eighty percent, while knowledge transferring
and reusing have less than 15 percent all together. As a matter of fact, knowledge reusing and
transferring has been respectively quoted just two and nine times, which means that participants
believe there are limited KM practices to support both transferring and reusing knowledge in
SCIENCO. These findings are in accordance with another study that was undertaken two years
ago at SCIENCO’s PMO to investigate the knowledge transfer in which authors have realised
the current challenges of knowledge transfer (Liang, et al. 2009).
From a project lifecycle point of view, the usage of KM practices at each project phase has
been analysed to examine how KM processes are used during a project life cycle. As Figure 5-9
presents, at initiation phase there are numbers of KM practices in place to support knowledge
capturing and creation processes, while knowledge transferring and reusing are yet to be
improved in this phase. This means that the lack of KM practices to support knowledge reusing
at this stage is significant. According to PMBOK (Project Management Institute 2013) both
initiation and planning are most important phases in which to utilise previous experience and
similar projects’ knowledge, however, knowledge reusing in SCIENCO not only in initiation
but also in other project phases has not been appropriately addressed.
At planning and execution phase, as Figure 5-9 depicts, all KM processes are supported
through numbers of KM practices, however, similar to the initiation phase, respondents believe
that most of the current KM practices facilitate the process of knowledge creation and capturing.
In other words, limited numbers of KM practices have been developed to support knowledge
reusing and transferring. According to the existing PM methodologies, knowledge creation at
planning phase is an important activity as all the project plans should be created at this phase
(Bentley 2009; Project Management Institute 2013; Reich and Wee 2006). The research
findings confirm this expectation in which planning is an important phase to create knowledge,
as shown at Figure 5-9.
Chapter 5 | Case Study Analysis: SCIENCO 99
Figure 5-9 KM processes at project lifecycle (developed for this research)
All KM processes should be employed at execution phase (Arora, et al. 2010; Owen and
Burstein 2005). The research findings explored that knowledge capturing and creation are fairly
supported through current practices, while knowledge reusing and transferring are to be
improved in this phase. According to the current literature, knowledge reusing at execution
phase is very helpful to improve the productivity and efficiency through benchmarking and
looking at similar projects (Polyaninova 2010). In addition, reusing previous knowledge helps
to monitor and control through defining proper criteria and measures (Project Management
Institute 2013). Also, training, mentoring and other simular activities to share and transfer
knowledge should be undertaken at execution phase, but little evidence was found in this
regard. Therefore, it could be initially concluded that KM practices to support knowledge
reusing and transferring at execution phase, are yet to be addressed in SCIENCO.
According to the research framework it has been assumed that only knowledge capturing
should be employed at closing phase (Owen and Burstein 2005). As shown at Figure 5-9, this
assumption has been confirmed since respondents believe that at closing phase the current KM
practices only support knowledge capturing, while there are few KM practices to facilitate other
KM processes. This means that the closing phase is all about delivering project outcomes and
capturing the knowledge activities such as lessons learnt and post project review (Kerzner 2009;
Project Management Institute 2013). In other words, from participants’ point of view, the
existing KM practices contribute to capture knowledge, which is consistent with the research
framework.
In summary, it could be concluded that all KM processes are supported, to some extent, by
associated KM practices at three project phases, and only knowledge capturing is managed at
closing phase, in SCIENCO. The research findings revealed that knowledge creation and
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Capturing
Creation
Transferring
ResuingReusing
100 Chapter 5 | Case Study Analysis: SCIENCO
capturing are supported, to some degree, by numbers of KM practices, while knowledge reusing
and transferring are yet to be developed. In addition, knowledge reusing is rarely supported
through current KM practices. As discussed earlier, the current maturity level of SCIENCO’s
PMO is one which means that PM is yet to be addressed in this organisation (Kerzner 2013).
This means that there are limited PM practices to support project management, and
consequently project knowledge management. Therefore, lack of KM practices could be
expected at this level of maturity, however, there are some bases for KM which need to be
improved. In the next sections each knowledge process will be individually discussed to answer
the second research question (RQ2. How do KM practices contribute to improve maturity level of
the PMO?).
Knowledge Capturing in SCIENCO’s Project Management Office 5.5.2.1
According to current literature, knowledge capturing is the only KM process that should be
employed from the beginning to the end of a project lifecycle (Owen and Burstein 2005). This
assumption was examined through investigation of obtained data, specifically from interviews
and survey-questionnaires. As discussed earlier, the research findings are in accordance with the
above-mentioned theory which means that SCIENCO’s employees believe that at closing phase
they have only employed knowledge capturing practices. In addition, further analysis
determined that more than 84 quotes, out of 160 in total, are related to utilisation of knowledge
capturing practices at four project phases: 25 at Initiation; 9 at planning; 34 at execution &
monitoring; and 16 at closing. In addition, Figure 5-10 indicates the frequency of obtained data
related to KM practices and it shows the utilisation of knowledge capturing practices at various
project phases. As this figure depicts, a documents management system (DMS) database is the
most frequent KM practice to support knowledge capturing, which has been mentioned by
participants.
In the next level of analysis, open coding and axial coding techniques were employed to
investigate the associated comments and quotes (Miles & Huberman, 1994). At depicted in
Table 5 13, there are eleven categories to support knowledge capturing. These categories were
used alongside the outcomes of the open coding process and, eventually, it was revealed that 7
out of 11 categories of knowledge capturing practices have mentioned by SCIENCO’s
employees. In other words, participants believe that seven types of knowledge capturing
practices are facilitated through the current developed practices, however, some of them are yet
to be improved. For instance, respondents believe that while the existing documents
management system and databases are fairly developed, the file management system and
management information system need to be enhanced. In addition, the research findings
explored that four KM practices, knowledge detection tools, knowledge inquiry systems,
frequently asked questions, and expert locater, are yet to be addressed in the SCIENCO’s PMO.
Chapter 5 | Case Study Analysis: SCIENCO 101
Figure 5-10 Knowledge capturing in SCIENCO’s PMO (developed for this research)
As Table 5-13 illustrates, there are three columns to discuss the status of knowledge
capturing practices in SCIENCO. The first column is the axial code, which is based on the
research framework. The second column represents the name of system, tools or practice, and is
used to support the associated knowledge capturing practice, or first column. And the third
column illustrates the frequency of KM practices, which were obtained through Nvivo analysis
functions.
From a project lifecycle point of view, these practices are employed mostly at execution and
initiation phases, while at planning and closing phase only 11, and 9 comments were
recognised. This means that, from the participants’ perspective, more than seventy percent of
knowledge capturing activities take places at initiation and execution phase. In other words,
participants believe that at both planning and closing phases the current KM practices are as
strong as initiation and execution phases. The lack of instruction and procedures has been
mentioned as the main reason of such as difference. Therefore, this is the PMO’s responsibility
to develop practices for addressing appropriate tools and processes in this regard.
As it could be found in Table 5-13, the documents management system (DMS) is the most
frequently mentioned KM practice. This means that DMS satisfactorily supports knowledge
capturing process from the respondents’ point of view. In addition, participants believe that the
current databases (DB) such as Trim and Wikis, contribute to the process of capturing project
knowledge. Also, SCIENCO has a unique way to capture some of the knowledge through a
publishing and e-publishing system (EPS), by which employees are advised to provide papers
for representing their tacit knowledge.
0
2
4
6
8
10
12
Initiation Planning Execution andMonitoring
Closing
Data base
Document Management System (DMS)
Hand Notebooks
Expert locator
File Management System(FMS)
Formal or Informal events
Frequently Ask Questions (FAQ)
Intranet
Knowledge detection tools
Knowledge inquiry system
Knowledge repositories
Management Information System(MIS)
102 Chapter 5 | Case Study Analysis: SCIENCO
The above mentioned KM practices are the most frequent KM practices to support
knowledge capturing in SCIENCO’s PMO. In other words, from participants’ point-of-view, the
current DMS, DBs and EPS contribute to the process of knowledge capturing, and KM in the
SCIENCO. However, further analysis through using the relationship function in Nvivo revealed
that there are correlations between these KM practices and the recognised KM challenges in
SCIENCO. For instance, despite the existence of DBs in SCIENCO, participants believe that
they have an issue of accessing to current DBs, as In.Sc.1 comments: “…sometimes I use
Google to search for accessing our published papers…“. This means that despite the existence
of some KM practices to support knowledge capturing, they are still faced with numbers of
issues, such as lack of accessibility and search-ability, which need to be addressed. According
to Alavi and Leidner (2001), appropriate systems such as DBs and DMS significantly contribute
to knowledge capturing in organisations, therefor SCIENCO’s PMO should improve the quality
of these KM practices through addressing the recognised challenges.
Table 5-13 Knowledge capturing’s categories and practices (developed for this research)
Knowledge capturing category Associated System/Practices in SCIENCO Frequency
Data base • Enterprise Opportunity Pipeline(EOP) • Trim • Wikis
18
Document Management System (DMS)
• Hand Notebooks • Intellectual Property (IP) documentation • Lessons learned • Meeting minutes • Off system and assistant Tools • Post project review • Project Briefing • Project Debriefing • Project Reports
35
Expert locator • None 0 File Management System (FMS) • Windows base system 4
Formal or Informal events • Regular meeting 3 Frequently Ask Questions (FAQ) • None 0
Intranet • MS SharePoint 6 Knowledge detection tools • None 0 Knowledge inquiry system • None 0
Knowledge repositories • Publishing and E-publishing system 13 Management Information System
(MIS) • SAP 4
In addition, the research findings recognised that some practices such as file management
system (FMS), management information system (MIS) and formal and informal event are being
used in SCIENCO to facilitate knowledge capturing. Since their frequency is not significant, so
it means that respondents do not frequently utilise them for knowledge capturing purposes. In
other words, these KM practices have not been recognised by SCIENCO’s employees for
managing KM activities. This is consistent with one of the recognised challenges, i.e. lack of
strong KM practices in the SCIENCO. In other words, there are some KM practices in place
Chapter 5 | Case Study Analysis: SCIENCO 103
which need to be appropriately communicated and trained to be effectively employed for
capturing project knowledge.
On the other hand, four out of eleven KM practices for knowledge capturing have not been
recognised in the SCIENCO’s PMO, i.e. Expert locator, knowledge detection tools, knowledge
enquiry system, and FAQ. This means that SCIENCO’s PMO should address these practices as
they significantly contribute to project knowledge management (Kamara, et al. 2003; Tan, et al.
2007). In addition, further analysis through using Nvivo revealed that the absence of these
practices has been mentioned by some participants. For instance, participants explained some
concerns in regards to finding the right expert to get right information, and consistently Expert
locater is a KM practice that could address their concerns. In other words, most of the current
KM challenges in the SCIENCO could be addressed through developing an appropriate KM
system, in accordance with the research framework.
According to the current KM literature, at first level of maturity, organisations are advised to
prepare an appropriate environment for both developing a common language for PM and, also,
realising the importance of KM (Desouza 2006; Kankanhalli and Pee 2009). According to the
research finding, all respondents have realised the importance of KM for improving project
success rate, as all of them have directly mentioned some concerns from a KM point-of-view.
This means that they have at least basic knowledge of project management, which is consistent
with the findings of a similar study in SCIENCO (Julian 2008). In other words, the recognised
awareness of importance of KM for project success in SCIENCO has met the basic requirement
for the first level of maturity, from a KM point-of-view. However, according to the research
framework, SCIENCO’s PMO should initiate an appropriate plan to address the recognised
challenges, in order to achieve the next level of maturity.
In summary, knowledge capturing is the most frequently mentioned phenomena among all
four KM processes, in which more than 50% of comments were found this regard (see table 5-
12). More than 40% of current KM practices support knowledge capturing, however, there are
still numbers of challenges in this regard. At the first level of maturity, it was found that the
subsequent practices which are utilised for capturing knowledge are databases; MIS; DMS;
knowledge repositories; and formal and informal events. In addition, some other practices such
as knowledge detection tools, expert locators, knowledge inquiry system and FAQ are yet to be
addressed in the SCIENCO PMO. The research findings have not revealed any inconsistency
against the research framework, as the SCIENCO PMO has the first level of maturity.
Knowledge Creation in SCIENCO’s Project Management Office 5.5.2.2
SCIENCO, as a research organisation, has significantly contributed to a body of knowledge
in many areas such as agriculture, oil and gas and mining, therefore, it could be inferred that
“creating knowledge” is one of SCIENCO’s missions (Julian 2008). In fact, most projects in
104 Chapter 5 | Case Study Analysis: SCIENCO
SCIENCO are defined to propose both a solution for current challenges in various industries or
to develop a technology or new knowledge. According to Nonaka (2001), knowledge creation
has four stages: Socialisation, Externalisation, Combination; and Internalisation or SECI.
According to the research framework, SECI could be supported through numbers of KM
practices, which have been illustrated and defined in the research framework (see Table 5-11 &
Figure 5-11). In order to investigate the current KM practices of knowledge creation, numbers
of questions were designed by using the KM framework. These questions were developed to
elicit participants’ thoughts about those practices that support creation of knowledge within
SCIENCO. These practices were classified to eleven categories and associated practices as
shown in Table 5-14.
Table 5-14 Knowledge creation’s categories and pratices (developed for this research)
Knowledge Creation categories Associated System/Practices in SCIENCO Frequency
Best Practice Cases • None 0 Community of practices • None 4
Data mining • None 0 Decision support system (DSS) • None 0
Deductive & Inductive thinking • Brainstorming, • Think tank 10
Documentation search • None 1 Experience Report • None 1
Expert systems (ES) • Expert Interview • Expert Judgment 6
Informal and formal Event • Formal face to face meeting • Workshops & seminar 28
Knowledge Broker • None 0
Research services • Experimentation • Simulation • Use of Metaphors
12
The initial investigation shows that more than fifty-three percent of knowledge creation
activities are undertaken at the execution phase, as shown in Figure 5-11. This outcome is in
line with the previous discussed assumption in which SCIENCO, as a research organisation,
undertakes projects to create knowledge. In other words, in SCIENCO the majority of
knowledge creation activities are well-conducted in the execution phase, where some KM
practices such as experiments and simulations are managed to create knowledge. In addition, the
research findings revealed that there are few knowledge creation activities at closing phase,
which is consistent with the research framework, as depicted at Figure 5-11. In other words, as
the research framework assumes, little activity has been recognised to facilitate knowledge
creation.
As illustrated in Table 5-14 and Figure 5-11, “formal and informal events” are the most
frequent KM practices for knowledge creation purposes, from participants’ points-of-view. In
other words, SCIENCO’S employees believe that most of the knowledge that they have created
Chapter 5 | Case Study Analysis: SCIENCO 105
so far, have been through face-to-face conversations, meetings (formal or informal),
participating in seminars, workshops or conferences. According to KM theories, “formal and
informal event” is a practice to support both socialisation and externalisation process for
creating knowledge (Nonaka and Takeuchi 1995). The following is an example of one of the
quotes to explain how formal and informal events contribute to create knowledge in the
SCIENCO.
“…more often will typically be one researcher who will spend a lot of time
developing the concept themselves and fleshing it out and then they will communicate
that idea…”, quoted by In.SC.4
Figure 5-11 Knowledge Creation practices in SCIENCO (developed for this research)
The second most frequent KM practice for facilitating knowledge creation is “research
services”. Three sub-practices are used to support research services: simulation, use of metaphor
and experimentation. According to Nonaka and Teece (2001) the research services support
“internalisation” to support the knowledge creation process. Since SCIENCO is a research
organisation, there are numbers of tools in place to manage knowledge creation. Following is
one of the comments which is mentioned to explain the experimentation: “… will work together
and they’ll do a little trial of something and then produce a model …”, quoted by In.Sc.3
The third most frequent knowledge creation practice is “deductive and inductive thinking”
such as brainstorming and think-tank. These types of KM practices support both
“externalisation” and, also extent “socialisation” processes of knowledge creation (Nonaka and
Teece 2001). Similarly, “expert system” and “community of practices” are the fourth and fifth
most frequent KM practices in the SCIENCO’s PMO. As shown in Figure 5-11, the research
findings revealed that these KM practices are used mostly at execution and monitoring phase. In
other words, both KM practices facilitate the socialisation part of SECI in which experts from
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Initiation Planning Execution andMonitoring
Closing
Best Practice Cases
Community of practices
Data mining
Decision support system
Deductive & InductivethinkingDocumentation search
Experience Report
Expert system
Informal and formal Event
106 Chapter 5 | Case Study Analysis: SCIENCO
various areas could get together and discuss a subject from different perspectives, in order to
create a new knowledge (Hsieh, et al. 2009; Peltola, et al. 2002; Wiig 1997b). This means that
these two practices have been fairly developed in the SCIENCO to contribute to the process of
knowledge creation.
On the other hand, the research analysis revealed that 6 out of 11 KM practices for
facilitating knowledge creation have not been appropriately addressed in the SCIENCO. In
other words, limited evidence has been explored to support utilisation of some of the KM
practices, i.e. knowledge broker, data mining, decision support system, and documentation
research. These types of practices mostly support the “combination” process of SECI model for
facilitating knowledge creation (Nonaka and Takeuchi 1995). This means that in SCIENCO’s
PMO, the “combination” process needs to be addressed, as numbers of practices to support
“socialisation”, “externalisation”, and ”internalisation” have been fairly developed and are in
place.
In summary, knowledge creation is the second most frequent KM process mentioned by
SCIENCO’s employees. In fact, research findings revealed that more than thirty percent of
current KM practices support knowledge creation in SCIENCO’s PMO. According to Nonaka
and Takeuchi (1995) four sub-processes or SECI are the main constituents of the knowledge
creation process. The research outcomes explored that there are some KM practices to fairly
support “socialisation”, “externalisation” and “internalisation”, however ”combination” is yet to
be addressed in the SCIENCO. As discussed earlier, SCIENCO’s PMO has the lowest level of
maturity, therefore, it is plausible to both explore some incomplete systems and recognise some
gaps from a KM point-of-view. According to the research framework, at this first level of
maturity, the awareness of knowledge creation should be raised alongside some basic KM
practices. Therefore, the SCIENCO’S PMO has met the minimum requirements in accordance
with the research framework.
Knowledge Transferring in SCIENCO’s Project Management Office 5.5.2.3
Similar to other KM processes, the research framework was employed to explore the current
knowledge transferring status at SCIENCO. After coding interviews, eleven categories were
developed in which some of them have some sub-categories, as depicted in Table 5-15.
According to the research findings, knowledge transfer is the third most frequent-mentioned KM
process. In fact, less than 12 percent of quotes and comments have discussed SCIENCO’S KM
activities from a knowledge transferring point-of-view. This means that from respondents’
point-of-view, the knowledge transferring process has not been well-developed as well as the
other two KM practices, i.e. knowledge creation and knowledge capturing. In other words, the
current KM practices for supporting knowledge transferring need to be improved, from a
respondents’ point of view. This is consistent with the outcomes of similar research in
Chapter 5 | Case Study Analysis: SCIENCO 107
SCIENCO by which Julian (2008) has focused on studying knowledge transferring in
SCIENCO.
As shown in Table 5-15, “formal and informal events” is the most frequently mentioned KM
practice for supporting a knowledge transferring process in SCIENCOS’ PMO. This means that
participants believe that the current knowledge is mainly transferred through formal and
informal events. For instance, following is a participant’s comment to explain workshops and
seminars, as one of associated practice for formal and informal events:
“…On the other hand in our group we have seminars every afternoon on the Wednesday
and during the seminars there will be one person talking to others you know let’s say
they’ve captured…that they really are into it scientifically...”, quoted by In.Sc.4.
Table 5-15 Knowledge transferring categories and pratices (developed for this research)
KM transferring categories Associated System/Practices in SCIENCO Frequency
Communication channels • Chat rooms • Email 5
Database • Wikis 5 Discussion forums • None 0
Electronic bulletin board • Project bulletin and reports 2 Formal and informal events • Seminar and workshops 11
Intranet • None 4 Knowledge directories • None 2
Knowledge list • None 0
Training & mentoring • Induction • Mentoring • Online learning systems
8
Video and Tele Conference meeting • None 2
Yellow page • None 0
Training and mentoring is the second most frequently mentioned practice to facilitate the
knowledge transferring process. According to research findings, some new KM practices for
knowledge transferring, such as Induction, have been fairly developed to improve the project
knowledge management, as one of the participants [In.Sc.3] explains:“… Also there is an
induction where you start, everyone has to go to a two day course. But no, I mean when I
started it was very difficult because there was nothing…”. In addition, direct observation
recognised numbers of mentoring programs for juniors, which are managed by senior staff,
consistent with one of the interviewee’s comments : “… a project that I was mentioning before
we did establish and …”, quoted by In.SC.5. In other words, from participants’ point-of-view
training and mentoring practices contribute to a process of knowledge transferring in the
SCIENCO’s PMO.
Communication channels and database are the third and fourth most frequently mentioned
KM practices to support the process of knowledge transferring. According to the research
findings, email was found as an important means for transferring knowledge since it is used
108 Chapter 5 | Case Study Analysis: SCIENCO
across the organisation, as In.Sc.4 comments; “…transfer again mostly done through documents
and email…”. Also, Wiki as the one of current DBs is the most reusable data base that
contributes to transfer project knowledge across the SCIENCO (Wiewiora, et al. 2010). On the
other hand, there are some challenges in regards to current DBs as well as communication
channels. In fact, accessibility and search-ability are the significant issues in this regard, which
need to be addressed by the PMO in the next level of maturity.
Figure 5-12 Knowledge Transferring at project lifecycle (developed for this research)
On the other hand, seven out of eleven KM practices to support knowledge transferring are
yet to be appropriately developed in SCIENCO’s PMO. In fact, the limited evidences have been
recognised to support the utilisation of numbers of KM practices in SCIENCO, i.e. Video Tele
conference, Intranet, Discussion forums, yellow pages, intranet, knowledge list, and “bulletin
board”. This means that a few KM practices are there to significantly support knowledge
transferring process. In other words, SCIENCO should focus on providing an appropriate plan
to address these KM practices in order to improve the quality of knowledge management, and
eventually increase the project success rate.
In summary, knowledge transferring is the third frequent KM process from participants’
point-of-view in the SCIENCO. In fact, the research outcomes revealed that respondents believe
the four following KM practices: formal and informal events; communication channels;
database; and training and mentoring, contribute to knowledge transferring in the SCIENCO’s
PMO, while the other associated practices, such as yellow pages and knowledge list, are yet to
be addressed. These findings are consistent with a similar study, undertaken by Wiewiora, et al.
(2010). According to Wiewiora, et al. (2010) the three major following practices: formal and
informal events; email; and Wiki, are used in SCIENCO for supporting knowledge transferring,
however, some factors such as lack of trust and appropriate culture make numbers of challenges
for transferring project knowledge. In fact, the lack of culture and trust in the project
0
1
2
3
4
5
6
Initiation Planning Execution andMonitoring
Closing
Communication channels
Database
Discussion forums
Electronic bulletin board
Formal and informal events
Intranet
Knowledge directories
Knowledge list
Training& mentoring
Video and Tele Conference meeting
Yellow page
Chapter 5 | Case Study Analysis: SCIENCO 109
environment could be improved through the following maturity models (Kerzner 2005; Project
Management Institute 2008b). In other words, SCIENCO’s PMO could address some of the
existing issues of knowledge transferring in the next level of maturity.
Knowledge Reusing in SCIENCO’s Project Management Office 5.5.2.4
The process of knowledge reusing has been recognised as the least frequently mentioned of
the KM processes in SCIENCO. In fact, only less than three percent of comments have been
discussed as knowledge reusing, as shown in Table 5-12. According to the research framework
there are 11 KM practices to support knowledge reusing. In order to investigate these KM
practices in the SCIENCO, the similar process of coding was managed, as presented in
Table 5-16. As it could be inferred from this table, there are a few practices to support
knowledge reusing in the SCIENCO. In other words, the existing KM practices do not
significantly support the process of knowledge reusing in this case study, in which only less
than 10 quotes have been found to support project knowledge reusing.
From participants’ point-of-view, the majority of knowledge reusing practices have not been
addressed in the SCIENCO, from respondents’ point-of-view. In addition, only less than six
comments have been mentioned to support the following KM practices: formal and informal
events, database, electronic notice board, internet and lesson learnt. However, their frequencies
are not significant enough to be considered as reliable KM practices to support knowledge
reusing. This means that either interviewee does not believe that there are some practices for
reusing knowledge in place, or the current practices have not been appropriately designed for
this purpose. Both scenarios indicate that the current KM practices are yet to be developed in
order to improve the quality of knowledge reusing in the SCIENCO’s PMO. According to
PMBOK (2013) the previous or similar project’s knowledge should be used at initiation,
planning, execution and monitoring phases, however, the research outcomes explored that there
are limited practices to facilitate reusing of the existing knowledge SCIENCO’s PMO.
Table 5-16 Knowledge Resing in SCIENCO’s PMO (developed for this research)
KM reusing categories Associated System/Practices at SCIENCO Frequency
Data base • Wiki 1 Data mining • None 0
Document Management System • After action review • Post project reports
0
Electronic notice board • None 1
Expert systems • None 0
Formal or informal meetings • None 2
Intranet • None 1
Knowledge detection tools • None 0
Knowledge map • None 0
Lesson learnt • None 1
Yellow page • None 0
110 Chapter 5 | Case Study Analysis: SCIENCO
Furthermore, the next level of analysis focuses on knowledge reusing at project life cycle. As
depicted at Figure 5-13, knowledge reusing is inadequately used at three project life cycle
except closing phase. This is consistent with the research framework, as it has been assumed
that only knowledge capturing should be employed at closing phase. In addition, the lack of
knowledge reusing practices is quite obvious in Figure 5-13.
Figure 5-13 Knowledge reusing in SCIENCO’s PMO (developed for this research)
In summary, knowledge reusing is the least used KM process in the SCIENCO, from
respondents’ point of view. As the research findings revealed, there are a few comments in this
regard, which means that knowledge reusing is not satisfactory from participants’ perspective.
In other words, knowledge reusing is yet to be addressed in the SCIENCO’s PMO. According to
Love, et al. (2003) lack of knowledge reusing practices causes the “rework”, which has been
mentioned as one of the significant challenges for projects in Australian companies. Therefore,
this knowledge process should be addressed, as it impacts on improving quality of project
outcomes. On the other hand, according to the research framework, knowledge reusing is
dependent on quality of knowledge capturing and transferring (Owen and Burstein 2005).
Consequently, if PMO focuses on improving knowledge capturing and transferring, then it will
impact on quality of the knowledge reusing process. This means that PMO as first level of
maturity SCIENCO should focus on improving three KM processes, i.e. knowledge capturing,
creating and transferring, however, the development of knowledge reusing should be considered
for achieving the next level of maturity.
Summary 5.5.2.5
In conclusion, the first research question (RQ1- How are KM practices and processes
employed in the PMOs?) and its sub-questions have been discussed in this section. In order to
answer the third sub-question (RQ 1.3 What kinds of KM practices are utilised in each maturity
level of PMO?), it was realised that more than 50 percent of the coded comments support
0
1
Initiation Planning Execution andMonitoring
Closing
Data base
Data mining
Document Management System
Electronic notice board
Expert systems
Formal or informal meetings
Intranet
Knowledge detection tools
Knowledge map
Lesson learnt
Yellow page
Chapter 5 | Case Study Analysis: SCIENCO 111
knowledge capturing, more than 30 percent knowledge creation, less than 13 percent knowledge
transferring, and less than 3 percent knowledge reusing process. This means that knowledge
capturing and creation are significantly supported by the research findings while knowledge
transferring and reusing are not as robust as other two KM processes.
Also, according to the research framework, it has been assumed that only knowledge
capturing should be employed at closing phase. To examine this assumption, numbers of
techniques were employed and, eventually, the research findings confirm that this assumption is
valid in the SCIENCO’s PMO. In addition, the research analysis explored that the majority of
KM activities are undertaken at Execution and Planning phase, while numbers of KM practices
in are at initiation and closing are significantly two other phases. This finding is in line with PM
literature, since PMBOK explicitly addresses numbers of PM processes to support KM at
planning and execution phase (Project Management Institute 2013).
Based on the case study findings, some propositions could be made to address the KM at
first at the first level of maturity: 1) Knowledge capturing and creation are the most important
processes to be improved at the first level of maturity. This means that PMO at this level should
firstly focus on improving current practices for capturing knowledge and then creation, 2)
Knowledge transferring has the third priority but the existence of some practices to support the
basics is necessary, 3) Knowledge reusing is the least important KM process at this level, and it
is dependent on quality of the knowledge capturing and transferring process. This means the
quality improvement of knowledge capturing and transferring directly impacts on quality of
knowledge reusing process.
The importance of knowledge processes in SCIENCO 5.5.2.6
In order to answer the second research question (RQ2-How do KM practices contribute to
improve maturity level of the PMO) a survey–questionnaire was distributed among participants
and seven of them were returned. In this survey, SCIENCO’ participants were asked to rank the
importance of four KM processes: Creation; Capturing; Transferring and Reusing at project
life cycle, i.e. Initiation; Planning; Execution & monitoring; and Closing. After collecting the
respondents’ answers, MS Excel was used to analyse the collected data. As discussed earlier,
the AHP technique is a suitable and accurate method for ranking the priority of competing
phenomena (Lindner and Wald 2011; Stam and Silva 1997), therefore, this technique was used
to rank KM processes in SCIENCO’s PMO.
According to the research findings, at the initiation phase respondents believe that
knowledge capturing and then transferring are the most important processes, while knowledge
reusing is not as important as other KM processes. The current PM standards advise that two
major PM processes: developing project charter; and identifying project stakeholders, should be
employed at the initiation phase (Kamara, et al. 2003; Project Management Institute 2013; Tan,
112 Chapter 5 | Case Study Analysis: SCIENCO
et al. 2007). As could be inferred, these two mentioned processes contribute to create required
knowledge for the next phase, i.e. planning, therefore the created knowledge needs to be
captured and transferred. In addition, according to the existing PM methodologies, the
utilisation of knowledge of similar projects plays a significant role at initiation phase.
However, participants rank knowledge reusing as the last important KM process, as shown at
Figure 5-14. As discussed in the previous section, knowledge reusing has limited numbers of
KM practices in SCIENCO. Also, the level of PMO’s maturity is one which means that
SCIENCO’s PMO is at its initial steps of development. Therefore, it could be justified that the
importance of knowledge reusing in the initiation phase has not be appropriately realised. This
means that the current research findings support previous evidence and clarify that knowledge
reusing is the last important KM process, when the level of maturity at PMO is one. So it could
be concluded that despite the importance of the knowledge reusing planning and initiation
phase, a PMO with first level of maturity should focus on other KM processes.
According to PMBOK, at the planning phase knowledge creation is the most important KM
process (Reich and Wee 2006). This research finding is consistent with the mentioned theory, in
which participants believe that knowledge creation has the first priority at planning phase, as
depicted at Figure 5-14. Also, they asserted that knowledge reusing is the second important KM
process at the planning phase. As discussed earlier, the interview analysis revealed that
knowledge reusing has the lowest KM practices in the SCIENCO, especially at planning phase.
This means that the importance of knowledge reusing at the planning phase has been realised by
participants, however, the current practices do not appropriately support the knowledge reusing
process.
Initiation Phase
Planning Phase
0
1
2
3
4
CapturingCreatingTransferringReusing
0
1
2
3
4
Chapter 5 | Case Study Analysis: SCIENCO 113
Execution and Monitoring phase
Closing Phase
Figure 5-14 The importance of KM processes in SCIENCO (developed for this research)
According to PM methodologies and the research framework, all of the KM processes
should be properly employed at the execution and monitoring phase (Kerzner 2013; Project
Management Institute 2013). The research findings explored that respondents have indicated
knowledge creation as the most important KM process, and knowledge capturing as the second
most important , while knowledge reusing has the lowest importance at this phase.
According to Reich and Wee (2006), at the execution and monitoring phase, the majority of
KM practices should managed the process knowledge capturing and transferring, so the
knowledge creation and reusing should have the next priorities, however, the research findings
do not support the above mentioned assumption. As explained earlier, SCIENCO is a research
organisation so the nature of its activities is different from other industries such as construction
or mining. In other words, SCIENCO undertakes project to create and deliver knowledge or
knowledge-driven deliverables, while a construction company conducts a project to deliver
products such as buildings or bridges. Therefore, knowledge creation is the most important
activities at execution phase for research projects in SCIENCO, while knowledge capturing and
transferring are the most important KM processes in other types of project bases organisations.
As discussed earlier, according to the research framework, knowledge capturing should be
the only KM process to be used at closing phase (Owen and Burstein 2005). This means that
knowledge capturing should be the most important KM process during the closing phase of a
project. As Figure 5-14 depicts, knowledge capturing has been ranked by SCIENCO’s
employee, as the most important KM process at closing phase, which is line with the research
assumption. This means that both interview findings and survey consistently confirm the
importance of the knowledge capturing process at closing phase.
0
1
2
3
4
0
1
2
3
4
114 Chapter 5 | Case Study Analysis: SCIENCO
Figure 5-15 The general ranking of KM processes in SCIENCO (developed for this research)
At the next level of analysis, the importance of KM processes has been analysed through
considering the project lifecycle. In other words, it was aimed at determining the general
ranking of KM process, regardless of the project life cycle. To do so, the AHP method was
employed through assigning appropriate weight to each project phase. This weighted model
enables a researcher to analyse the overall rank of the KM process regardless of various phases
(Lindner and Wald 2011). The research findings explored the following ranking of KM
processes: 1) Capturing, 2) Creation, 3) Transferring, and 4) Reusing, which are depicted in
Figure 5-15.
According to the research findings, in general, knowledge capturing is the most important
KM process in SCIENCO from participants’ points-of-view. This means that SCIENCO’s
employees believe that, in the current situation, the first priority is to develop a KM system to
support knowledge capturing, and then creation. In addition, knowledge transferring and reusing
have the third and fourth level of importance. This means that SCIENCO’s employees have
realised the importance of these two KM processes, however, their first priority is to focus on
knowledge capturing and creation process. According to the literature and the research
framework, a robust knowledge capturing system provides a reliable ground for other KM
processes, specifically KM transferring and reusing (Arora, et al. 2010; Owen, et al. 2004).
Therefore, it should be reminded that this ranking has been obtained through conducting the
survey, therefore, for validation purposes, it needs to be compared to previous findings.
In summary, the research findings from the survey, interview analysis, documents analysis,
and observation have consistently agreed on the importance of knowledge capturing and
creation processes as the first priority from participants’ points of-view, while knowledge
transferring and reusing have not been found to be as important as the other two KM processes.
So it could be concluded that current KM practices mainly support knowledge management
processes in the following order: Capturing, Creating, Transferring and Reusing. In addition,
by considering the maturity level of SCIENCO’s PMO, it could be summarised that at the first
Capturing
Creating
Transferring
Reusing
0
1
2
3
4
Capturing
Creating
Transferring
Reusing
Chapter 5 | Case Study Analysis: SCIENCO 115
level of maturity PMO should focus on developing appropriate KM practices for facilitating
project knowledge capturing and creation, however, basic practices for knowledge transferring
and reusing will contribute to the equality of project knowledge management. At this section,
the first sub question of the second research (RQ2-How do KM practices contribute to improve
maturity level of the PMO) was answered. The next section aims to discuss the remaining part
of the second question.
DISCUSSION AND IMPLICATIONS 5.6
In the previous sections, the first question, and initial part of the second research question
have been discussed. At first, the existing challenges of project KM in SCIENCO have been
explored at the early sections of this chapter, then the importance of the four KM processes have
been analysed through using both interview, and questionnaire methods. As discussed, the
research outcomes from both mentioned methods are consistent, which contributes to the quality
of research findings (Yin 2009). In this section, another level of research analysis will be
discussed to explore the potential relation between the recognised challenges and four KM
processes as well as their associated sub-processes.
Knowledge capturing’s sub processes and practices in SCIENCO 5.6.1
As discussed earlier, the initial analysis has shown that most of challenges are related to
knowledge capturing. However, according to the research findings, knowledge capturing not
only has been ranked as the most important KM process, but also most of the current KM
practices in the SCIENCO facilitate the knowledge capturing process. In order to examine this
phenomenon, further analysis was undertaken through employing the research framework.
According to the research framework, knowledge capturing has been classified into four sub-
processes: Identification, Storing, Classification, and Selection, as shown at Table 5-17 (Lytras
and Pouloudi 2003; Nissen, et al. 2000). As discussed earlier, five KM challenges have been
recognised in SCIENCO’s PMO: 1) Difficulties of searching and detecting required knowledge,
2) Issue of locating and accessing right information and/or right expert, 3) Lack of KM practices
and processes during project life cycle, 4) Lack of appropriate systems to support project KM,
and 5) Issue of appropriate access to the existing systems.
The collected data was entered to Nvivo as well as the research framework, and then
numbers of Nvivo’s functions such as queries and relationship were employed to analysis the
relation between challenges and knowledge capturing sub-processes. The analysis outcomes
revealed that “knowledge storing” is the most satisfactory process among other knowledge
capturing sub-processes, in which its related KM practices are appropriately used in the
SCIENCO, as depicted at Table 5-17. In addition, the only challenge against the knowledge
storing process is the issue of access to the associated applications. This means that knowledge
116 Chapter 5 | Case Study Analysis: SCIENCO
storing is the strongest KM sub-process to support knowledge capturing. Similar analysis was
managed for the other three sub-processes and their results have been presented in Table 5-17.
Table 5-17 Knowledge capturing sub-processes in SCIENCO (developed for this research)
K. Capturing Sub
Processes
Practices for Knowledge Capturing
Associated Challenges Current Status
Knowledge Identification
• Expert locator • Formal and informal
event
• Knowledge detection tools • Knowledge repositories 1, 3 and 5
A few practices in place, however, it is yet to be developed
Knowledge Storing
• Data base • Formal and informal
event
• Document Management System (DMS) 5
Most of the current system support this
process
Knowledge Classification
• DMS • Frequently ask
questions (FAQ) • Intranet
• File management system • Management information
system (MIS) 4,5
After knowledge storing this process
has the most KM practices to be
supported
Knowledge Selection
• Knowledge inquiry system (KIS)
• Data base • Frequently ask questions
(FAQ) 1,4,5
A few practices in place, however, it is yet to be developed
The knowledge classification process has been fairly developed in SCIENCO, and the
research findings confirm that some of the associated KM practices to knowledge classification,
such as MIS and DMS, are used in this case, but some practices such as frequently asked
question (FAQ) are MIS are yet to be developed to improve knowledge classification, and
ultimately knowledge capturing. In addition, from the respondent point-of-view, two of five
recognised issues, i.e. 4 and 5, impact on the quality of knowledge classification, as depicted in
Table 5-17. This means that knowledge classification needs to be improved, since some of its
associated practices are yet to be addressed.
Knowledge selection is another sub-process of knowledge creation with three practices, as
shown in Table 5-17. According to the research findings only the database has been addressed
to support knowledge selection, while KIS and FAQ are yet to be improved in SCIENCO. In
addition, further investigation through using revealed that three recognised challenges are
directly related to lack of knowledge selection practices, i.e. 1, 4, and 5. This means that the
current practices do not appropriately support the knowledge selection process and it needs to
be improved accordingly.
According to the research framework there are four KM practices to facilitate knowledge
identification: Expert locator, Knowledge detection tools, Knowledge repositories, Formal and
Informal event. The research findings explored that except for formal and informal event, the
other mentioned practices are yet to be addressed in SCIENCO. In addition, three out of five
recognised challenges are directly related to lack of practices for supporting knowledge
identification. This means that knowledge identification faces three mentioned challenges and
they are yet to be addressed in the SCIENCO.
Chapter 5 | Case Study Analysis: SCIENCO 117
In summary, knowledge storing and classification have been fairly addressed in SCIENCO,
while knowledge selection and identification are yet to be appropriately addressed in this case.
This means that knowledge selection and identification are supported with a few practices, but
there are numbers of KM practices to support knowledge storing and classification. However,
all four mentioned sub-processes are faced with numbers of challenges, as shown in Table 5-17.
This means that knowledge capturing has been developed in some aspect but it still needs to be
improved and there are some issues related to the knowledge capturing process. In other words,
despite the fact that the majority of current KM practices support the knowledge capturing
process, they have not addressed all the current KM challenges in SCIENCO. The research
findings explored that SCIENCO should focus on improving knowledge identification and
selection in order to both develop knowledge capturing and address the current KM issues.
According to the research framework, this shall contribute to improve the quality of knowledge
transferring and knowledge capturing, and ultimately the level of PMO maturity.
Knowledge creation’s sub processes and practices in SCIENCO 5.6.2
As discussed earlier, knowledge creation is the second important KM process in
SCIENCO’S PMO, and also has the most KM practices after knowledge capturing. Knowledge
creation is part of daily activity in SCIENCO, as a research organisation. According to Nonaka
and Takeuchi (1995) knowledge is created through four processes: Socialisation,
Externalisation; Combination; and Internalisation which is called SECI. The SECI model was
adopted in the research framework by which knowledge creation has been classified to four KM
sub processes and their associated KM practices, as presented in Table 5-18.
According to the research framework, Socialisation is the process of creating tacit
knowledge through various types of communicating (Nonaka & Teece, 2001) in which it is
facilitated through any type of formal and informal events, as shown in Table 5-18. Hoegl and
Schulze (2005) discuss that informal events are the best practices for supporting socialisation by
which tacit knowledge is discussed and sometimes transferred among individuals. As discussed
earlier, formal and informal events are the most mentioned KM practice to support knowledge
creation practices, as illustrated in Table 5-14. This means that socialisation is appropriately
supported in SCIENCO through a number of practices such as workshop & seminar, community
of practice, and formal and informal events.
Table 5-18 Knowledge creation sub procesess in SCIENCO (developed for this research) K. Creation
Sub Processes Practices for
Knowledge Creation Current Situation
Socialisation • Formal and informal event
• Workshops & seminar • Community of practices
Most of them have been put in place and utilised
Externalisation
• Workshops & seminar
• Deductive & Inductive thinking
• Experts system • Experience Report • Community of practices
Most of them have been put in place and utilised but some of them such as expert system should be
118 Chapter 5 | Case Study Analysis: SCIENCO
improved
Combination • Community of
practices • Best Practice Cases
• Knowledge Broker • Data mining • Documentation search
Except the community of practices, other are yet to
be addressed
Internalisation • Research services • Simulation
• Experimentation Most of them are utilised
The Externalisation is the processes of transforming tacit to explicit knowledge (Nonaka and
Teece 2001). According to the research framework there are numbers of practices to facilitate
Externalisation such as community of practice and expert systems. The research findings
revealed that most of the mentioned KM practices are used to some extent, however, some of
them are yet to be improved. For instance SCIENCO’s employees participate in numbers of
seminars and workshops, but they believe that a community of practice is yet to be improved
upon in SCIENCO. Also, they mentioned that the current expert system faces some issues as
one of participants explains [In.Sc.3]“…most of our researchers are protective about their
knowledge ...”. In fact, externalisation has been fairly developed in SCIENCO, however, it
needs to be improved to address some of the mentioned issues.
The process of transforming the explicit knowledge to more complicated explicit knowledge
is called Combination (Nonaka and Teece 2001), which is supported through numbers of
practices as shown in Table 5-18. According to the research findings, respondents believe that
community of practice is the only KM practice, among other combination practices, which is
used in SCIENCO to support a combination process. This means that there are four KM
practices to facilitate combination which are yet to be addressed in SCIENCO: knowledge
Broker, Data mining, Documentation search, and Best Practice Cases. In other words, the
majority of KM practices for Combination process need to be improved in SCIENCO’s PMO.
According to Nonaka (1994) Internalisation is another way of creating knowledge through
developing new tacit knowledge from existing explicit knowledge. According to the research
framework there are three KM practices to support Interrelation: research services, simulation,
and experimentation, as depicted in Table 5-18. The research findings explored that from
respondents’ perspectives, all of the mentioned practices are used in SCIENCO. In other words,
SCIENCO as a research organisation has provided adequate tools for knowledge creation
through Internalisation process.
Tacit Knowledge TO Explicit Knowledge
Tacit Knowledge
From
Socialization (has been addressed in
SCIENCO)
Externalization (has been addressed in
SCIENCO)
Explicit Knowledge
Internalization (has been addressed in
SCIENCO)
Combination (yet to be properly
addressed)
Figure 5-16 The SECI Model at SCIENCO (Nonaka and Teece 2001)
Chapter 5 | Case Study Analysis: SCIENCO 119
In summary, knowledge creation has been significantly addressed in SCIENCO, however,
there are some issues that are yet to be addressed. As discussed, three out of four knowledge
creation sub-processes have been addressed, but the Combination sub-process is faced with lack
of KM practices such as data mining and documentation search. According to Nonaka (2001;
2011) the SECI model follows a spiral method in which all four sub-processes should be
interconnected as illustrated at Figure 5-16. This means that the process of knowledge creation
is fully supported when all four sub-processes are being appropriately utilised. As shown at
Figure 5-16, three out of four knowledge creation wings, Socialisation, Externalisation, and
Internalisation, have been developed to some extent, but Combination needs to be addressed
accordingly. In other words, the SECI model does not completely work in the SCIENCO’S
PMO and it needs to be improved through addressing the mentioned issue.
Knowledge transferring’s sub processes and practices in SCIENCO 5.6.3
According to the research framework there are two sub-processes for knowledge
transferring: Distribution & Forwarding; and Sharing, as depicted at Table 5-19 (Lytras and
Pouloudi 2003; Newell, et al. 2006; Nissen, et al. 2000). The communication channels (Email,
chat), and intranet are an example of “knowledge distribution”, and, training, discussion forums
and mentoring are instances of “knowledge sharing”. In fact, distribution process technologies
are more influential, while for knowledge sharing procedures, people play an influential role
(Hurt and Thomas 2009; Nonaka and Takeuchi 2011; Wiewiora, et al. 2010). As shown in
Table 5-15, the research findings revealed that both sub-processes are employed, to some
extent, during project lifecycle for knowledge transferring purposes, however, they need to be
improved since some of their associated practices have not been appropriately developed. In
other words, it was explored that all three out of four practices for knowledge sharing (formal
and informal events, training, and mentoring) are used in SCIENCO. In addition, some of the
KM practices for supporting knowledge distribution, such as knowledge list and yellow pages,
have not been mentioned by SCIENCO’s participants. This means that from the respondents’
point of view, both knowledge sharing and distribution needs to be improved in SCIENCO.
As discussed earlier, a similar study was conducted by Wiewiora (2011) to investigate
knowledge transferring in SCIENCO. In that research, numbers of factors such as “trust” and
“culture” have been discussed to investigate the challenges of knowledge transferring in
SCIENCO (Wiewiora, et al. 2009a). According to Wiewiora (2011) lack of “trust”, and
appropriate culture, impacts on transferring knowledge among SCIENCO’s employees. This
means that SCIENCO should address appropriate practices to improve both trust and
organisational culture for motivating employees in order to share their knowledge.
Table 5-19 Knowledge transferring sub processes in SCIENCO (developed for this research) K. Transferring Sub Processes
Practices for Knowledge Transferring Current Situation
120 Chapter 5 | Case Study Analysis: SCIENCO
Knowledge Distribution and
Forwarding
• Project bulletin and reports
• Communication channels
• Knowledge list
• Video and Tele Conference meeting
• Yellow page • Intranet • Data base
Some practices need to be improved such as yellow
pages, intranet, and knowledge list
Knowledge Sharing • Discussion forums • Formal and
informal events
• Mentoring • Training
Some practices need to be improved such as mentoring
and discussion forums
In addition, according to the research framework, transferring knowledge is dependent on the
quality of knowledge capturing (Arora, et al. 2010; Owen and Burstein 2005). As discussed
earlier, SCIENCO faces a number of challenges to capture project knowledge. The research
findings revealed that the lack of appropriate systems is one of the mentioned challenges which
hinder knowledge capturing. Therefore, SCIENCO has been advised to developed new systems
to improve the quality of knowledge capture. According to the research framework some of the
KM systems, such as DMS and DBs, are used both for knowledge capturing and transferring
purposes. In other words, developing a KM capturing system directly contributes to improve
knowledge transferring.
In summary, transferring knowledge in SCIENCO’S PMO is not as strong as the other two
mentioned KM processes, i.e. capturing and creation. According to the research framework,
knowledge transferring comprises two sub-processes: distribution and sharing, in which
distribution relies more on systems and application, while human factors, such as trust and
culture, impact on knowledge sharing. The research findings revealed that SCIENCO not only
needs to improve the associated systems for knowledge distribution purposes such as DMS and
DBs, but also it is advised to develop appropriate practices such as incentives and rewards for
addressing the current issues, i.e. trust and culture. This will contribute to enhance the quality of
project knowledge management, ultimately to improve the maturity level of SCIENCO’s PMO.
Knowledge reusing sub-processes and practices in SCIENCO 5.6.4
As discussed earlier, knowledge reusing is the least important of the KM processes in
SCIENCO, from participants’ points-of-view. According to the research framework, knowledge
reusing comprises three sub-processes: Adapting, Applying, and integrating, as depicted in
Table 5-20 (Lytras and Pouloudi 2003; Nissen, et al. 2000). In addition, in the research
framework, knowledge reusing has strong coloration with knowledge capturing and transferring
(Owen and Burstein 2005). This means that robust knowledge capturing and transferring plays a
significant role, in order to implement a reliable knowledge reusing system. As mentioned
previously, less than three percent of the coded comments have discussed KM from a
knowledge reusing point-of-view. This means that participants believe that the current practices
are not strong enough to support knowledge reusing in SCIENCO’S PMO. In other words, all
three sub-process of knowledge reusing needs are yet to be improved.
Table 5-20 Knowledge reusing sub-processes in SCIENCO (developed for this research)
Chapter 5 | Case Study Analysis: SCIENCO 121
K. Reusing Sub Processes
Practices for Knowledge Reusing Comments
Knowledge Adapting
• Electronic notice board • Documents management
system (DMS) • Intranet
• Data base • Yellow page • Knowledge detection tools • Formal or informal events
Majority of the mentioned KM practices are
yet to be addressed for
knowledge reusing
purposes
Knowledge Applying • Expert systems • DMS
Knowledge Integrating • Knowledge map • Data mining
In summary, SCIENCO’s PMO with first level of maturity has developed limited practices
to support the knowledge reusing process. The research findings revealed that all three sub-
processes of knowledge reusing are yet to be addressed in SCIENCO’s PMO. According to the
research framework, knowledge reusing is improved through developing knowledge capturing
and transferring. Therefore, SCIENCO’s PMO is advised to address the recognised issues of
knowledge capturing and transferring, which ultimately contribute to improve knowledge
reusing. In other words, SCIENOC at this level of maturity is advised to prioritise KM in
accordance to the recognised importance of knowledge processes.
CONCLUSION 5.7
This chapter aims to answer the first and second research questions (RQ1. How are KM
practices and processes employed in the PMOs, and RQ2. How do KM practices contribute to
improve maturity level of the PMO), and their associated sub-questions (what are the current
challenges of the PMO from KM perspective, What types of knowledge are required at each of
following project phases, What kinds of KM practices are utilised in each maturity level of
PMO, What is the importance of knowledge processes at each phase of project, How PMO
should contribute for managing the project Knowledge). The selected case study, SCIENCO, is
a research organisation which has a PMO with first level of maturity. In order to investigate the
above mentioned questions in SCIENCO, the research framework (Chapter 3) has been
employed by following the research methodology (Chapter 4). In that section, a summary of the
research findings has been explained accordingly.
According to the research findings, SCIENCO deals with the following challenges from a
KM point-of-view: Difficulties of searching and detecting required knowledge, Issue of locating
and accessing right information and/or right expert, Lack of KM practices KM processes during
project life cycle, Issue of appropriate access to the existing systems, Lack of appropriate
systems to support project KM. This means that project knowledge management is yet to be
developed in SCIENCO, since the PMO deals with the five basic issues of KM.
The research findings revealed the following order, from participants’ points-of-view, for the
required types of knowledge: 1) Knowledge about Clients, 2) Knowledge of who knows what,
3) Project Management Knowledge, 4) Costing Knowledge, 5) Knowledge about suppliers, 6)
122 Chapter 5 | Case Study Analysis: SCIENCO
Knowledge about Procedures, 7) Technical Knowledge, 8) Legal and statutory Knowledge. This
is a clear indication for SCIENCO, or PMOs with a similar maturity level, to prioritise the
importance of their required knowledge.
Moreover, the importance of KM processes has been discussed through analysing both
interviews and survey, and consistently both revealed the following order: 1) Knowledge
Capturing 2) Knowledge Creation 3) Knowledge Transferring, and 4) Knowledge Reusing. This
means that knowledge capturing and creation are the most important KM practices, while
transferring and reusing are not as important as the other two. In addition, informal and formal
events are the most utilised KM practices, which contribute to all four KM processes. These are
valuable findings for the PMO to improve this practice, as they play a significant role for project
knowledge management.
In the last section of this chapter, i.e. 5.6, the relation between KM challenges and KM
processes, as well as sub-processes, have been discussed. These findings will contribute to
prioritise the development of KM processes, sub-processes and practices. In other words, the
research findings address appropriate KM practices and processes with regards to their
associated challenges and issues. This will assist PMOs to improve the quality of project
knowledge management, and consequently the maturity level of PMO.
In the end, the following have been summarised in SCIENCO’s PMO, with first level of
maturity:
• At the first level of maturity the awareness of KM has been raised and considered,
• The first and second priority are knowledge capturing and knowledge creation, which need to be improved through providing associated KM practices,
• Knowledge transfer has the third level of importance in which basic KM practices should be put in place,
• At this level of maturity, the current PM methodology is abstract, so it is recommended to integrate both PM and KM practices to improve the quality of project knowledge management ,
• The PMO should provide appropriate practices to assist project team members with assessing the three most important types of knowledge:
o Knowledge of project management through providing PM methodology, o Knowledge about clients through developing proper KM practices, and o Knowledge of who know what through addressing appropriate KM practices
• The PMO at this level should focus on understanding the current PM systems in order to appropriately integrate them for PM and KM purposes.
Chapter 5 | Case Study Analysis: SCIENCO 123
124 Chapter 6 | Case Study Analysis: GOVCO
Chapter 6
CASE STUDY ANALYSIS: GOVCO
INTRODUCTION 6.1
In Chapter 5, the first case study, i.e. SCIENCO, was investigated through following both
research framework (Chapter 3) and methodology (Chapter 4). In this chapter, similar
procedures will be followed to scrutinise a second case study, GOVCO, from a KM point-of-
view. In this chapter, GOVCO’s PMO will be investigated to explore project knowledge
management in a governmental organisation in order to discuss the two first research questions
(RQ1. How are KM practices and processes employed in the PMOs, and RQ2. How do KM
practices contribute to improve maturity level of the PMO?). To do so, first the organisation’s
background will be explained, followed by data collection procedures. Second, the PMO’s
maturity level will be discussed alongside the current PM systems. Third, the data analysis will
be undertaken to discuss the current status of GOVCO’s PMO from a KM perspective. And
finally, concluding remarks and the research findings will be summarised.
GOVCO’S BACKGROUND 6.2
GOVCO is an Australian state governmental department which delivers a range of housing,
building and construction services to other governmental or non-governmental agencies. It also
provides appropriate policies, advice, and consultancy services in the areas of construction,
asset management and procurement for the state government. In addition, GOVCO in the main
body that manages government projects in the fields of construction and building. In fact,
GOVCO with more than 5500 employees deals with significant numbers of small and large
projects undertaken to improve the quality of public services. To do so, a PMO has been
developed within GOVCO’s structure in order to facilitate project management, ultimately to
contribute to project success rate, as shown at Figure 6-1.
The GOVCO’s PMO is responsible for developing appropriate and practical processes and
procedures to improve the quality of project management. In addition, this PMO is not in charge
of project implementation during project implementation. This means that GOVCO’s PMO has
been designed to provide PM services, so it is not involved in a project implementation. This
type of functionality of PMO is close to the definition of PMO as a “Centre of Excellence”.
According to the current literature, the PMO is the centre of excellence in which it has limited
involvement in project implementation, except providing services for improving the quality of
project management (Kerzner, 2005; Project Management Institute, 2008b). In other words, the
Chapter 6 | Case Study Analysis: GOVCO 125
centre of excellence develops services, processes and procedures to project managers for
assisting them with providing quality outcomes. This definition is compatible with the
expectations of GOVCO’s senior managers from their PMO.
Figure 6-1 A snapshot of GOVCO’s structure (from GOVCO’s organisational chart)
The GOVCO’s PMO provides numbers of services to project managers as well as other
project stakeholders. It has developed numbers of processes and procedures to facilitate project
management within GOVCO, and also offers numbers of training courses and workshops to
project managers in order to improve the knowledge of project management within the
organisation. In this chapter, GOVCO’s PMO will be discussed to not only assess the maturity
level of PMO, but also, to investigate “how project knowledge is managed” in this case study.
To do so, the reliable data will significantly contribute to the quality of this research, so in the
next section the process of data collection has been explained, accordingly.
DATA COLLECTION PROCEDURES 6.3
Similar to the previous case study, the research methodology alongside the case study
protocol were followed to arrange the data collection in the field. In addition, the appointed
liaison person assisted with providing a schedule to conduct the research data collection. In
total, seven interviewees were selected: GOVCO’s senior manager, PMO manager and
coordinator, a program manager, two project managers, and one project team member, as shown
at Table 6-1. In some cases, interviews were conducted two times as the researcher needed more
clarification. For confidentiality purposes, interviewees’ names were replaced by a selected
code as can be seen in Table 6-1.
All interviews and the majority of data collection activities were undertaken at GOVCO’s
site, from late March 2012 to early June 2012. In addition, four days were spent to directly
observe the current PM activities in GOVCO. Also, it took three days to study the utilised
software and systems in GOVCO’s PMO. After the data collection stage, the collected
interviews were transcribed into the MS Word format in order to prepare them for uploading in
Nvivo, as the selected software for analysis purposes. In total, this process took two months, and
more than 140 pages of interviews transcriptions were provided to be used in Nvivo.
State Government
Other govermental departments GOVCO
Program management office
126 Chapter 6 | Case Study Analysis: GOVCO
Table 6-1 Interviewees’ list and schedule in GOVCO (developed for this research)
Interviewee Position 1st interview 2nd interview
In.Gd.1 GOVCO senior Manager 30/05/2012 (face to face)
08/06/2012 (face to face)
In.Gd.2 PMO manager 11/05/2012 (face to face)
24/05/2012 (face to face)
In.Gd.3 PMO Coordinator 24/05/2012 (face to face)
30/05/2012 (face to face)
In.Gd.4 Program Manager 25/05/2012 (face to face)
30/05/2012 (face to face)
In.Gd.5 Project Manager 25/05/2012 (face to face)
(30/05/2012 (face to face)
In.Gd.6 Project Manager 29/03/2012 (face to face)
07/06/2012 (face to face)
In.Gd.7 Project team member 29/03/2012 (face to face)
07/06/2012 (face to face)
THE DATA COLLECTION METHODS 6.4
According to the research methodology, three forms of data collection were employed: 1)
semi-structured interviews alongside the two types of questionnaires, one for assessing the PMO
maturity level and another for assessing the importance of KM processes, 2) direct observation,
and 3) document analysis. The first questionnaire was developed to assess the maturity level of
project management activities, and was given before the interview questions, and the second
questionnaire was asked after finishing the interview questions.
Table 6-2 Data collection methods (developed for this research)
Data Collection Method Location Facilitator Date
Interviews and Questionnaires
GOVCO building Researcher
Mentioned in Table 6-1
Documents Review GOVCO
building and QUT
Researcher and GOVCO’s liaison
person
12/05/2012 till 31/06/2012
Direct Observation GOVCO building
Researcher and GOVCO’s liaison
person
16/06/2012 to 20/06/2012
Both direct observation and document analysis have assisted the researcher, not only for
gathering complementary information from this case, but also for investigating GOVCO’s
activities from a PM as well as KM point-of-view. The data collection activities were conducted
in accordance with the case study protocol, also by getting assistance from the assigned
employee, as GOVCO’s liaison, as depicted in Table 6-2. In addition, the triangulation of data
collection methods was adopted in order to ensure the quality of gathered data (Singh, et al.
2009; Yin 2009).
THE DATA ANALYSIS 6.5
After data collection, the process of data analysis was conducted to investigate GOVCO’s
PMO from PM and KM points-of-view, and to ultimately answer the research questions. At the
Chapter 6 | Case Study Analysis: GOVCO 127
first step, the maturity level of the PMO was assessed, then PM and KM challenges were
discussed, followed by analysing the required types of knowledge during the project lifecycle.
At the end, the importance of four KM processes, Creation, Capturing, Transferring, and
Reusing were analysed, and then they have been examined against the explored KM challenges
to explore the relationship between KM process and KM issues in GOVCO’s PMO.
The maturity level of GOVCO’s Project Management Office 6.5.1
According to the research methodology, the assessment of the PMO’s maturity level is the
initial step to commencing the process of data analysis. The designed assessment model was a
questionnaire survey, which comprises 13 questions to cover the examination of nine PMBOK’s
knowledge areas during the project life cycle. This assessment model is the customised form of
PM assessment method, suggested by Kerzner (2013) which has been simplified to meet the
research scope and objectives.
Table 6-3 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study)
PMBOK’s Knowledge area Maturity level Average ML
Project Scope management 1.93
2.32
Project Cost management 2.57 Project Time management 2.14
Human Resource management 1.93 Project Quality Management 2.79
Project Risk management 2.79 Project Communication management 2.00
Project Procurement management 2.29 Project Integration management 2.43
The questionnaires were distributed among numbers of employees in GOVCO, by which
participants were asked to rate each question from 0 (lowest) to 10 (highest) in which they
should choose “0-1” for poor, “2-3” for weak, and eventually “8-10” for world standard
quality. In total, 12 questionnaires were distributed among respondents and, eventually, eight of
them were returned and all the answers entered in MS Excel 2010. According to the research
framework and (Kerzner (2005); Kerzner (2013)), the level of maturity for a PMO could be any
number from 1 to 5, in which number 1 represents the lowest level of maturity, while number 5
claims the highest maturity level (ML). In other words, a maturity level is defined at five levels
in which the lowest maturity level, i.e. ML=1, indicates that the PMO is in its initial steps to
improve the quality of project management, in contrast the highest maturity level, i.e. ML=5,
means that the PMO has developed and customised a robust and advanced project management
system to support organisational projects (Project Management Institute 2008b).
At the first step, the maturity level (ML) for nine knowledge areas of PMBOK was
investigated, as depicted in Table 6-3 and Figure 6-2. The research findings revealed that the
average maturity level for GOVCO’s PMO is 2.32 out of 5. According to the research
framework and the current literature, ML=2.32 is classified as the second level of maturity
128 Chapter 6 | Case Study Analysis: GOVCO
(Kerzner 2005; Project Management Institute 2008b). In addition, as Table 6-3 illustrates the
cost, risk and quality management are ranked at top levels in GOVCO, while HR,
communication, and scope management are yet to be developed in this case. In fact, participants
believe that PM practices have been fairly developed to support project cost, quality, and risk
management, while project scope, human resource, and communication are yet to be addressed
through developing appropriate practices. These findings have been confirmed during document
analysis, when numbers of processes were found to facilitate project risk and quality
management, while a few forms have been recognised to support cost, and communications.
Figure 6-2 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study)
In the next step, maturity level was analysed from a project lifecycle point-of-view, as the
result depicted at Table 6-4 and Figure 6-3. According to the research findings the average
maturity level is 2.39, which should be ranked at second level of maturity (Kerzner 2005).
Table 6-4 The ML of GOVCO’ PMO: project lifecycle (developed for this research)
Project Phases Maturity level (ML) Average ML
Initiation 2.50
2.39 Planning 2.79
Execution and monitoring 2.00 Closing 2.29
From a process point-of-view, planning and initiation are more satisfactory in comparison to
execution and closing. This means that from participants’ perspectives, the current PM practices
are fairly developed to facilitate initiation and planning phases, while a few practices support
execution and closing phases. Consistently, the interview analysis revealed that participants
have mentioned the lack of PM practices at execution phase, as In.Gd.2 explains “…I think we
actually do the least amount at execution. Because of what we do about the only thing that
would support them would be the training capability you know when they’re executing it…”. As
discussed earlier, GOVCO’s PMO has been designed to be the centre of excellence, therefore it
1.93 2.57
2.14
1.93
2.79 2.79
2.00
2.29
2.43
Project Scope
Project Cost
Project Time
HR management
Project QualityProject Risk
ProjectCommunication
ProjectProcurement
Project Integration
ML OL
Chapter 6 | Case Study Analysis: GOVCO 129
should have less involvement in the execution phase. In other words, the GOVCO’s PMO
should significantly contribute to project initiation, planning, and closing, however, the basic
PM practices to support execution phase, are helpful.
Figure 6-3 The ML of GOVCO’ PMO: project lifecycle (developed for this research)
The research findings revealed that maturity level assessment from both PMBOK’s
knowledge areas, and project lifecycle, have consistently determined that GOVCO’s PMO has
the second level of maturity. In addition, an internal assessment had been previously done by
GOVCO, and consistently they came up with a similar maturity level, as PMO’s manager
[In.Gd.2] explains “… we are probably 2 on a 5 scale the standard…”. In fact, the outcomes
from both methods of maturity assessment are consistent with the internal maturity assessment,
which means that the various methods of data collection have reliable as well as quality results
in this regard.
According to (Kerzner (2005); Kerzner (2013)) and the research framework, the second level
of maturity is called “common process”, which means that there some numbers of common
processes in place to facilitate project management. In addition, at this level of maturity the
benefits of project management have been recognised by organisational employees as well as
senior managers. Also, there is at least one project management framework in place to be
employed by project stakeholders. In other words, the PMO has passed the first level of
maturity, i.e. common language, where the existence of basic PM practices was essential. This
means that the PMO has been developed to address the basic requirements for the first level of
maturity. As discussed in the research framework (Chapter 3) the main characteristics of the
second level of maturity are (Kerzner 2005; Kerzner 2013):
• In the second level of maturity benefits of Project management were recognised and
emphasised,
2.50
2.79
2.00
2.29 0.00
1.00
2.00
3.00
4.00
5.00Initiation
Planning
Execution&monitoring
Closing
ML OL
130 Chapter 6 | Case Study Analysis: GOVCO
• The need for processes and methodologies were recognised and supported at all
levels of organisation,
• The importance of cost, scope and quality were acknowledged by senior managers,
and projects stakeholders, and
• Project management training courses have become an important prerequisite for all
levels of project stakeholders, specifically project managers.
Table 6-5 Participants’ quotes in regards to GOVCO’s PMO matuirty (developed for this research) Subject Associated participants’ comments
PM Training
In.Gd.3 : “…We also offer training to new people once they’ve joined Project Services if they haven’t used our programs and software before we run the training for that…”
In.Gd.2: “…We’ve got someone who actually just works on training and all they do is actually coordinate training for project managers in the organisation…”
In.Gd.3:”…We do offer training to the people who haven’t done Prince 2 training or haven’t done SAP training and we run that to help them deliver their projects and things…”
PM Methodology
In.Gd.2:”… We have developed our methodology. We actually have taken a number of the international standards. So we’ve looked at PMBOK, we’ve looked at the ICB from IPMA,
there’s a Japanese one which goes from project to program management, Prince 2…” In.Gd.4:”…they [PMO] were basing it on PMBOK but I think more recently they’re moving
towards Prince 2...” In.Gd.5:”…I think well the real push for Prince 2 at the moment in learning the methodology. I
don’t think it’s all being applied or it’s being applied but in different terminology. But I think it’s more of a patchwork of some of PMBOK, some of Prince 2…”
Since it was revealed that GOVCO’s PMO has the second level of maturity, therefore the
above mentioned characteristics should be consistent with the current activities of PMO from a
PM point-of-view. In order to investigate the consistency of the above mentioned criteria, the
collected data, such as interview and direct observation, were utilised. The research findings
from interview analysis have confirmed the majority of mentioned criteria, and Table 6-5 covers
two subjects: PM methodology and PM training. This means that participants’ thoughts about
the current situation of PMO are consistent with the PMO at a second level of maturity. In other
words, both interview analysis and PMO assessment confirm the same level of maturity for
GOVCO’s PMO.
As shown in Table 6-5, participants have mentioned that PMO provides PM training courses
project stakeholders. This also has been confirmed during the direct observation stage, as this
researcher participated in one of the PM courses. In addition, respondents believe that there is a
PM methodology, as illustrated in Table 6-5. After conducting the document analysis stage, a
PM framework has been recognised in the GOVCO’s PMO, which will be the subject of next
section. In fact, these findings show that the obtained information from various data collected
methods is consistent and this contributes to the research quality.
The GOVCO’s project management methodology 6.5.1.1
As discussed earlier at the second level of maturity, at least one PM methodology should be
in place to be used by project stakeholders (Kerzner 2005). A PM framework was found in the
GOVCO’s PMO, during the documents analysis stage. In addition, the interview analysis
Chapter 6 | Case Study Analysis: GOVCO 131
revealed that all participants were aware of the existence of a methodology, and the majority of
them have been trained in this regard. According to the PMO manager, the existing PM standard
has been customised through combining of PMBOK and PRINCE2: “…We actually have taken
a number of the international standards. So we’ve looked at PMBOK, we’ve looked at the ICB
from IPMA, there’s a Japanese one which goes from project to program management, Prince 2
but it’s amalgamation of both…” quoted by In.Gd.2 .
The existing PM standard has been developed through customising both PMBOK and
PRINCE2 [In.Gd.2]. According to the research findings, participants believe that the current
PM methodology significantly contributes to PM, through addressing the required processes,
procedures and actions that need to be done during project lifecycle. In addition, the existing
PM standard has been reasonably collaborated with the current processes and forms. Also, an
internal developed tool for project managers, i.e. The PMMate, has been integrated with PM
methodology to improve the quality of project outcomes in GOVCO.
On the other hand, the research findings revealed the following in regard to the current PM
methodology: 1) some of the participants have not clearly realised the importance of it in their
daily work; 2) this framework has not been completely endorsed by senior managers, so project
managers are not obliged to follow it, during project lifecycle; 3) Some of the current systems
and tools, such as SAP and risk management tools, have not been integrated with the PM
methodology. These issues show that GOVCO’s PMO should develop the current PM
methodology to address the existing concerns in this regards.
In summary, despite the usefulness of the existence of PM methodology, there are some
issues that are yet to be addressed, such as integrating with the current systems such as PMMate
and SAP. Also, there are some processes in place, for instance risk management, which have not
completely collaborated the existing PM standard. However, the current PM methodology is
consistent with the minimum requirements for the second level of maturity, therefore GOVCO’s
PMO could improve the level maturity through addressing above mentioned issues. In other
words, to achieve the next level of maturity a unique PM framework is required, by which the
majority of current systems have been collaborated (Kerzner 2005).
GOVCO’s Project Management Office as a Centre of Excellence 6.5.1.2
According to GOVCO’s senior managers, the PMO has been designed to be centre of
excellence [In.Gd.1]. A centre of excellence refers to an entity that provides support for a
focused area, without being involved in the undertaken activities (Raymond, et al. 2010).
Therefore, a PMO as a centre of excellence should support projects through providing PM
services and tools such as process, applications, research, and best practices in order to improve
the quality of project management (Dai and Wells 2004). This means that when a PMO is
132 Chapter 6 | Case Study Analysis: GOVCO
developed as a centre of excellence, then it should not have any involvement in project
implementation.
The research findings explored that GOVCO’s PMO has been developed to help project
managers as well as team members, through providing various services such as, forms and
templates, training and workshop, monitoring and control, and sending alerts and reminders. In
other words, GOVCO’s PMO does not undertake any activities in the project, specifically at
execution, but it provides services for the project from initiation to closing phase.
“…The PMO is not …and the people in the PMO are not to be considered as additional
resources for the project manager…” quoted by In.Gd.1, the GOVCO’s senior manager
From a KM point-of-view, a centre of excellence should provide practical practices to
facilitate management to project knowledge (Crawford 2002; Walker and Christenson 2005).
According to the research framework (Chapter 3) the following criteria should be found at the
second level of maturity: 1) awareness of KM at this level should be realised by the senior
manager, 2) project team members should be familiar with the basics of KM, and 3) knowledge
capturing should be improved through practical practices for documentation and a repository
system. According to both the collected data and also the conducted observations, all above
mentioned criteria have been met, so following are some quotes in this regard:
“…I guess …is in increasing the awareness of the PSO so people are happy to contact
us…”, In.Gd.5.
“… We lose this big opportunity of gathering information progressively through a
project so we got involved up the front…”, In.Gd.3.
“…but it’s those others lessons that we learn or don’t learn during the project that
we’re not capturing so well…”, In.Gd.4.
“…I think that is a gap in capturing the reason for the changes type of thing more so
than the change itself often gets captured if that makes sense…”, In.Gd.4.
In summary, the level of maturity for GOVCO’s PMO is two, which means that there should
a PM methodology, some PM processes and also a training course in place (Kerzner 2005;
Kerzner 2013). These conditions have been confirmed through analysing PMO documents,
interview data and direct observation, in which all data collection methods confirmed the
required characteristics for a second level of maturity. In other words, the provided data from
different methods and sources, triangulation, are consistent, by which they improve the quality
research outcomes. In addition, it was revealed that GOVCO’s PMO has been designed as a
centre of excellence, which means that it does not intervene in project implementation. Since
the existing PMO’s systems significantly contribute to the quality of PM (Alavi and Leidner
2001; Davidson and Jillian 2009), they will be discussed in the next section.
Chapter 6 | Case Study Analysis: GOVCO 133
Project management systems and tools in the GOVCO 6.5.1.3
According to the research findings, GOVCO’s PMO has number of systems and tools in
place, as depicted at Table 6-6. From a process point-of-view, more than 60 forms were
recognised, which are used to facilitate PM activities alongside the current PM methodology.
Also, there are numbers of tools such as MS project, MS excel, and email-based helpdesk,
which are used for facilitating PM. As shown at Table 6-6, there are five main tools: Internet;
SAP; PMMate; Risk Management System; and AConnect, in GOVCO, which significantly
contribute to management of GOVCO’s projects.
Table 6-6 The current system and tools in GOVCO’s PMO (developed for this research)
Application Propose of use
SAP To integrate cost and revenue of projects across GOVCO
PMMate It’s a customised processes program to maintain quality of project management activities
Intranet To capture and transfer project information Risk Management system It’s an excel base system to create estimation for project risk
AConnect It’s a web based software for contract administration
SAP is a total system which deals with project facts and figures, such as cost and revenue.
This software is a total solution for organisations to capture and transfer the costing knowledge
of projects, however, it is not a complete application for project management purposes
(Crawford 2012). This means that SAP has not been designed managing organisational projects,
but the integration of SAP and project management software could make a reliable collaboration
for both PM and organisational KM. This could be one of the future steps for GOVCO’s PMO
to improve the quality of PM. In addition, participants have mentioned a number of SAP’s
issues which need to be addressed:
“…The problem is that we have a program in SAP in our computer system, our business
system but it’s not particularly user friendly or flexible so we all tend to use MS
Project…” quoted by In.Gd.4.
“…The programming ability of SAP is very poor. I don’t think that there’ll be any way
that they can change SAP, I don’t think the IT people can rewrite SAP to make the way it
does a Gant chart easier and more flexible and less clunky…” quoted by In.Gd.4
PMMate is another PM application that comprises numbers of processes and procedures to
assist project managers with addressing appropriate PM processes. It is also used for quality
assurance purposes by which project team members undertake suitable actions, during project
life cycles. In addition, PMMate helps project team members by automatically populating letter
and forms when it is required. According to respondents, this application is quite useful to
capture and transfer the knowledge of a project. As In.Gd.3 explains “…PMMate is basically a
134 Chapter 6 | Case Study Analysis: GOVCO
QA procedure and the templates embedded in sort of like…it automatically populates you know
letters and stuff like that …”.
Another system which is utilised during project lifecycle is the “intranet”. The internal
network has been designed to facilitate access to the required information across the
organisation. Also, it contributes to both capturing and transferring the project information. In
addition, there are some forms and templates as well as procedures which are available through
the intranet. Also, basic notice board has been developed on the intranet, which is used for
knowledge transferring.
An Ms Excel-based risk management system is used to facilitate the process of risk
management in GOVCO’s PMO. This application is currently considered as the main tool to
assess and manage the project risks, and then record all the collected information in order to use
for future projects. From one of the respondent’s point-of-view this system”… redeveloped that
whole process in Excel to enable people to go through and actually do both preliminary and
detailed risk assessments…”,[quoted by In.Gd.3]. However, it is fairly new to the department
and it needs to be trained appropriately, to be utilised by project team members.
AConnect is a web-based contract administration system in GOVCO, which is used both
internally and externally. This tool gives GOVCO’s clients and suppliers an environment in
which to access their required information. As one of the participants explains, “…it’s not an
internal thing, it’s external AConnect is a company a worldwide company that come up with a
very expensive, a good program that lots of people are using on bigger projects now…”, quoted
by In.Gd.4.
In summary, GOVCO’s PMO has numbers of systems in place to support the PM. These
systems and applications are used for various purposes and they contribute to the quality of
project management in GOVCO. In addition, more than 60 forms were recognised in GOVCO,
which are used to facilitate PM activities alongside the customised PM methodology. Also,
there are some tools such as MS project and MS excel, monkey server, and an email-based
helpdesk which are used for managing project. However, the lack of integration among the
current systems has been recognised as one of the major challenges in the GOVCO’s PMO. In
the next section, major issues of GOVCO’s PMO from a KM perspective will shed more light
on the issues in GOVCO.
Knowledge management challenges in GOVCO 6.5.1.4
As discussed in the previous chapter, to recognise the issues of PMO from a KM perspective,
interview data was used as the main source of research information. In addition the research
framework was followed, in which interviews’ transcriptions were uploaded to the Nvivo, as the
data analysis software. Then, the process of coding, both open coding and axial coding, was
managed as it is advised by similar qualitative research (Charmaz 2014; Corbin and Strauss
Chapter 6 | Case Study Analysis: GOVCO 135
2008; Wiewiora, et al. 2010). In the first stage of the open coding process, more than 85 nodes
were developed in the Nvivo. These codes or comments have directly or indirectly mentioned
the current challenges from a KM point of view. Following are some of the examples of the
coded comments:
“…The reality is that SAP is an office wide program that all our admin staff use,
all the billing and everything as well, it’s not a program that’s been designed for
project managers…”, In.Gd.4.
“…The knowledge transfer when you are changing personnel or something like
that, handing over a project or something like that …is not particularly fantastic…”,
quoted by In.Gd.4.
“…I should say that there is information on processes, on how project services
wants those processes to work, but I wouldn’t say that it’s ….easily accessible or
made easily available to new people…”, quoted by In.Gd.5.
In the next level of analysis some of the Nvivo’s functions, such as queries and
classification, were utilised to find the relationships among the current coded information.
Eventually, after running numbers of models, four categories, as the research axial codes, were
developed as the major challenges of GOVCO’s PMO. In other words, all 85 coded comments,
in regards to KM challenges, have been classified in five major categories by following research
methodology (Corbin and Strauss 2008). This means that each category, or axial code,
represents a number of associated issues of KM in the GOVCO’s PMO. In other words, the
following KM challenges of GOVCO’s PMO have been recognised through following both
“theory making” and “Grounded theory” techniques, advised by qualitative research experts as
methods to make theory from similar data (Charmaz 2014; Corbin and Strauss 2008; Eisenhardt
and Graebner 2007):
1) Lack of integration among current processes and systems
2) Issue of locating and accessing right information and/or right expert
3) Lack of KM practices and KM processes during project life cycle
4) Issue of appropriate access to the existing systems
Table 6-7 is an example of presenting how participants’ quotes were related to open codes,
and also, how axial codes were developed accordingly.
In the next step of data analysis, the importance of each challenge has been investigated to
get insightful information about their significance. According to research methodology, the
frequency of each phenomenon should be used to analyse the importance of each phenomenon.
To do so, after running numbers of matrix queries in Nvivo, the obtained data was transferred to
Ms Excel for further analysis. As shown in Figure 6-4, the research findings revealed that 44
136 Chapter 6 | Case Study Analysis: GOVCO
percent of the coded comments have indicated the “lack of KM practices and KM processes
during project life cycle” as the most frequently mentioned challenges. This means that
participants believe that the current KM practices are not enough to support their expectations
from a KM point-of-view.
For instance, the majority of participants have mentioned their issues with managing project
lessons learned as well as project review processes, as In.Gd.3 quotes “…The defect, the lessons
learned might be started earlier and updated but it wouldn’t actually be finished and emailed to
the PMO until the very end…”. This means that participants are already aware of importance of
KM practices to improve the quality of project management. In other words, the lack of KM
processes is a recognised issue, and it needs to be addressed accordingly.
Chapter 6 | Case Study Analysis: GOVCO 137
Table 6-7 Example of using Axial &Open coding in GOVCO’s PMO (developed for this study)
Axial coding Open coding Quote’s samples
Lack of integration among current processes and
systems
Project information and SAP are not synchronised “…The reality is that SAP is an office wide program that all our admin staff use, all the billing and everything as well, it’s not a program that’s been designed for project managers…”, In.Gd.4.
“…kind of just haphazardly getting four or five different things together, then seeking approval, If it was possible to design a one size fits all this is what you need to move forward that would be quite useful…”, quoted by In.Gd.3
“…I think the one thing that we’ve yet to do is actually upgrade our high level process overflow which actually says you know pictorially this is the process flow and these are all the various components in the planning that you get to do…”,
quoted by In.Gd.2.
Processed need to be Improved
Poor change management system
Current processes are not quite practical
Challenges with SAP
Issue of locating and accessing right information and/or
right expert
PMO staffs are multi-tasking “…The knowledge transfer when you are changing personnel or something like that, handing over a project or something
like that …is not particularly fantastic…”, quoted by In.Gd.4. “…We wanted some experienced project managers in there as well as other staff who could act in the…more of a support
role…”, quoted by In.Gd.1. “…I think the biggest difficulty is the staff change. Because we’ve got staff coming in and going out , you don’t get the
level of efficiency within PMO to be able to start actually like real time affecting things…”, quoted by In.Gd.2. “…If I had someone who was skilled on change management, this is what we’re going to roll out, they can actually come
up with a detailed plan and communication…”, quoted by In.Gd.2
Main issue is to get right person
Issues with transferring knowledge to new person
Staffs are changed regularly
Lack of KM practices KM
processes during project life cycle
Project reviews should be undertake properly “…if there was a way of accessing information about a similar project for a similar budget and similar contract type I would have gone and had a look at it to try and find out some information about you know what they recommend you do.
But I didn’t really get anything specific…”, quoted by In.Gd.4. “…We ask for it and it’s something that they should be doing but yes whether they actually do it and send it to us is where
we’re finding the difficulty…”, quoted by In.Gd.3. “…I think that is a gap in capturing the reason for the changes type of thing more so than the change itself often gets
captured if that makes sense…”, quoted by In.Gd.5 “…we lose this big opportunity of gathering information progressively through a project so we got involved up the front,
we get involved sort of in the planning and at the end…”, In.Gd.2.
Knowledge of previous projects is not available
Issues with capturing lesson learned
Knowledge transferring and reusing should be improved
Internal & external communications are not satisfactory Challenges with knowledge capturing practices
Issue of appropriate access to the
existing systems
Proper access to information resources is a challenge “…I should say that there is information on processes, on how project services wants those processes to work, but I wouldn’t say that it’s ….easily accessible or made easily available to new people…”, quoted by In.Gd.5.
“…I think to help out the whole closing of the whole project it would be helpful to have more information throughout. The project reviews I also think like I’ve filled them in and sent them to the PMO and I don’t know where they go type of
thing…”, quoted by In.Gd.4. “…you need to make it easy because people are busy , people are lazy so in order to try to make it easy for them to be able
to see it up front I think that would be helpful…”, quoted by In.Gd.4. “Internally we do have project reviews that are fairly new, they’ve just redone it all over the past year or so through the
PSO and you know I haven’t, none of my projects have been at the stage of finishing like in the last six months or so…”, quoted by In.Gd.2.
PMO does not offer any practical assistance throughout the project
PMO does not help to find external consultant The current data base for project reviews are not easy
accessible
Challenges of access to Intranet
Chapter 6 Case Study Analysis: GOVCO 138
Figure 6-4 The exsisting KM challenges of GOVCO’s PMO (developed for this study)
The second and third most frequently mentioned challenges, with 22 %, and 21 %, are “lack
of integration in the current systems” and “issues of access to the existing systems”. According
to Alavi and Leidner (2001) KM has three main players; people, process, and technology, in
which a KM system is the combination of processes and technology to address how people
should employ a system for KM purposes. The research findings revealed that the current
systems have been faced with issues not only from integration, but also from access points-of-
view. This means that GOVCO’s participants believe the existing systems should be developed
in order to improve their contribution to management of project knowledge. For instance, the
following are some of the participants’ concerns in this regard:
“…there’s no way of getting whatever file that those are all stored in, if you come along
on a new project I don’t think you can easily find out what someone might have said on a
particular project about lessons learnt…”, quoted but In.Gd.4.
“…so again PMO doesn’t help you to find this kind of expertise…”, quoted by In.Gd.5
According to the research framework, access to knowledge is part of the knowledge
capturing process. This means that knowledge capturing should be problematic, as there are
some issues in regards to access to the current system. However, more evidence is required to
confirm that issues of access to the current systems impact on knowledge capturing in the
GOVCO’s PMO.
The fourth concern, with 13 percent, is the lack of processes or systems to facilitate locating
and/or finding right expert or information. Since the PMO at GOVCO is a centre of excellence,
therefore, it is expected to recognise some processes or practices to facilitate finding the right
expert or information, however, the majority of respondents believe that current systems are yet
to be developed to address this issue. Followings are some of the interviewees’ comments in
this regard:
“…the main issue has been trying to get the right people into the PSO…” , quoted by
In.Gd.1
21%
44%
13%
22% Lack of integration among current processesand systems
Lack of KM practices KM processes duringproject life cycle
Issue of locating and accessing rightinformation and/or right expert
Issue of appropriate access to the existingsystems
Chapter 6 Case Study Analysis: GOVCO 139
“…I think the biggest difficulty we’ve got is the staff changed. Because we’ve got staff
coming in and going out it’s, you don’t get the level of efficiency within the PSO to be able to
start actually like real time affecting things…” quoted by In.Gd.2
According to the research framework, inappropriate access to the right person impacts on
both Knowledge Reusing and Knowledge Capturing. Therefore, it is expected to see some
inefficiency in knowledge capturing and reusing in the GOVCO’s PMO. The relation between
KM process and the recognised KM knowledge will be discussed in section 6.6.
In summary, four challenges have been explored in GOVCO’s PMO, from a KM point of
view. As discussed, the mentioned challenges were examined through employing the research
framework as well as the current literature, in order to investigate their relationship with four
KM processes. It was revealed that all KM processes have been impacted by these issues,
especially knowledge reusing. This means that there are numbers of issues that are yet to be
addressed in the GOVCO. In this section, the primary parts of the first question (RQ1- How are
KM practices and processes employed in the PMOs?) have been discussed to explore KM
issues in GOVCO. In the next section, the second part of the first research question will be
discussed to find the importance of knowledge types during the project life cycle.
The required types of knowledge at project life cycle in GOVCO 6.5.1.5
According to the research framework, there are eight types of knowledge in project
environments: Project Management Knowledge; Knowledge about Procedures; Technical
Knowledge; Knowledge about Clients; Costing Knowledge; Legal and statutory Knowledge;
Knowledge about suppliers; and Knowledge of who knows what. In this stage of data analysis,
it was aimed to understand the importance of each type of knowledge for answering another part
of the first research question. To rate the importance of each knowledge type, survey forms
were distributed among the 10 participants and, eventually, eight completed forms were
returned. In the survey, respondents were asked to rank various types of knowledge from 1, the
least, to 8, the most important ones.
After collecting data and entering these to MS Excel sheets, an Analytical Hierarchy Process
(AHP) was employed to analyse survey responses. This technique is a process that uses
hierarchical decomposition through a weighted matrix to analyse complex information in multi-
criterion decision (Ghodsypour and O'brien 1998). It is a highly recommended technique for
ranking the importance of competing factors in operational management (Lindner and Wald
2011; Stam and Silva 1997). This technique was employed and the advised processes were
followed to rank the importance of types of knowledge in GOVCO’s PMO, as shown at
Figure 6-5.
In the initiation phase, the research findings revealed that the “knowledge about client” and
“project management knowledge” are the most important types of knowledge, while “legal
140 Chapter 6 | Case Study Analysis: GOVCO
knowledge” and “knowledge about supplier” are the less important types of knowledge.
According to PMBOK (2013) client expectations and knowledge of PM are important to initiate
projects, therefore, the research findings are in line with PMBOK, as the adopted PM standard.
As depicted in Figure 6-5 and Table 6-8, the research outcomes explored that at initiation phase,
knowledge about supplier and legal knowledge are considered as important as other types of
knowledge. As defined in the current PM standard, the aim of the initiation phase is to conduct
high level activity for preparing projects (Project Management Institute 2013; Wideman 2002).
This means that the PMO’s priority should be on providing the “knowledge about client” and
“PM knowledge”, instead of preparing “knowledge about supplier” or “legal knowledge”.
Figure 6-5 Types of required knowledge in GOVCO (developed for this research)
At the planning phase, two types of knowledge have been ranked as the most important
knowledge: PM knowledge and knowledge of organisational procedures, in contrary,
knowledge about supplier and legal knowledge have been categorised as the less important
ones. Project management methodologies emphasise the importance of knowledge of PM for
planning, more than other types of knowledge, because it helps to integrate all related
information for providing a realistic and reliable project plan (Bentley 2009; Project
7
6
4
8
3
2 1
5
0
1
2
3
4
5
6
7
8Initiation 8
7
4
6
3
2
1
5
Planning
8
6 7
2
5 5
3
1
Execution 8 7
2
6
4
3
1
5
Closing
Chapter 6 Case Study Analysis: GOVCO 141
Management Institute 2013). This means that participants expect from PMO to develop various
types of training and workshops for improving the knowledge of PM among project team
members. Also, it indicates that PMO should consider developing the PM processes and
procedures in order to collaborate with the current organisational systems.
Table 6-8 Types of knowledge and their rank at GOVCO (developed for this research)
Types of Knowledge \ Project Phase
Individual Rank Total weighted Rank Initiation Planning Execution Closing Rank Percentage
Project Management Knowledge 7 8 8 8 8 19.8%
Knowledge about Procedures 6 7 6 7 7 14.7%
Technical Knowledge 4 4 7 2 5 11.8%
Knowledge about Clients 8 6 2 6 6 14.5%
Costing Knowledge 3 3 5 4 3 11.2%
Legal and statutory Knowledge 2 2 5 3 2 9.6%
Knowledge about suppliers 1 1 3 1 1 6.5%
Knowledge of who knows what 5 5 1 5 5 11.8%
At the execution phase, respondents have punctuated the importance of “PM knowledge” but
“technical knowledge” has been ranked as the second most important knowledge at this stage.
This means that technical knowledge has become an important type of knowledge at execution
phase. Need for technical knowledge is an obvious requirement at this phase and it is mandatory
to execute all project activities (Project Management Institute 2013; Reich and Wee 2006). This
analysis confirms the consistency of participants’ answers with both common sense and project
management practices. In addition, “knowledge of who knows what” and “knowledge about
client” were ranked as the less important knowledge at execution. This means that at execution
phase, the process of project planning has been conducted, so both knowledge about client, and
finding the right person are not as important as other types of knowledge (Project Management
Institute 2013).
At the closing phase, “knowledge of PM” and “knowledge about organisational procedure”
are the most important knowledge, from respondents’ points-of-view, while, “knowledge about
supplier” and “legal knowledge” are not as important as other types of knowledge. According to
PM standards, at closing, the project should be formally finished through verifying the project
deliverables and terminating the contract (Project Management Institute 2013). Therefore,
knowledge of PM is mandatory to professionally follow the closing steps, and also, it is very
important to have a good knowledge of organisational procedures to formally finish projects in
accordance with organisational policies. On the other hand, since project deliverables have been
already submitted and they are ready to verify, then knowledge about suppliers and legal
knowledge are not going to be very helpful at this stage (Project Management Institute 2013).
After analysing the rank of each type of knowledge at various phases, another level of
investigation was carried out to determine the overall rank of eight types of knowledge,
142 Chapter 6 | Case Study Analysis: GOVCO
regardless of project lifecycle phases. Similarly, the AHP technique was used to assign correct
weights for each entity, then, their weighted percentages were calculated and ranked, as
depicted in Table 6-8. According to research findings, “project management knowledge”,
“knowledge about procedures”, and “Knowledge about client” are the most important types of
knowledge required during the project lifecycle, while, ”knowledge about suppliers”, “legal and
statutory knowledge”, and “costing knowledge” are not as important as the other types of
knowledge.
In summary, eight types of knowledge were examined in the GOVCO to explore the
importance of them during project lifecycle. In addition, the total rank has been analysed to find
the importance of knowledge types at first level maturity, in which the following ranking was
revealed: 1) Project Management Knowledge, 2) Knowledge about Procedures, 3) Knowledge
about Clients, 4) Technical Knowledge, 5) Knowledge of who knows what, 6) Costing
Knowledge, 7) Legal and statutory Knowledge, and 8) Knowledge about suppliers.
Consistently, the first three types of knowledge are very important knowledge to initiate and
undertake the project (Project Management Institute, 2012). This could be insightful
information for those PMOs which have a similar level of maturity. So far, the first two sub-
questions have answered the first research question (RQ1- How are KM practices and processes
employed in the PMOs?). The next section aims to completely answer the first research question
as well as second research question (RQ2- How do KM practices contribute to improve maturity
level of the PMO?), through discussing four knowledge management processes and their
subsequent KM practices.
Knowledge management processes and practices in GOVCO 6.5.2
As discussed in the previous chapter, four KM processes were adopted in which each process
has numbers of KM practices. Also, it was assumed that all four KM processes are employed
throughout the project lifecycle (PLC) except for the closing phase, as depicted in Table 6-9.
This means that all KM processes should be utilised during PLC, however, knowledge capturing
is the only KM process which should be used at closing phase. This assumption will be
examined during the case study analysis.
Table 6-9 KM processes and PLC (adopted from Owen and Burstein (2005))
Initiation Planning Execution
& monitoring
Closing
Knowledge Creation √ √ √ Knowledge Capturing √ √ √ √
Knowledge Transferring √ √ √ Knowledge Reuse √ √ √
In this section, the second research question (RQ2- How do KM practices contribute to
improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so, the
Chapter 6 Case Study Analysis: GOVCO 143
following steps have be carried out: 1) investigating the utilisation of KM practices and KM
processes at four phases of PLC, 2) examining the above-mentioned assumption about KM
processes at project lifecycle, and 3) ranking the importance of four KM practices at each phase
of the project lifecycle. To do so, the research framework and research methodology were
followed thoroughly, as explained in the previous chapter, i.e. section 5.5.2. After following all
required processes, the obtained information was entered into Nvivo and eventually the
following categories have been developed, as depicted at Figure 6-6.
Figure 6-6 A snapshot of KM process categories in the Nvivo (developed for this research)
In order to analyse the collected data, frequency was used as the main criteria to explore the
current status of knowledge management in this case. During the process of coding interviews,
more than two hundred and fifty (250) comments and quotes, which have been directly
mentioned to explain the usage of KM practices, were recognised and then coded accordingly.
After analysing GOVCO’S employees’ comments, it was revealed that more thirty one percent
of KM practices are employed at execution and monitoring phase, while only less than nineteen
percent are utilised at closing stage, as shown at Table 6-10. This is an indication of using
more KM practices during the execution and monitoring phase in comparison to closing phase.
This finding is consistent with KM and PM literature, since the majority of project activities
should be undertaken at execution and monitoring phase (Project Management Institute 2013).
144 Chapter 6 | Case Study Analysis: GOVCO
In addition, initiation phase and then planning are the second and third phase in terms of
frequency.
From KM process perspective, it was found that more sixty percent of current practices are
utilised for knowledge capturing, while only less than 1.5 percent are employed for facilitating
project knowledge reusing. This finding shows that the majority of current KM practices have
been developed to support the knowledge capturing process, while few practices contribute to
knowledge reusing. This is consistent with previous findings in which participants were
complaining about poor access to previous project information as well as lessons learned.
Despite the significant number of KM practices for capturing project knowledge, there are still
some challenges in this regard. For instance, finding the right person or having proper access to
the existence information have been mentioned as current issues of GOVCO’s PMO.
Table 6-10 The usage of KM processes in GOVCO (developed for this research)
Initiation Planning Execution &
monitoring Closing
29.2% 20.8% 31.7% 18.3% Knowledge Creation 14.0%
Percentage of KM processes Knowledge Capturing 60.8%
Knowledge Transferring 23.8% Knowledge Reuse 1.4%
In addition, knowledge transferring is the second most frequent-mentioned KM process. This
means that there are quite numbers of practices to assist with transferring project knowledge. As
it was observed in the GOVCO’s PMO, training is an important activity for PMO as well as
email communication to share the knowledge. In addition, there are some practices such as
lunch forums and mentoring programs to facilitate the transferring project knowledge either in
public or person. On the other hand, knowledge creation, with only fourteen percent of total KM
practices, does not appear significantly supported by current practices.
According to the research framework, only knowledge capturing practices should be
employed at the closing phase. This assumption has been confirmed, as 19 out of 20 practices at
closing phase are used to capture project knowledge, mostly for project review and lessons
learned. As Figure 6-7 depicts, more than ninety-five percent of quotes have been mentioned to
emphasis the utilisation of knowledge capturing activities at closing phase, which is consistent
with research framework. In addition, from participants’ point-of-view, the knowledge
capturing process is supported by numbers of practices during the project lifecycle, however,
the current knowledge capturing practices are yet to be developed, as numbers of issues related
to knowledge capturing have been recognised earlier. This means that despite the existence of a
number of practices to capture project knowledge, respondents believe that not only current
processes need to be improved, such as lessons learned, but also there is a significant need to
Chapter 6 Case Study Analysis: GOVCO 145
develop new practices, such as knowledge filtering, to improving the capturing process. [“…
There is obvious need to filter current information…”, quoted by In.Gd.4. ]
Figure 6-7 KM processes at project lifecycle: GOVCO (developed for this research)
According to the research findings, the second most frequently mentioned KM process is the
knowledge transferring, as illustrated at Table 6-10. The study findings show that the majority
of knowledge transferring practices are used at initiation, execution and planning phases, while
there is only one practice, conducting workshops at the end of project, which is utilised at
closing phase. According to the research framework this practice is used at both knowledge
capturing and knowledge transferring points. Since a closing phase is about to terminate all
project activities, it could be assumed that these kinds of workshop are mostly conducted for
capturing purposes rather than transferring. Therefore, there some practices in place to facilitate
knowledge transferring at three phases of projects, however, the existing process needs to be
improved, from a respondent point-of-view, as a number of issues have been mentioned in this
regard. For instance, the following is one of the comments about knowledge transferring in
GOVCO’s PMO
“…knowledge transferring doesn’t always happen at lunch forum, and if it does
people are sometimes more interested in the lunch and their conversation about the
weekend than what’s actually being talked about…”, quoted by In.Gd.3
Knowledge creation is the third most frequently mentioned KM process in the research
findings in which it is supported by numbers of practices at three phases, except closing.
Respondents believe that most knowledge creation activities are conducted at initiation,
execution, and planning phase, respectively. However, it was found that knowledge creation is
not the main priority for the PMO. In other words, fourteen percent of coded comments indicate
that project knowledge creation is not as important as capturing and transferring in GOVCO.
Two reasons could be mentioned to justify this finding: 1) GOVCO’s PMO aims to be the
centre of excellence, which means that PMO does not involve in project execution and
Initiation Planning Execution &Monitoring
Closing
7 6 5
0
23
15
30
19
15
6
10
1 1 0 1 0
Creation Capturing Transferring ResuingReusing
146 Chapter 6 | Case Study Analysis: GOVCO
implementation, and 2) at the second level of maturity the major focus has been on developing
processes for facilitating project knowledge capturing and transferring rather than creation and
reusing. Consistently, according to the research framework, knowledge capturing and
transferring are not only the main priority for the lower level of maturity, but also knowledge
creation and reusing are dependent on the efficiency of knowledge capturing and transferring. In
addition, as will be discussed in a later section, respondents consistently ranked the importance
of KM processes, in which knowledge capturing and transferring are chosen as the first priority,
in comparison to knowledge creation and knowledge reusing.
In summary, it could be inferred that the majority of KM processes are supported through
their associated practices during a project lifecycle, however, only knowledge capturing is
managed at the closing phase. Recalling the maturity level of PMO, the existing practices are
not only faced with numbers of challenges, but also there are some requirements yet to be
addressed through developing new practices. In this section, four KM processes have been
discussed in general. In the next sections, each knowledge process will be individually
discussed to answer the second research question (RQ2. How do KM practices contribute to
improve maturity level of the PMO?).
Knowledge Capturing in GOVCO’s Project Management Office 6.5.2.1
According to the current literature, and also the research framework, knowledge capturing is
the only KM process that should be employed from beginning to end of the project lifecycle
(Owen and Burstein 2005). As discussed earlier, the research findings have confirmed the
above-mentioned assumption through examining interview data as well as survey-questionnaire.
In addition, as it was mentioned earlier, knowledge capturing is the most frequently mentioned
KM process, with more than sixty percent of the associated comments. As depicted at Table 6-
11, three columns have been presented to illustrate the knowledge capturing at the GOVCO’s
PMO, in which the first table shows KM categories based on the research framework, the
second column represents the customised practices or systems to support the main categories,
and the third one displays the associated frequency of the KM categories.
The further analysis revealed that more than half of the comments have emphasised
utilisation of a support document management system (DMS) in the PMO. This means that
respondents believe that there are numbers of forms and templates, as well as a document
management system, to support some practices such as project report, meeting minutes, and
lessons learned. In addition, during the document analysis and direct observation stages, more
than sixty forms and templates that are used during the project life cycle were recognised. These
findings indicate that the current DMS in GOVCO’s PMO addresses many the required project
management practices, such as meeting minutes and project reports, as shown in Table 6-11.
Chapter 6 Case Study Analysis: GOVCO 147
The second most frequently mentioned practice for capturing knowledge in GOVCO, is
formal and informal events. The research findings confirm that formal and informal events are
supported through numbers of ways, such as meetings, lunch forums and workshops. According
to the research framework, practices such as forums and workshops could be used for both
knowledge capturing and knowledge transferring purposes. In addition, GOVCO’s employees
believe that during these events not only they could get, formally or informally, some answers
to their questions, but also they help them to transfer some of their knowledge to their
colleagues and project team members, which normally doesn’t happen in other environments.
Table 6-11 Knowledge capturing’s practices: GOVCO (developed for this research)
Knowledge Capturing categories Associated Practices in GOVCO Frequency
Data base • Yellow page • Team contact list • Survey monkey
6
Document Management System (DMS)
• Technical design • Request for information • Project Reports • Project Proposal • Project Management templates • Project Debriefing • Project Briefing • Post project review • Meeting minutes • Lessons learned
66
Expert locator • Through email and PMO guidance 4 File Management System (FMS) • Windows base system 1
Formal or Informal events • Regular meeting • Lunch forums • Workshops
28
Frequently Ask Questions (FAQ) • None 0
Intranet • A customised web-based intranet 8 Knowledge detection tools • None 0 Knowledge inquiry system • None 0
Knowledge repositories • None 0
Management Information System (MIS) • PM Mate • A-Connect • SAP
20
The Management Information System (MIS) is the third frequently mentioned practice
which contributes to capture project knowledge in GOVCO. During the course of data
collection three applications were recognised which are utilised to support knowledge capturing:
PMMate, A connect and SAP. These applications and their purposes of usage have been
discussed earlier, based on direct observation and document analysis. From interviewees’
points-of-view these tools are useful to assist them with capturing knowledge, however, the
integration among the current systems and other applications are yet to be addressed in the
GOVCO. This finding indicates that the existence of a reliable MIS is necessary for capturing
148 Chapter 6 | Case Study Analysis: GOVCO
project knowledge, therefore the PMO is responsible for developing such a system to support
KM.
A customised intranet, numbers of data bases, expert locator, and an internal file
management system are the other KM practices in the GOVCO’s PMO for facilitating project
knowledge capturing. According to GOVCO’s respondents, the current file management system
has been useful for them to locate required knowledge, which is stored internally; however, this
system should be updated since it is not web-based, so it is not capable of searching or filtering
information. In addition, the current database such as yellow page and contact list have been set
up, separately, therefore integrating these systems is another necessary step for PMO, especially
to obtain the next level of maturity. On the other hand, some of the proposed knowledge
capturing practices in the framework, such as knowledge detection tools and knowledge inquiry
system, have not been recognised in GOVCO’s PMO. Since the maturity level of PMO is still at
low levels, it is reasonable to explore some undeveloped KM practices. Having said that, these
practices should be considered when PMO’s managers decide to improve the maturity level of
PMO.
Figure 6-8 Knowledge Capturing in project lifecycle: GOVCO (developed for this research)
From a project lifecycle point-of-view, as depicted at Figure 6-8, more than twenty five
percent of knowledge capturing activities incur in the execution and monitoring phase, twenty
percent at initiation, sixteen percent at closing, and twelve percent at the planning phase. As it
can be found in Figure 6-8, the combination of utilisation of KM practices varies at each phase.
In the Planning phase most of the KM practices are used, while only three practices are
employed at execution phase. Also, DMS are the most utilised KM practice in four project
phases. This could be an indication for PMO at the same level to improve their DMS to support
knowledge capturing speciality at Execution and Closing phases.
02468
101214161820
Management InformationSystem(MIS)Knowledge repositories
Knowledge inquiry system
Knowledge detection tools
Intranet
Frequently Ask Questions (FAQ)
Formal or Informal events
File Management System(FMS)
Expert locator
Document Management System(DMS)
Chapter 6 Case Study Analysis: GOVCO 149
In conclusion, knowledge capturing is recognised as the most frequently mentioned KM
process, with more than 60 percent of the total KM process comments. In addition, the majority
of the proposed knowledge capturing practices, by the research framework, are employed in
GOVCO, but some KM practices such as FAQ are yet to be addressed. According to the
research framework, awareness of knowledge capturing should be raised, at both manager and
employee level, in the second level of maturity (Kerzner 2005). The research findings confirm
this assumption, in which all respondents have mentioned the number of practices to explain
knowledge capturing process in GOVCO.
Knowledge Transferring in GOVCO’s Project Management Office 6.5.2.2
According to the research findings, knowledge transferring is the second most frequently
mentioned KM process, with more than twenty-three percent of the coded data. This means that
about a quarter of coded data for KM processes, support those KM practices which facilitate
transferring project knowledge. In other words during the coding process, interviews were
analysed against research framework and if there was a comment that was related to associated
KM practices, then it was coded accordingly (Lindner and Wald 2011). Then through using
query and classification functions, the model was built up to explain the knowledge transferring
process and its associated practices.
Table 6-12 Knowledge Transferring categories and pratices: GOVCO (developed for this research)
KM transferring categories Associated System and Practices
at GOVCO’s PMO Frequency
Communication channels • Chat rooms • Email • Phone
26
Database • Contact list 2 Discussion forums • None 5
Electronic bulletin board • Project bulletin and reports 2
Formal and informal events • Seminar and workshops • Face to face conversation 29
Intranet • Customised web-based network 3 Knowledge directories • None 0
Knowledge list • None 0
Training& mentoring • Induction • Mentoring 15
Video and Tele Conference meeting • None 0
Yellow page • None 1
The most frequently mentioned practice for transferring project knowledge is “formal and
informal events”, as shown at Figure 6-9 and Table 6-12. According to the research framework,
this practice and its underpinnings, i.e. seminar and workshops, could be used for both
knowledge capturing and knowledge transferring. As discussed earlier, “formal and informal
events” was ranked as the second most frequently mentioned practice for capturing knowledge,
while knowledge transferring is the most important practice from a participant’s point-of-view.
150 Chapter 6 | Case Study Analysis: GOVCO
This means that participants believe that workshops and seminar as well as face to face
conversation are used in GOVCO to facilitate the knowledge transferring process. In addition,
discussion forums are other practices which could be considered in this category.
The second most frequently mentioned practice for transferring is the existing
“communication channels”. In fact, GOVCO’s employees believe that email is a very useful
tool for knowledge transferring and the PMO is proactive in sending emails as reminders or
sharing knowledge, as following the comments explain:
“…PMO is sending out alerts is very helpful just to keep to know who needs to be
signing of and everything before you’re going out to tender or going to engage
anyone…”, quoted by In.Gd.4
“… PMO sends that out regular email as to some of the things that we’ve mentioned.
So it is about capturing and transferring that knowledge that way…”, quoted by In.Gd.1
Another KM practice which is part of a communication channel is phone conversations. In
addition, the PMO has a comprehensive contact list for all experts and it facilitates internal and
external phone discussion, which could be considered as another informal event as well.
Training and mentoring are the third most frequent observation for knowledge
transferring, however, the PMO manager and GOVCO senior manager believe that it is the most
important activity that PMO conducts for the purpose of transferring knowledge, as In.Gd.1
describes “…training is definitely something that PMO does… So we coordinate training. Now
what we do is we ask the PMs what sort of training they need and what areas. So we get a fairly
basic course , and then we start to then focus on that training…” and, also In.Gd.2 believes
“…Well we’ve got a structured training program and it’s basically…we’ve just done an
induction manual when people first come into the organisation and these are things you need to
know…”. The training courses are conducted mostly through providing project management as
well as associated technical courses for GOVCO’s employees. Most of the trainings are
managed in the classroom but for remote areas, some video tapes or CDs are provided and sent.
In addition, the mentoring programs have been initiated recently but most of them are managed
informally. However, this needs to be improved, as there are some issues in this regard, “…I
think they’re trying to look at mentoring; the hard thing is we have relatively small teams so I
know when I started they talked about having like a mentor for me but then because lots of work
came in they kind of just dumped the work on you…”, quoted by In.Gd.4.
Moreover, there are some other tools such as internet, DBs and electronic bulletins, which
facilitate the sharing and transferring of project knowledge. But these practices have not been
well developed, as numbers of challenges were discussed earlier in this regard. For instance,
participants believe that the current intranet is not only searchable, but also the access to
required information is not user friendly. Also, the current DBs are not properly integrated to
Chapter 6 Case Study Analysis: GOVCO 151
SAP and internet, which needs to be improved. On the other hand, three important KM practices
for knowledge transfer, i.e. knowledge directory, knowledge list, and teleconference meeting,
are yet to be addressed in GOVCO. Since the maturity level of PMO is two, so it is plausible to
see that some of the advanced KM practices have not been developed yet.
From a project lifecycle perspective, as could be seen in Figure 6-9, the majority of
knowledge transferring activities are managed at initiation, execution, and planning phases,
while at closing phase there are limited practices to support knowledge transferring. According
to the research framework, knowledge capturing should be the only KM process to be employed
at closing phase, therefore this finding is consistent with the research framework and the
proposed assumption. In addition, respondents believe that the majority of knowledge
transferring activities incur at the initiation, and execution and monitoring phases through
“formal and informal events’ as well as training and mentoring programs. This finding is also in
line with PM standards as well as the research framework, as it is assumed that most of training
and events should be managed at execution phase. (Project Management Institute 2013). These
findings indicate the importance of knowledge transferring at initiation and execution phase,
where projects are defined and then executed.
Figure 6-9 Knowledge Transferring practices in GOVCO (developed for this research)
In summary, knowledge transferring is the second most frequent KM process from
participants’ points-of-view. According to the research framework, the above mentioned
findings confirm the research assumptions. From respondents’ perspectives, “formal and
informal events” is the most important practice for transferring project knowledge and,
respectively, communication and training practices are the second and third most important KM
practices. However, there are numbers of practices that are yet to be developed in GOVCO’s
PMO for improving the quality of knowledge transferring, such as knowledge list and
0
2
4
6
8
10
12
14
16
18
Initiation Planning Execution&Monitoring
Closing
Communication channels
Database
Discussion forums
Electronic bulletin board
Formal and informal events
Intranet
Knowledge directories
Knowledge list
Training& mentoring
Video and Tele Conference meeting
Yellow page
152 Chapter 6 | Case Study Analysis: GOVCO
knowledge directories. These practices could be addressed by GOVCO’s PMO in order to
achieve the next level of maturity.
Knowledge Creation in GOVCO’s Project Management Office 6.5.2.3
The third most frequently mentioned KM process in GOVCO is knowledge creation,
however, it has been mentioned only 32 times out of more than two hundred and fifty associated
quotes. According to the research framework, there are numbers of practices that could facilitate
knowledge creation process in projects, as shown in Table 6-13. This table shows knowledge
creation practices and their frequencies. It could be inferred that knowledge creation is not used
as frequent as the two previously discussed knowledge processes in GOVCO’s PMO. In other
words, respondents believe that only a small number of practices are in place in GOVCO to
contribute to creating knowledge during the project lifecycle.
Table 6-13 Knowledge creation’s categories in GOVCO (developed for this research)
KM creation categories Associated System/Practices in GOVCO Frequency
Best Practice Cases • None 1
Community of practices • None 9 Data mining • None 0
Decision support system (DSS) • None 0
Deductive & Inductive thinking • Brainstorming 1
Documentation search • None 0
Experience Report • None 3
Expert systems (ES) • Expert Interview • Expert judgment
0
Informal and formal Event • Formal face to face meeting • Workshops & seminar
7
Knowledge Broker • None 4
Research services • Experimentation • Simulation • Use of Metaphors
0
As depicted in Table 6-13, the first and second most frequent KM practices for knowledge
creation are “community of practice”, and informal and formal event” in which respondents
believe that there are some tools to facilitate managing a community of practice and formal and
informal events for knowledge creation purposes, as explained in the following comments:
“…People are gathering together to solve a problem. To do the same practice for instance
you know let’s say the IT guys gathering together to create a new, some sort of you know
feature for the software that would be a community of practice…”, quoted by In.Gd.5.
“…We’ve got a section here called professional services portfolio so on our client projects
we need an architect, an engineer and those sorts of people but normally it’s just been allocated
someone in house…”, quoted by In.Gd.3.
Chapter 6 Case Study Analysis: GOVCO 153
Further investigation revealed that despite the existence of some tools to support community
of practice, the respondents believe that PMO needs to be improved in this regards, as In.Gd.2
comments:
“…We don’t have a community of practice as a formal community of practice but
within each work group I actually run sort of like a mini group session…”.
“…We also facilitate our interaction as an organisation with other parts of Public
Works in a community of practice…”.
According to KM theories, “formal and informal event” is a practice to support both
socialisation and externalisation processes for creating knowledge (Julian 2008; Nonaka and
Takeuchi 1995; Srikantaiah, et al. 2010). In other words, participating in seminars, workshops
and discussion forums is useful to create knowledge during the project lifecycle. The research
findings revealed that the current practices should be improved to enhance the utilisation of
formal and informal events in GOVCO, as In.Gd.3 comments:
“… Possibly for risk there would be a workshop but that’s only on the bigger scale
projects. The smaller projects wouldn’t have a workshop… it would be one of those
meetings in the initiation stage…”
Another KM practice to facilitate knowledge creation is “knowledge broker”. According to
the current literature PMO, itself, is considered as a knowledge broker in which it has the
responsibility to facilitate communication among employees for knowledge creation purposes
(Barclay and Osei-Bryson 2010). This means that PMO has a critical responsibility for
facilitating project knowledge management in organisations. The research findings revealed that
the importance of PMO as a knowledge broker is yet to be realised in GOVCO, as participants
have only mentioned the knowledge broker four times, out of more than 30 times. In other
words, from respondents’ points-of-view there some practices in place to support PMO as the
knowledge broker, however, those practices are not significant enough to emphasise the
importance of PMO for managing project knowledge, as In.Gd.3 comments: “…And then
contact us for more information or yes I am the one in a hundred that’s going to have this
problem. Show me someone show me another form or show me someone to talk to or introduce
me to this person in those sorts of less common examples. But I still think we miss stuff because
of that technology barrier…”.
The research findings explored that the other KM practices for supporting knowledge
creation, such as expert system, Research services, and data mining, are yet to be developed in
GOVCO, as little evidence was recognised to facilitate the mentioned practices. This is another
indication for GOVCO’s PMO to improve the quality of project knowledge creation.
154 Chapter 6 | Case Study Analysis: GOVCO
From a project lifecycle perspective, GOVCO’s respondents have mentioned that knowledge
creation practices are employed, to some extent, at three project phases: Initiation; planning; and
execution, while there is limited evidence to support knowledge creation at the closing phase.
This finding again confirms one of the research framework premises, which assumes that only
knowledge capturing should be managed at a closing phase. Also, it revealed that in GOVCO’s
PMO, the majority of knowledge creation activities are managed at Planning, then the execution
phase, which is in line with the PM standards, as they advise to create knowledge during
planning and execution phases (Project Management Institute 2013; Reich and Wee 2006). This
might be good guidance for PMOs with the same maturity level to help focus on improving
their knowledge creation practices at planning and execution phases, as there is no need to
create knowledge at closing phase.
Figure 6-10 Knowledge Creation in GOVCO (developed for this research)
In summary, knowledge creation is the third most frequent KM process in the GOVCO’s
PMO. As discussed earlier, GOVCO’s PMO has been designed to be the centre of excellence.
This means that it is not involved in the project and therefore, knowledge creation could not be
the first priority. As discussed earlier, in this case, knowledge capturing and transferring are the
first and second most frequently mentioned KM process, while knowledge creation is the third.
This means that GOVCO’s participants believe that majority of the current KM practices
support knowledge capturing and transferring. According to the research framework, the quality
of knowledge creation is dependent on knowledge capturing and transferring processes (Owen
and Burstein 2005; Owen, et al. 2004). This means that, in order to develop productive
knowledge creation practices, the existence of practical processes for supporting knowledge
capturing and transferring is mandatory. Therefore, a PMO with low level of maturity should
focus on developing, capturing and transferring processes first, and then it may initiate the
0
1
2
3
4
5
Initiation Planning Execution&Monitoring
Closing
Best Practice Cases
Community of practices
Data mining
Decision support system (DSS)
Deductive & Inductive thinking
Documentation search
Experience Report
Expert systems (ES)
Informal and formal Event
Knowledge Broker
Research services
Chapter 6 Case Study Analysis: GOVCO 155
development of knowledge creation practices. Consistently, the research findings confirm the
research framework and its associated premises in this regards.
Knowledge Reusing in GOVCO’s Project Management Office 6.5.2.4
The last process of KM is knowledge reusing which has been mentioned only 6 times during
the data collection course. This means that participants do not believe that current tools and
systems significantly contribute to reusing of project knowledge. As shown in Table 6-14, only
DBs, DMS and the intranet are relatively facilitated knowledge reusing processes, however,
they are yet to be developed from the respondents’ perspective.
Table 6-14 Knowledge Reusing in GOVCO (developed for this research)
KM reusing categories Associated Practices Frequency
Data base • Internal DB 2 Data mining • None 0
Document Management System • After action review • Post project reports 2
Electronic notice board • None 0 Expert systems • None 0
Formal or informal meetings • None 0 Intranet • The existing intranet 1
Knowledge detection tools • None 0 Knowledge map • None 0 Lessons learnt • Some internal process 1 Yellow page • None 0
According to the research findings, the majority of respondents are aware of the usefulness
of having KM practices to support knowledge reusing, but they believe that knowledge reusing
practices have not been appropriately addressed in GOVCO, as some comments confirm this
statement:
“…We’ve got so much information that we’re actually developing that people are now
starting to struggle with knowing exactly what they do at what point…”, quoted by In.Gd.2.
“…if there was a way of accessing information about a similar project for a similar budget
and similar contract type I would have gone and had a look at it to try and find out some
information about you know what they recommend you do. But I didn’t really get any specific
documentation from anyone…”, quoted by In.Gd.4
156 Chapter 6 | Case Study Analysis: GOVCO
Figure 6-11 Knowledge reusing in GOVCO (developed for this research)
Similarly, from a project lifecycle point-of-view, the collected data shown confirms the
status of knowledge reusing in GOVCO, as can be found in Figure 6-11, where they revealed
that the current practices for supporting knowledge reusing are not significant and they need to
be appropriately developed. Having said that, these limited practices are used at initiation,
planning, and execution phase, while there is no practice for reusing knowledge at closing
phase. Similar to previous KM processes, this finding confirms the research framework’s
assumption, in which it is assumed that only knowledge capturing should be conducted at
closing phase.
In summary, knowledge reusing is the least frequently mentioned KM process in
GOVCO’s PMO. In other words, reusing the previous projects’ knowledge has not been
appropriately facilitated, because of the lack of KM practices. According to Love, et al. (2003)
“rework” is one of the significant challenges for projects in Australian companies, costing more
than fifty percent of overrun costs. Therefore, PMOs should significantly contribute to
developing KM practices to improve the knowledge reusing process. According to the research
framework, a reliable knowledge capturing and transferring system is required to develop an
efficient knowledge reusing process. This means that the research findings are in line with the
research framework in this regard. It could be inferred that, at the low level of maturity, the
main focus should be on improving the knowledge capturing and transferring then knowledge
creation, and reusing.
Summary 6.5.2.5
In conclusion, the first research question (RQ1- How are KM practices and processes
employed in the PMOs?) and its sub-questions were answered in this section. In order to answer
the third sub-question (RQ 1.3 What kinds of KM practices are utilised in each maturity level of
0
1
Initiation Planning Execution &Monitoring
Closing
Data base
Data mining
Document ManagementSystemElectronic notice board
Expert systems
Formal or informal meetings
Intranet
Knowledge detection tools
Knowledge map
Lesson learnt
Chapter 6 Case Study Analysis: GOVCO 157
PMO?), it was realised that more than sixty percent of comments support knowledge capturing,
while about twenty-three percent of them discuss knowledge transferring. In addition,
knowledge creation and reusing, together, are supported by only less than fifteen percent of the
collected data. Therefore, it could be concluded that knowledge capturing and transferring
practices are the most utilised KM practices, in comparison to knowledge reusing and creation.
According to the research framework, only knowledge capturing should be employed at
closing phase. This assumption was examined through using some techniques and eventually, it
was revealed that the collected data supports this research assumption. In addition, the research
data explored that the majority of KM activities are undertaken at Execution and monitoring
phases which is in line with PM literature, since PMBOK explicitly addresses numbers of PM
processes to support KM at planning and execution phase (Project Management Institute 2013).
According to the study findings, the following propositions could be made to address the
KM at the second level of maturity: 1) Knowledge capturing and transferring are the most
important processes to be improved at the second level of maturity, which means that the PMO
should firstly focus on improving the current practices for capturing knowledge, and then
transferring, 2) Knowledge creation has the third priority at the PMO with a second level of
maturity, however, the existence of some practices to support the basics is necessary, 3)
Knowledge reusing is the least important KM process at this level, and it is dependent on
capturing and transferring. This means the quality improvement of knowledge capturing and
transferring directly impacts on quality of the knowledge reusing process.
The importance of knowledge management processes in GOVCO 6.5.3
In order to answer the second research question (RQ2-How do KM practices contribute to
improve maturity level of the PMO) a survey–questionnaire was distributed among participants,
and seven of them were returned. In this survey, GOVCO’s participants were asked to rank the
importance of four KM processes: Creation; Capturing; Transferring and Reusing at project
life cycle, i.e. Initiation; Planning; Execution & monitoring; and Closing. After collecting the
respondents’ answers, MS Excel was used to analyse the collected data. As discussed earlier,
the AHP technique is a suitable and accurate method for ranking the priority of competing
phenomena (Lindner and Wald 2011; Stam and Silva 1997), therefore, this technique was used
to rank KM processes in GOVCO’s PMO.
The research findings revealed that, at the initiation phase, knowledge capturing and then
transferring, were ranked as the most important KM processes, while knowledge creation and
reusing got the third and fourth rank, as depicted at Figure 6-12. According to PMBOK (2013)
two major PM processes: developing project charter; and identifying stakeholders, should be
conducted at the initiation phase. In fact, both the recommended PM processes contribute to
capturing the required knowledge about project stakeholders as well as project boundaries
158 Chapter 6 | Case Study Analysis: GOVCO
(Project Management Institute 2013; Reich and Wee 2006). Also, it is important to run
workshops and seminars to transfer the existing knowledge in order to provide accurate
information for the next phase. In addition, the created knowledge should be captured, since it is
a fundamental prerequisite for the next phases, especially planning.
As PMBOK (2012) advises, information about similar projects contributes to better
provision of project charter, scope statement, and planning materials. This means that
knowledge reusing is an important KM process at the initiation and planning phases. However,
GOVCO’s respondents ranked knowledge reusing as the least important process in both
questionnaires, and in the collected data from interviews. This means that research findings are
not in line with the current literature in this regard. In order to analyse this inconsistency, both
PMBOK and the maturity level of GOVCO’s PMO have been considered. In fact, it was found
that PMBOK has an assumption in which it assumes that all PM practices should be conducted
simultaneously, so the capability of the project environment has not been taken into account. In
addition, PMO maturity models have been proposed to develop the mentioned capability and
through implementing PM practices in gradual steps at various levels (Project Management
Institute, 2008b). This means that PM practices should be developed based on priorities as well
as organisational readiness. In other words, at the low levels of maturity, the basic PM practices
should be developed for preparing PMO to manage advanced practices in higher maturity levels
(Kerzner, 2005).
0
1
2
3
4
Initiation Phase
Capturing Creating Transferring Reusing
0
1
2
3
4
Planning Phase
Chapter 6 Case Study Analysis: GOVCO 159
Figure 6-12 Importance of KM process in project lifecycle: GOVCO (developed for this study)
The research findings revealed that, from a KM perspective, knowledge capturing and
creation have higher priorities for GOVCO’s PMO at this level of maturity, therefore
knowledge reusing has been not ranked as an important process at this stage. According to
PMBOK, at the planning phase, knowledge capturing and creation are the most important KM
processes (Reich and Wee 2006). In a consistent manner, GOVCO’s respondents have ranked
knowledge capturing and creation as the first and second most important KM process at
planning phase. This means that these two processes are at this phase, since all project plans are
created and need to be captured accordingly. In addition, knowledge transferring has been
placed as the second most important KM practice, similar to creation. This level of importance
logically makes sense because the created knowledge need to be captured and also transferred
appropriately. In other words, if the created knowledge at planning phase is not captured or
transferred, then the project success rate is significantly reduced (Reich and Wee 2006).
On the other hand, knowledge reusing was asserted as the least important KM process at the
planning phase. As discussed earlier, using knowledge of previous projects has a significant
impact on creating and developing project plans (Project Management Institute 2013), however,
knowledge reusing has been ranked as important as other KM processes. Similar to previous
discussion about the initiation phase, it could be justified that the level of maturity is an
important factor for prioritising the importance of KM processes. This means that at this level of
maturity, participants believe that knowledge reusing is not their first priority, as they are
dealing with numbers of challenges in regards to transferring and capturing project knowledge.
According to PM methodologies and the research framework, all of the KM processes
should be employed at the execution and monitoring phase (Owen and Burstein 2005; Owen,
et al. 2004; Reich and Wee 2006). According to research findings, the maturity level of the
PMO is an important factor to determine what sort of KM processes should be employed. In the
GOVCO’s PMO, respondents have indicated that capturing and transferring are the most
important KM processes, while they believe that knowledge creation and reusing are in their
0
1
2
3
4
Execution and Monitoring Phase 0
1
2
3
4
Closing Phase
160 Chapter 6 | Case Study Analysis: GOVCO
next level of priority. According to PM standards, knowledge capturing and transferring should
be selected as the first priority (Project Management Institute 2013; Reich and Wee 2006), so
the research findings are in line with the research framework as well as the current literature.
In order to analyse the importance of knowledge creation over knowledge reusing at
execution phase, other collected data were considered, specifically interviews. As discussed
earlier, GOVCO’s PMO has been designed to be a centre of excellence, which means that it
does not involve itself at project implementation as a resource. In other words, it just facilitates
execution through some forms and they have minimum information about created knowledge in
the execution phase, as one of the respondents explains, “…So in that stage you’re kind of
leaving the consultants to their own devices a little bit because they’re the experts in their field
but then making sure that they’re all on the same path…”, quoted by In.Gd.4. Therefore, it
could be inferred that participants have ranked knowledge creation at the third priority as they
believe that they have less involvement during the execution phase.
The research framework assumes that knowledge capturing should be the only KM process
to be employed at the closing phase. This assumption was examined in the previous section,
and it was confirmed through interview data analysis. As shown in Figure 6-12, knowledge
capturing was ranked as the most important KM process at closing phase, by GOVCO’s
respondents. This means that the research findings from both interview and the survey-
questionnaire confirm the importance of the knowledge capturing process for closing phase.
This could be a useful indication for PMOs in order to focus on managing project knowledge at
closing phase in order to improve their systems to facilitate this KM process.
Figure 6-13 The general ranking of KM processes in GOVCO (developed for this research)
In the next step of analysis, the importance of KM processes in project lifecycle has been
conducted to explore the general rank of KM processes, regardless of project phases. To do so,
the AHP method was employed through assigning appropriate weight to each project phase.
This weighted model enables the researcher to analyse the overall rank of the KM process
regardless of various phases (Lindner and Wald 2011). The research findings explored the
following ranking of KM processes: 1) Capturing, 2) Transferring, 3) Creation, and 4) Reusing,
0
1
2
3
4
Capturing Creating Transferring Reusing
Chapter 6 Case Study Analysis: GOVCO 161
as depicted at Figure 6-13. According to the research findings, GOVCO’s respondents believe
that knowledge capturing and transferring are the most important KM processes, while
knowledge creation and reusing are not as important as the other two processes.
In the previous section, interviews have been analysed to investigate the management of
project knowledge in the GOVCOs’ PMO. As discussed, knowledge capturing was revealed as
the most frequently mentioned KM process among other KM processes. In fact, more than sixty
percent of the coded comments have discussed the current KM practices from a knowledge
capturing perceptive. In addition, knowledge transferring was found as the second most
frequently mentioned KM process with more twenty three percent of the collected data. Also,
knowledge creation and reusing were placed as third and fourth most frequently mentioned KM
process in GOVCO’s PMO. As can be seen in Figure 6-13, the outcomes from the survey are
confirmed by the research findings in the interviews. This consistency of the research findings
significantly improves the quality of collected data, and contributes to develop reliable
propositions for this study.
Furthermore, GOVCO’s PMO has developed more than sixty forms and templates to
facilitate the PM. This finding emphasises the importance of knowledge capturing during the
project lifecycle. In addition, the collected data from direct observation and interview analysis
revealed the importance of knowledge transferring, facilitated through numbers of practices
such as workshops, seminars, and discussion forums. However, during the direct observation
some evidence was found for supporting knowledge creation and reusing. These findings, are
also are consistent with the mentioned research findings in regards to the importance of
knowledge capturing and transferring over knowledge creation and reusing.
In summary, the research findings from the survey-questionnaire, interview analysis,
document analysis and direct observation, have consistently revealed that knowledge capturing
and transferring are the most important KM processes in the GOVCO’s PMO, while knowledge
creation and reusing are not as important as the other two KM processes. Therefore, it could be
concluded that current KM practices mainly support knowledge management processes in the
following order: Capturing, Transferring, Creating, and Reusing. In addition, it could be
inferred that, at the second level of maturity, the PMO should focus on developing KM practices
to support knowledge capturing and transferring processes as their first priority. In other words,
if a PMO aims to improve the level of maturity, it should firstly provide a reliable KM system
for supporting KM capturing and transferring, and then it could focus on knowledge creation
and reusing practices. At this section, the first sub-question of the second research (RQ2-How
do KM practices contribute to improve maturity level of the PMO) has been answered. The next
section aims to discuss the remaining part of the second question.
162 Chapter 6 | Case Study Analysis: GOVCO
DISCUSSION AND IMPLICATIONS 6.6
In the previous sections the first question, and initial part of the second research question
have been discussed. At first, the existing challenges of project KM in GOVCO have been
explored at the early sections of this chapter, then the importance of the four KM processes have
been analysed through using both interview, and questionnaire methods. As discussed, the
research outcomes from both mentioned methods are consistent, which contributes to the quality
of research findings (Yin 2009). In this section, each KM process will be discussed to
investigate its relation with both the recognised KM challenges, and its associated sub-
processes.
Knowledge capturing’s sub processes and practices in GOVCO 6.6.1
According to the research framework, knowledge capturing has been classified into four sub-
processes: Identification, Storing, Classification, and Selection, as shown at Table 6-15 (Lytras
and Pouloudi 2003; Nissen, et al. 2000). As discussed earlier, four KM challenges have been
recognised in GOVCO’s PMO: 1) Lack of integration among current processes and systems, 2)
Issue of locating and accessing right information and/or right expert, 3) Lack of KM practices
and KM processes during project life cycle, and 4) Issue of appropriate access to the existing
systems. The collected data was entered into Nvivo as well as the research framework, and then
numbers of Nvivo’s functions, such as queries and relationship, were employed to analyse the
relation between challenges and knowledge capturing sub-processes.
According to the research findings “knowledge storing and classification” are the most
frequent knowledge capturing sub-processes, while knowledge identification and selection are
yet to be addressed in GOVCO’s PMO. In addition, the developed queries in the Nvivo have
revealed that most of the recognised challenges are knowledge identification and selection, as
illustrated in Table 6-15. For instance, “issue of locating right information or person” has
occurred because of lack of some KM practices such as “expert locater” and ‘knowledge
detection tools”, and similarly, “issue of appropriate access to the existing systems” is related to
lack of practices such as data base and FAQ. In addition, the majority of the associated
practices to support knowledge storing and classification have been addressed, to some extent,
as shown in Table 6-15. On the other hand, according to the research findings, most of the KM
practices to support knowledge identification and selection are yet to be addressed in GOVCO.
In a consistent manner, it was revealed that most of the recognised challenges are related to
knowledge identification and selection. This means that the development of some missing KM
practices such as expert locator, FAQ, and knowledge detection tools, will contribute to address
the recognised KM challenges in GOVCO’s PMO.
Table 6-15 Knowledge capturing sub-processes in GOVCO (developed for this research)
Chapter 6 Case Study Analysis: GOVCO 163
K. Capturing Sub
Processes
Practices for Knowledge Capturing
Associated Challenges Comments
Knowledge Identification
• Expert locator • Formal and informal
event
• Knowledge detection tools • Knowledge repositories 2, 3, and 4
A few practices in place, however, it
is yet to be developed
Knowledge Storing
• Data base • Formal and informal
event
• Document Management System (DMS) 1
Most of the current system support this
process
Knowledge Classification
• DMS • Frequently ask
questions (FAQ) • Intranet
• File management system • Management information
system (MIS) 4
After knowledge storing this one has
numbers of practices
Knowledge Selection
• Knowledge inquiry system (KIS)
• Data base • Frequently ask questions
(FAQ) 2 and 4
A few practices in place, however, it
is yet to be developed
The research findings confirm that three KM practices to support knowledge storing, have
been addressed in GOVCO’s PMO, and participants have mentioned this KM sub process as the
most frequent knowledge capturing sub-process. This mean that knowledge storing is supported
through existing KM practices. However, the integration of current KM practices especially for
knowledge storing, is yet to be addressed in the GOVCO’s PMO.
The research analysis revealed that knowledge classification is the second most frequent
mentioned KM sub-process in GOVCO’s PMO. According to the collected data, four out of five
KM practices have been addressed in this case study, i.e. DMS, File management systems, MIS
and Intranet. This means that the majority of the recommended KM to support knowledge
classification has been developed in GOVCO, except for frequently asked questions (FAQ). In
addition, the current knowledge classification practices face one of the recognised KM
challenges, i.e. issue of appropriate access to the existing systems. In other words, GOVCO’s
PMO should develop the access to the current system, to both address the mentioned challenge,
and improve the knowledge classification.
In summary, in GOVCO’s PMO, knowledge capturing is supported by numbers of sub-
processes and their associated practices, as shown in Table 6-15. The research findings revealed
that more than sixty percent of the coded comments support the knowledge capturing process in
this case study. On the other hand, knowledge capturing is faced with numbers of issues and
challenges. According to the research framework, knowledge capturing consists of four sub-
processes: Identification, Storing, Classification, and Selection. The data analysis explored that
knowledge classification and storing have been addressed in GOVCO, while knowledge
identification and selection are yet to be addressed. This means that the development of
knowledge identification and selection contributes to address some of the recognised current
KM challenges in GOVCO.
164 Chapter 6 | Case Study Analysis: GOVCO
Knowledge transferring’s sub processes and practices in GOVCO 6.6.2
As discussed earlier, knowledge transferring is the second most frequently mentioned as well
as an important KM process in the GOVCO’s PMO. According to the research framework,
knowledge transferring comprises two sub processes: knowledge distribution & forwarding; and
sharing, as depicted in Table 6-16 (Nissen, et al. 2000). The research framework assumes that
technologies and systems play an important role in supporting knowledge distribution and
forwarding processes, while organisational employees have a significant impact on sharing
knowledge (Alavi and Leidner 2001; Landaeta 2008; Wiewiora, et al. 2009a). As it can be
found in Table 6-16, there are numbers of practices for each sub-process by which knowledge
transfer is supported. For instance email, chat, and phone are examples of distributing
knowledge practices, while training, seminar, and mentoring are employed to share project
knowledge.
Table 6-16 Knowledge transferring sub processes in GOVCO (developed for this research)
K. Transferring Sub Processes
Practices for Knowledge Transferring
Associated Challenges Current Status
Knowledge Distribution and
forwarding
• Project bulletin and reports
• Communication channels
• Knowledge list
• Video and Tele Conference meeting
• Yellow page • Intranet • Data base
1,2, and 3
Some of the practices needs to be improved such as yellow pages,
intranet, and knowledge list
Knowledge Sharing
• Discussion forums
• Formal and informal events
• Mentoring • Training 2
Majority of practices have been developed
and are being conducted
As discussed earlier, the research findings explored that formal and informal events are the
most frequently mentioned practices for facilitating knowledge transferring, and respectively
communication channel and training are the second and third most frequent KM practices for
knowledge transferring. This means that, from GOVCO’s employees’ perspective, knowledge
sharing is stronger than knowledge forwarding. In other words, human factors play a better role
in transferring project knowledge, in comparison to technology and systems. Therefore,
GOVCO’s PMO should develop an appropriate system in order to improve the quality of
knowledge distribution and forwarding, and ultimately knowledge transferring.
On the other hand, according to the research findings, there are three KM practices:
knowledge list; knowledge directories; and video and tele conference, which are yet to be
addressed in GOVCO’s PMO. As could be inferred, these three KM practices are part of
knowledge distribution and forwarding sub-process, as depicted at Table 6-16. In other words,
GOVCO’s PMO could develop knowledge transferring through addressing the mentioned
practices. In addition, further analysis revealed that the unaddressed KM practices have created
some challenges such as the issue of finding the right person or information. As shown in Table
6-16, the relations between KM challenges and knowledge transferring sub-processes have been
Chapter 6 Case Study Analysis: GOVCO 165
illustrated. These findings accurately address the required actions to tackle the current KM
challenges in the GOVCO’s PMO.
All-in-all, knowledge transferring in GOVCO’s PMO is the second most frequent KM
process and it is supported through two KM sub-processes: knowledge distribution &
forwarding; and sharing. According to the research findings, current KM practices mainly
support knowledge sharing, while knowledge distribution needs to be appropriately improved
through developing some practices, such as knowledge lists and knowledge directories. In
addition, GOVCO needs to develop numbers of systems and technology to address some of the
existing concerns, such as locating the right person. In other words, knowledge transferring, as
the second most important KM process in GOVCO, should be improved by addressing the
mentioned challenges and KM practices.
Knowledge creation’s sub processes and practices in GOVCO 6.6.3
As discussed earlier, “Knowledge Creation” is the third most important KM process in
GOVCO’s PMO. According to Nonaka and Takeuchi (1995) knowledge is created through four
processes: Socialisation, Externalisation; Combination; and Internalisation, (SECI), which are
depicted in Figure 6-14. The SECI model was adopted in the research framework by which
knowledge creation has been classified to four KM sub-processes and their associated KM
practices, as presented in Table 6-17. The research findings revealed that there are limited
practices to support knowledge creation at GOVCO’s PMO, in which only 14 percent of the
coded comments have mentioned this KM process.
According to the research framework, Socialisation is the process of creating tacit
knowledge through various types of communications (Nonaka and Teece 2001) in which it is
facilitated through some practices such as formal and informal events, and community of
practice, as shown in Table 6-17. Hoegl and Schulze (2005) discuss that informal events are the
best practices for supporting socialisation by which tacit knowledge is discussed and sometimes
transferred among individuals. The research findings revealed that both community of practices
and formal and informal events are the most frequent KM practices to support knowledge
creation through socialisation. In other words, GOVCO’s PMO facilitates the majority of
socialisation KM practices.
Table 6-17 Knowledge creation sub procesess in GOVCO (developed for this research)
K. Creation Sub Processes
Practices for Knowledge Creation Comments
Socialisation • Formal and informal event
• Workshops & seminar • Community of practices
This is the most satisfactory practices among other
creation practices
Externalisation
• Workshops & seminar • Deductive & Inductive thinking
• Experts system • Experience Report • Community of practices
Except workshop, other practices are yet to be
addressed
166 Chapter 6 | Case Study Analysis: GOVCO
Combination
• Community of practices (COP) • Best Practice Cases (BPC)
• Knowledge Broker • Data mining • Documentation search
Except COP and PBC, other practices are yet to be
addressed
Internalisation • Research services • Simulation
• Experimentation All practices are yet to be addressed
Externalisation is the process which aims to transform tacit to explicit knowledge (Nonaka
and Teece 2001). According to the research framework, there are numbers of practices that
could be used to support externalisation, which are illustrated in Table 6-17. The research
findings show that only a few of them are facilitated, to some extent, such as workshops,
seminars and a limited practice of deductive and inductive thinking. In other words, the majority
of KM practices to manage externalisation are yet to be addressed in GOVCO’s PMO. This
means that transformation of tacit knowledge to explicit knowledge is a considerable challenge
in the GOVCO in which employees keep significant amounts of tacit knowledge with them.
These findings indicate that if the PMO aims to get to the next level of maturity through
improving its KM system, externalisation is an important process to prevent knowledge
leakiness in the projects.
The processes of transforming the explicit knowledge to more complicated explicit
knowledge is called combination (Nonaka and Teece 2001), and it is facilitated by numbers of
practices, as shown at Table 6-17. According to the research framework, the process of
combination is supported when there is a system in place for developing current manuals,
instructions, procedures, methodologies and as such (Alavi and Leidner 1999; Nonaka 1994).
This development happens through adding the individual input to current documents. The
research findings show that some KM practices are in place to support the combination process,
such as community of practices, best practices, and knowledge broker. However, other practices
such as documentation search and data mining are yet to be addressed. In addition, despite the
existence of some practices to facilitate combination, they need to be developed to satisfy
knowledge creation process. In other words, the combination process does not significantly
contribute to knowledge creation in GOVCO’s PMO.
According to Nonaka (1994) Internalisation is the process of knowledge creation by which
new tacit knowledge is created through existing explicit knowledge. There are numbers of
practices such as research services, simulation, and experimentation to facilitate knowledge
creation through internalisation, as depicted in Table 6-17. During both the direct observation
process, and also interview, analysis of the limited KM practices recognised support for the
internalisation process. This means that internalisation is the only sub-process in GOVCO’s
PMO in which limited evidence was found to be supported. As discussed earlier, GOVCO’s
PMO has been designed to be a centre of excellence, therefore the quality of project activities is
the most important responsibility for PMO (Walker and Christenson 2005). This means that
Chapter 6 Case Study Analysis: GOVCO 167
knowledge creation is not included in the first priority of GOVCO’s PMO. Consequently, some
practices, such as research services and simulation, might be addressed in higher level of
maturity.
Tacit Knowledge TO Explicit Knowledge
Tacit Knowledge
From
Socialisation (has been addressed in
GOVCO)
Externalisation (yet to be properly addressed)
Explicit Knowledge
Internalisation (yet to be properly
addressed)
Combination (yet to be properly addressed)
Figure 6-14 The SECI model in GOVCO’s PMO (Nonaka and Teece 2001)
In summary, knowledge creation is the third most important KM process in GOVCO.
According to the research findings, only one-out-of four knowledge creation sub-processes
(SECI) has been addressed, i.e. Socialisation. This means that current KM practices need to be
improved to address three sub-processes: Combination, Externalisation, and Internalisation.
According to Nonaka (2001), the SECI model follows a spiral method in which all four sub-
processes should be interconnected, as illustrated at Figure 6-14. This means that the process of
knowledge creation is fully supported when all four sub-processes are being appropriately
utilised. As depicted in Figure 6-14, three-out-of-four knowledge creation wings, Combination,
Externalisation, and Internalisation, are yet to be addressed in GOVCO’s PMO. In other words,
the SECI model does not completely work in the GOVCO’s PMO and it needs to be
significantly improved through addressing numbers of mentioned KM practices.
Knowledge reusing’s sub processes and practices in GOVCO 6.6.4
As discussed earlier, knowledge reusing is the least important KM process in GOVCO, in
which less than two percent of the coded comments support this KM process. According to the
research framework, knowledge reusing comprises three sub-processes, Adapting, Applying,
and Integrating, as depicted in Table 6-18 (Lytras and Pouloudi 2003; Nissen, et al. 2000). In
addition, in the research framework, knowledge reusing has strong correlation with knowledge
capturing and transferring (Owen and Burstein 2005). According to the research findings,
GOVCO’s participants believe that the current practices are not strong enough to support
knowledge reusing. This means that the three mentioned sub-processes of knowledge reusing
should be appropriately developed through addressing associated KM practices.
Table 6-18 Knowledge reusing sub-processes in GOVCO (developed for this research)
K. Reusing Sub Processes
Practices for Knowledge Reusing Comments
Knowledge Adapting
• Electronic notice board • Documents management system (DMS) • Intranet • Data base
• Yellow page • Knowledge detection tools • Formal or informal events
Majority of the mentioned KM
practices are yet to be addressed for knowledge
reusing
168 Chapter 6 | Case Study Analysis: GOVCO
Knowledge Applying • Expert systems • DMS
purposes
Knowledge Integrating • Knowledge map • Data mining
In summary, knowledge reusing GOVCO has been ranked as the lowest KM process in
terms of its importance. Also, there are limited KM practices in place to facilitate any of the
three mentioned sub-processes in the PMO. According to the research framework, knowledge
reusing is improved through developing knowledge capturing and transferring. This means that
GOVCO’s PMO should address the recognised issues of knowledge capturing and transferring,
as their first priority, which ultimately contributes to improving knowledge reusing.
CONCLUSION 6.7
In this chapter it has been planned to answer the first and second research questions (RQ1.
How are KM practices and processes employed in the PMOs, and RQ2. How do KM practices
contribute to improve maturity level of the PMO), and their associated sub-questions (what are
the current challenges of the PMO from a KM perspective, What types of knowledge are
required at each of following project phases, What kinds of KM practices are utilised in each
maturity level of PMO, What is the importance of knowledge processes at each phase of project,
How PMO should contribute for managing the project Knowledge). In the previous chapter,
these questions have been extensively answered to achieve the research objectives. The same
process has been followed in GOVCO, and ultimately the research questions have been
answered. In this section, a summary of the research findings has been discussed as follows.
The research findings revealed that GOVCO is faced with the four following challenges
from a KM perceptive: Lack of integration among current processes and systems, issue of
locating and accessing right information and/or right expert, Lack of KM practices and KM
processes during project life cycle, Issue of appropriate access to the existing systems. This
means that the main focus of PMO should be on addressing these issues and underpinning them.
According to the research findings, the following ranking represents the importance of the
required types of knowledge, from participants’ points-of-view: 1) Project Management
Knowledge, 2) Knowledge about Procedures, 3) Knowledge about Clients, 4) Technical
Knowledge, 5) Knowledge of who knows what, 6) Costing Knowledge, 7) Legal and statutory
Knowledge, and 8) Knowledge about suppliers. This could be a significant indication for
GOVCO, or PMOs with similar maturity level, to prioritise the importance of their required
knowledge.
Furthermore, both interviews and survey-questionnaire outcomes, consistently, have
determined the following order to present the importance of KM processes: 1) Knowledge
Capturing 2) Knowledge Transferring 3) Knowledge Creation, and 4) Knowledge Reusing.
Chapter 6 Case Study Analysis: GOVCO 169
These findings explain that knowledge capturing and transferring are the most important KM
practices, while creation and reusing are not as important as the other two. In addition, in similar
previous case study outcomes, informal and formal event is the most utilised KM practice.
As discussed in the last section, i.e. 6.6, KM challenges and KM processes have been
discussed alongside KM sub processes. The findings at that section shall contribute to prioritise
the development of KM processes, sub-processes and practices. In other words, it addresses
appropriate KM practices and processes with regards to their associated challenges and issues.
This will assist PMOs to improve the quality of project knowledge management, and
consequently the maturity level of the PMO.
In the end, the following have been summarised in GOVCO’s PMO, with second level of
maturity:
• KM awareness have been raised at both senior management and employee levels,
• The main focus should be on the development of knowledge capturing through
addressing the recognised challenges,
• Knowledge transferring is the second priority, which needs to be addressed by
providing adequate practices,
• Knowledge creation has the third level importance in which basic KM practices should
be put in place,
• Since the PMO at this level has one or more PM standards, it is recommended to
integrate both PM and KM practice to prepare for the next level of maturity,
• PMO should provide proper practices to assist project team members with assessing the
three most important types of knowledge:
o Knowledge of project management through providing PM methodology,
o Knowledge about clients through developing proper KM practices, and
o Knowledge of who knows what through addressing appropriate KM practices
Chapter 7 | Case Study Analysis: MINCO 171
Chapter 7
CASE STUDY ANALYSIS: MINCO
INTRODUCTION 7.1
In the previous chapter, the second case study, i.e. GOVCO, was investigated through
following both research framework (Chapter 3) and methodology (Chapter 4). In this chapter,
similar procedures will be followed to investigate a third case study, i.e. MINCO, from a KM
point of view. To do so, MINCO’s PMO will be explored through discussing the two first
research questions (RQ1. How are KM practices and processes employed in the PMOs, and
RQ2. How do KM practices contribute to improve the maturity level of the PMO?). First, the
organisation’s background will be explained, followed by data collection procedures. Second,
the PMO’s maturity level will be discussed alongside the current PM systems. Third, the data
analysis will be undertaken to discuss the current status of MINCO’s PMO from a KM
perspective. Finally, concluding remarks and the research findings will be presented
accordingly.
MINCO’S BACKGROUND 7.2
The third case is a leading global resource company which produces major commodities,
including coal, iron ore, silver and uranium. The corporate strategy is based on owning and
operating assets diversified by commodity, geography and market. As shown in Figure 7-1, this
case comprises the numbers of divisions to manage various assets. For this study, the coal
mining asset met the research criteria (explained in Chapter 4) and it was selected as the third
case study, so it will be called MINCO herein after.
Figure 7-1 Snapshot of MINCO’s structure ((extracted from MINCO’s organisational chart)
MINCO, with more than 15 000 employees, is responsible and accountable to produce,
operate and market coal, locally and internationally. To do so, MINCO undertakes a plethora of
projects and programs to both sustain the current production and operation, and develop new
coal mines as well as markets. In order to manage organisational projects, a department was
GLobal Enterprise
Other Asset Presidents Mining Asset President (MINCO)
Project Group Department
172 Chapter 7 | Case Study Analysis: MINCO
developed about five years ago which is called “Project group”, as depicted at Figure 7-1. This
department plays a key role in undertaking, supporting, and overseeing MINCO’s projects. The
functionality of the MINCO’s Project group department is similar to a classic PMO, therefore it
will be called PMO in this report.
Projects are an important part of MINCO’s daily activities for not only maintaining the
current operations in different coal mines, but also exploring new coal resources for future
purposes. In fact, more than fifty percent of MINCO’s operations deal with various types of
projects to achieve the organisation’s mission, i.e. to be the best coal mining company in the
world. MINCO undertakes various types of projects from construction, building and road, to
drilling and explorations. A well-established PM system is required to centrally facilitate and
support all organisational projects, for delivering quality outcomes. MINCO’s PMO is the major
body to develop the mentioned system in order to manage, oversee, and control MINCO’s
projects from initiation to closing phase. In other words, PMO is responsible to assist projects
and project managers (PMs) by providing appropriate processes, procedures, systems, and
advice in order to improve the quality of project management, and ultimately project success.
The role of MINCO’s PMO is to provide appropriate direction to PMs, and to contribute to
projects by offering technical advice during project implementation; ultimately PMs are
responsible for project success or failure. In other words, PMO has been designed to be a strong
arm for PMs in order to facilitate management of the project from initial to close out phases. In
addition, PMO offers numbers of services such as training, consultancy, controlling, auditing,
risk management, and other administration services to PMs to ensure that they have adequate
resources to manage their projects.
This chapter aims to investigate current PM activities in MINCO’s PMO to discuss how
project knowledge is managed. Similar to previous chapters, the research framework and
methodology have been employed to identify the processes and outcomes of this investigation.
To do so, firstly the research protocol and data collection methods have been used to gather the
required information. In the next section, the data collection processes were discussed
accordingly.
DATA COLLECTION PROCEDURES 7.3
Similar to other cases, the research methodology and the case study protocol were followed
to gather quality information from MINCO, getting assistance from a liaison person. In order to
conduct the data collection methods, a schedule was prepared to organise the required activities,
as shown in Table 7-1 and Table 7-2. In total, six interviews were conducted with MINCO’s
senior manager, PMO knowledge manager, a program manager, two project managers, and a
project planner. Approximately, each interview took about 75 minutes in which was included
the undertaking a questionnaire survey and interview questions. In some cases, interviews were
Chapter 7 | Case Study Analysis: MINCO 173
conducted two times as the researcher needed more clarification. For confidentiality purposes,
interviewees’ names were replaced by a selected code as can be seen in the following Table.
Table 7-1 Interviewees’ list and schedule in MINCO (developed for this research)
Interviewee Position Location 1st interview 2nd interview
In.Mc.1 MINCO senior Manager 19/07/2013 (face to face)
25/07/2013 (face to face)
In.Mc.2 knowledge manager 19/07/2013 (face to face)
26/07/2013 (face to face)
In.Mc.3 PMO Planner 23/07/2013 (Face to face)
31/07/2013 (face to face)
In.Mc.4 Program Manager 23/07/2013 (face to face)
31/07/2013 (face to face)
In.Mc.5 Project Manager 25/07/2013 (face to face)
3/08/2013 (face to face)
In.Mc.6 Project Manager 25/07/2013 (face to face)
3/08/2013 (face to face)
The data collection activities, specifically interviews, were undertaken in MINCO’s office in
Brisbane, from mid-July 2013 to late August 2013. All interviews were electronically recorded
and more than 110 pages of the transcribed interviews were provided to be used in Nvivo. Also,
four days were spent to directly observe the current PM activities in MINCO. In addition, it
took three days to investigate the utilised software and systems in the MINCO’s PMO, as
depicted in Table 7-2. The document analysis stage was conducted for more than 4 months in
conjunction with data analysis.
Table 7-2 The Data collection methods (developed for this research)
Data Collection Method Location Facilitator Date
Interviews and Questionnaires MINCO office Researcher
Mentioned in Table 7-1
Documents Review MINCO office and QUT
Researcher and MINCO’s liaison person
10/07/2013 till 31/11/2013
Direct Observation MINCO office Researcher and MINCO’s liaison person
16/08/2013 to 19/08/2013
After the data collection stage, the data analysis stage was conducted through: 1) assessing
the maturity level of project management by using collected data from questionnaires, 2)
interviews were conducted, transcribed and then coded in Nvivo, and 3) the second
questionnaire was analysed accordingly. In the next section, data analysis will be discussed to
gain insightful information about the selected case study.
DATA ANALYSIS 7.4
This section has been provided to present the data analysis activities and outcomes. The
research methodology and framework were employed to manage the data analysis process.
According to the research methodology, the maturity level of MINCO’s PMO should be
assessed, in the first stage of analysis. In the next step, MINCO’s PMO challenges were
174 Chapter 7 | Case Study Analysis: MINCO
discussed from a KM point-of-view, followed by analysing the required types of knowledge
during the project lifecycle. At the end, the importance of four KM processes: Creation,
Capturing, Transferring, and Reusing were analysed, and then examined against the explored
KM challenges to discuss the relation between KM process and KM issues in the MINCO’s
PMO. In fact, the first and second research questions (RQ1- How are KM practices and processes
employed in the PMOs, RQ2) How do KM practices contribute to improve maturity level of the
PMO) will be answered at the end of the analysis section.
MINCO’s PMO maturity level 7.4.1
The similar process for the other two cases was followed, in this case to determine the
PMO’s maturity level from a KM perspective, as discussed in section 5.5.1. From project
knowledge perspectives, the average maturity level is 3.18 out of 5, which technically means
that the PMO has the third level of maturity, as depicted in Table 7-3 and Figure 7-2. The data
analysis shows that project risk, communication and cost management have been ranked as the
top three PM knowledge areas, while project procurement, quality and time management are not
as strong as the other six knowledge areas. This means respondents believe that current PM
practices need to be improved to strengthen project time, cost and procurements management.
Table 7-3 PMO’ ML from PM knowledge perspective (developed for this research)
PMBOK’s Knowledge area Maturity level (ML) Average ML
Project Scope management 3.00
3.18
Project Cost management 3.21
Project Time management 3.00
Human Resource management 3.07
Project Quality Management 2.93 Project Risk management 4.21
Project Communication management 3.29
Project Procurement management 2.79
Project Integration management 3.14
In addition, during the document analysis stage, numbers of practices have been recognised
which are designed to support risk and communication. This is consistent with the mentioned
findings, as it was found that, from participants’ points-of-view, project, project risk and
communication are appropriately addressed in MINCO. Also, during direct observation, a
robust Risk and Safety system was recognised which all employees are obliged to follow
accordingly. These outcomes indicate that MINCO’s PMO should be classified as a PMO with
third level of maturity, from PMBOK’s knowledge perspective (Desouza 2006; Kerzner 2005;
Project Management Institute 2008b).
Chapter 7 | Case Study Analysis: MINCO 175
Figure 7-2 ML of MINCO’s PMO’s from knowledge areas perceptive (developed for this study)
From a project lifecycle point-of-view, the maturity level of MINCO’s PMO was determined
as 3.02 out of five, as shown in Table 7-4. This means that PMO’s maturity level has obtained
the third level out of five possible levels of maturity (Kerzner 2005; Kerzner 2013). As shown
in Table 7-4, the planning and execution phase has gained a better maturity level, in comparison
to initiation and closing phases. This means that from participants’ points-of-view the current
PM practices to facilitate planning and execution phases are stronger than closing and initiation
practices. In order to obtain more information in this regard, further investigation were
conducted by looking at interviews and direct observation data. Interestingly, it was realised that
MINCO’s employees believe that inadequate information is obtained at initiation phase, so they
expect to be actively involved at this phase, as In.Mc.3 comments:”…the knowledge transfer
form initiation is not enough to get accurate information….”.
Table 7-4 MINCO’s PMO ML from project lifecycle perspective (developed for this research) Project Phases Maturity level(ML) Average ML
Initiation 2.07
3.02 Planning 3.93
Execution and monitoring 3.29 Closing 2.79
Furthermore, analysis of data indicates that, in general, participants believe MINCO’s PMO
supports projects in a satisfactory manner; they illustrate followings perceptions:
“…it’s again I’d probably say [level] four, again it’s fairly well developed and they’ve
got the frameworks there…”, quoted by In.Mc.4.
“…PMO should be going on without basing on people but we are really based on
people skills still. So let’s say 4 because there is more to go…”
“…I’d probably put it at mid-range, I still think there’s a lot to learn and a lot to
go…”
3.00 3.21
3.00
3.07
2.93
4.21
3.29
2.79
3.14
Project Scope
Project Cost
Project Time
HRmanagement
Project QualityProject Risk
ProjectCommunicatio
n
ProjectProcurement
ProjectIntegration
ML OL
176 Chapter 7 | Case Study Analysis: MINCO
Figure 7-3 MINCO’s Maturity level from project lifecycle perceptive (developed for this research)
The maturity level of MINCO’s PMO has been graphically presented from both knowledge
and project lifecycle perspectives, in which both indicate the third level of maturity, as shown at
Figure 7-2 and Figure 7-3. This means that MINCO’s PMO has significant numbers of PM
practices to facilitate project management (Kerzner 2005; Kerzner 2013). In a consistent
manner, during interview data analysis, participants responded that MINCO’s PMO is mature
enough to contribute to project success. In addition, during direct observation, numbers of
systems and procedures were recognised that are appropriately used in project lifecycle. An
internal assessment, which has been done by the PMO, shows the maturity of 3.5 out of five,
which is in line with the research findings.
The third level of maturity for MINCO’s PMO means that there are adequate tools and
systems in place to support MINCO’s projects (Kerzner 2005). According to the research
framework, a third maturity level is called “Singular methodology” (Kerzner 2013). This means
that there is a developed- comprehensive PM methodology in place for project management
(Kerzner 2013). In other words, at the third level of maturity it is assumed that PMO has
developed a PM standard to address both basic, and some of the advanced PM practices. In fact,
in a PMO with third level of maturity : 1) all utilised PM practices have been integrated at one
PM standard, 2) all various PM methodologies have been combined in one organisational-wide
PM methodology, and 3) Project team members actively adhere to the developed PM standard
(Kerzner 2005). In general, PMO with third level of maturity should have following
characteristics (Kerzner 2005; Kerzner 2013):
• Organisation has totally committed to the concept of project management,
• The current project management processes and procedures have been integrated into a
single methodology with demonstrated successful execution,
• There is corporate-wide culture that supports informal project management and
multiple-boss reporting, and
2.07
3.93
3.29
2.79
Initiation
Planning
Execution&monitori
Closing
ML OL
Chapter 7 | Case Study Analysis: MINCO 177
• PMO has developed a sense of shared responsibility and accountability for the
principles of project management.
Since previous findings indicate that MINCO’s PMO has the third level of maturity,
therefore, these characteristics should be consistent with the current status of PM in MINCO. In
order to investigate the consistency between the research findings and framework, the collected
data from interviews and documents were analysed to examine data against the above
mentioned characteristics.
In the first step, the MINCO’s PM methodology was analysed against the research
framework. As discussed, in a PMO with the third maturity level, one singular PM standard
should be utilised across the organisations. The direct observation and document analysis
confirms the existence of a comprehensive PM standard in MINCO. This PM framework has
been accepted as the main methodology to be followed during project life cycle and it is
strongly supported by MINCO’s senior managers. This PM framework will be discussed further
in section 7.4.1.1.
Furthermore, appropriate training, workshop and an induction program are provided for new
employees or junior staff to make them familiar with the current culture and develop their
knowledge of project management. In addition, there are numbers of practices and processes, in
line with PM standards, to improve the project success rate through improving their knowledge.
For instance there is a practice which is called “safety share”, by which at every weekly meeting
all participants should discuss a risk that they have faced, and then discuss about both an
appropriate mitigation method and a lesson learned. This means that the current culture of
project management contributes to quality of project outcomes but it does not mean that it is
perfect.
From the participants’ points-of-view the current project management framework is robust
enough to assist project managers (PMs) in conducting their assigned activities. In addition, all
respondents mentioned that they are quite familiar with the existing PM standard and they have
been trained appropriately. Also, the research findings revealed the majority of PMs are familiar
with the current PM standards such as PMBOK and PRINCE2 which made them to criticise the
current PM methodology. This means that in the current culture of PM there is a dynamic
approach to improve the quality of project management environment (Project Management
Institute 2013). Moreover, it was found that there is a good understanding of matrix
organisations in MINCO, in which one employee could have more than one boss (Project
Management Institute 2013). This means that the multiple-boss reporting, as another
characteristic of third level of maturity, has been identified in MINCO’s PMO.
178 Chapter 7 | Case Study Analysis: MINCO
As Table 7-5 depicts, two main criteria of PMO with third level of maturity, i.e. PM
methodology and culture, have been selected to present some of participants’ comments in this
regard.
In order to examine other criteria of PMO with third level of maturity, such as a sense of
sharing the responsibility and accountability, direct observation data was analysed
accordingly. According to the current MINCO’s employee assessment procedure, one of the
criteria to assess human resource performance is the employee’s contribution to his/her fellow
team members. This criterion has developed a culture by which responsibility of team members
is not limited to their formal job, but it is linked to project success. Therefore, team members
have a sense of shared responsibility and accountability, as required for the third level of
maturity.
Table 7-5 Participants’ quotes in regards to MINCO’s PMO matuirty (developed for this research) Subject Associated participants’ comments
PM Methodology
In.Mc.2: “…Our project managers are all trained on the PM courses…so that’s yeah your PMBOK…”
In.Mc.3: “…Well I mean [MINCO] has got their project development manual that basically sets out how you manage your project. So that’s the framework for it…”
In.Mc.1: “…there is a defined delivery project management framework that’s defined to manage all project ….”, “…what I mean is like it’s been defined, it’s got the PMBOK elements in it.
The PMBOK elements underpin the project management framework…”
Culture of Project
Management
In.Mc.2: “…let’s say we have a building that has a non-compliant fire system in it because it’s been expanded a lot. So we have to put in, we have to expand the fire system in the project, in
the site. So that becomes a risk reduction project…” In.Mc.4: “…So we go and visit the project every month and check its progress, check its
deliverable quality, are they completing their registers, are they executing the plan? Are they executing the contract...”
In.Mc.5: “…So we rely quite heavily on our tool kit for that. So we have a, there’s something that one of our principals in the assurance team…”, “…Well the PMO provides all the resources so we’ve got…so when you go from selection to definition it’s…so identification and selection
is run by the development group within the projects so they do all the studies…”
In summary, the collected data from different sources are consistent in terms of maturity
levels of MINCO’s PMO (Kerzner 2013; Project Management Institute 2013). This means that
triangulation of various data sources contributes to the quality of research findings (Yin 2009).
In other words, the maturity level of MINCO’s PMO was assessed through not only survey-
questionnaire, but also, analysing the collected data, and both consistently provide similar
outcomes. During the process of document analysis, a PM framework was recognised in
MINCO. In the next section, this framework has been analysed in order to shed more light on
the current PM methodology in MINCO.
Project management methodology in MINCO 7.4.1.1
According to the research findings, MINCO’s PM standard has been developed through
mainly employing PMBOK, and comprises four phases: 1) Identification, 2) Selection &
Definition, 3) Execution, and 4) Operation, as shown in Figure 7-4. Each phase has numbers of
processes and procedures to facilitate the associated activities, as depicted in Figure 7-5.
Chapter 7 | Case Study Analysis: MINCO 179
In the Identification phase, high level activities and feasibility studies should be undertaken
to prepare accurate information. In addition, the project opportunity and its alignment with
organisational objectives should be defined at this phase. Also, it should be justified as to how
this opportunity will benefit whole organisation. This is similar to definition of “business case”
in the PMBOK (Project Management Institute 2013). In fact, significant knowledge is created in
this phase through applying the recommended processes and practices in order to provide
reliable input for the next phase.
Figure 7-4 MINCO's project life cycle (adopted from MINCO’s PM framework)
If the green light is given by MINCO’s senior managers then the next phase, i.e. Selection
and definition phase, is conducted to define and provide project scope, schedule, budget and
deliverables, as shown at Figure 7-4. In fact, this phase is similar to the planning phase in the
PMBOK (Project Management Institute, 2012). As presented at Figure 7-5, in order to manage
the selection phase, there are numbers of processes and procedures in place such as stakeholder
management plan, risk management plan. According to the MINCO’s PM standard at the end of
this phase, the provided plans should be integrated in one plan, which is called a project
management plan.
180 Chapter 7 | Case Study Analysis: MINCO
Figure 7-5 Selection &definition phase (adopted from MINCO’s PM framework)
In the Execution phase, the project management plans should be followed to ultimately
deliver project predefined outcomes and deliverables. According to MINCO’s PM standard,
numbers of activities such as monitoring and control, risk management, change management,
and quality control should be managed during the execution phase. Also, numbers of documents
such as project progress and costing report should be provided for associated stakeholders. This
phase finishes when the project deliverables have been submitted and accepted, so project
stakeholders are satisfied to proceed to the closing phase.
After delivering project outcomes, the Operation phase is commenced to integrate those
outcomes in MINCO’s business. In this phase, there is an assumption in which all undertaken
projects in MINCO should add some value to current business performance. In other words,
MINCO does not aim to undertake any client projects. In this phase, project close out
documents should be provided, as well as manuals and lessons learned. Also, training plan,
operational support documents, and post project review should be managed at this phase. These
processes have been clearly defined in the PM standard and their associated applications were
advised accordingly, which make it user friendly.
In summary, the current PM framework has been developed in the last 10 years, and now
participants believe that it is mature enough to be followed by project managers. In addition, it
is supported by numbers of processes, procedures and systems such as risk management tools, a
close out process and Primavera. These processes and tools are reasonably integrated to
contribute to the project success. On the other hand this PM standard is widely accepted among
MINCO’s employees and there is strong support from senior managers to push everybody to
follow this comprehensive PM standard. This framework has significantly contributed to
support the culture of PM in MINCO. According to the current literature, PM systems and tools
Chapter 7 | Case Study Analysis: MINCO 181
are important factors to facilitate PM alongside the PM methodology. In the next section, the
current PM systems and applications will be discussed to gain insights in this regard.
Project management systems and tools in MINCO 7.4.1.2
The performance of the project management environment is dependent on the current
systems, tools and processes (Project Management Institute 2013). According to the collected
data from interviews, document analysis, and direct observation, MINCO has developed
numbers of tools as systems to assist project stakeholders with managing their activities. For
instance, more than ninety processes and procedures, have been recognised in MINCO, such
as risk management, safety management, quality management and stakeholder management. In
addition, there are some tools in place such as Primavera, MS project, and other similar
applications, in order to facilitate PM in MINCO.
The research findings revealed that there numbers of systems and tools in MINCO to
facilitate project management, as shown in Table 7-6. In fact, MINCO has a collaborated
information technology system, by which the current applications can be accessed through one
gate around the globe. This means that MINCO’s employees could have access to their required
applications through an assigned laptop, regardless of their location. The MINCO’s applications
have been designed for various purposes, therefore, only those applications that are directly
utilised by PMO were discussed in this report. In total, five applications have been recognised,
which are used to manage projects in MINCO: SAP; Primavera; Intranet; Hummingbird; and;
Galileo.
Table 7-6 The current systems and tools in MINCO’s PMO (developed for this research)
Application Propose of use
SAP To integrate cost and procurement across the MINCO
Primavera To plan and control all projects in one system
Intranet To provide access to different applications used by employees across the globe
Hummingbird To capture and transfer project information
Galileo To save project information from past and have a database of projects history
SAP is a total system in MINCO which is used for cost and procurement purposes. In other
words, project data such as cost, invoices, claims, and contracts are saved and populated in SAP
software. SAP is an organisation-wide solution to capture and somehow transfer the project
knowledge, however, there are some issues with SAP from a PM point-of-view, which are yet
to be addressed. In fact, SAP is not an appropriate software for managing projects and it needs
to be integrated with other software to directly contribute to project success (Crawford 2012).
182 Chapter 7 | Case Study Analysis: MINCO
This gap was found by MINCO’s experts, so the PMO offers some other software, such as
Primavera and Ms Project, in conjunction with SAP for PM purposes.
Primavera is one of the popular PM softwares which is widely used by enterprises to
manage organisational projects (Tang, et al. 2010). This software contributes to project time,
cost and scope management, so the other PM knowledge area such as risk and quality
management cannot be directly managed by Primavera (Tang, et al. 2010). MINCO’s PMO
employs this software to plan and control the existing projects and also to provide appropriate
project progress reports. The central database of Primavera significantly contributes to access
the required information in order to both assess project progress and audit the project
deliverables.
A well-established Intranet is another organisational-wide application, which gives
employees appropriate access to their appointed software. Also, an intranet assists project
stakeholders with accessing different forms, procedures and manuals, such as leave request
form, and project report procedure. During the direct observation, it was revealed that the
current intranet is, also, used as the main gateway to update project databases. In addition,
access to organisational mailbox and appointed folders for each group or division has been
facilitated through the intranet. In fact, the current intranet is a well-structured system by which
the required accesses to various types of applications and databases are authenticated based on
the employees’ role and responsibilities. For instance, access to current PM systems such as
Galileo and Hummingbird, are also managed through the current intranet.
MINCO’s employees are advised to upload all their work related files, presentations, reports,
and manuals into Hummingbird. In other words, all of an organisation’s documents should be
saved and recorded in this database. This means that Hummingbird is one of the major
applications for knowledge capturing and transferring in MINCO. Hummingbird is accepted
among employees and they try to use this application as the main project knowledge repository,
as one interviewee comments:”…within [MINCO] the key knowledge management source or
data base for managing knowledge is Hummingbird…”, quoted by In.Mc.2. The further
investigation revealed that MINCO’s employees are frequently using this software due to its
availability across MINCO.
Galileo is another system in MINCO to record the project information. This system is
utilised to gather project history from the initiation, when an idea is developed, to the end, when
the project is finished. Clearly, Galileo is a system to capture project information for
transferring and reusing purposes. Participants believe that this system has a significant
influence on their works since it is helpful when they need to find information about similar
projects for developing a new idea. Following are the respondents’ comments about Galileo:
Chapter 7 | Case Study Analysis: MINCO 183
“…So a project idea is entered into our reporting system Galileo from where it’s been
adopted and built upon…”, quoted by In.Mc.4
“…No Galileo is to capture all the project in the Galileo it’s sort of a report that you can
run monthly, daily and see which projects have how much actual detail what is the forecast
putting in place…”, quoted by In.Mc.3
In summary, the research findings revealed that current systems have significant
contributions to managing projects in MINCO. For instance SAP is used for project costing and
invoicing purposes and Intranet provides required access to various organisational resources. In
addition, Primavera is used for collaborating project activities and undertaking project control,
and Galileo facilitates the access of project information and also previous project experiences.
However, there are some issues that are yet to be addressed if MINCO’s senior manager aims to
improve the quality of their PM services. For instance, integration between SAP and PM
application needs to be addressed in order to improve collaboration among the current systems.
Having said that, this research aims to focus on the PMO from a KM point-of-view, therefore,
in this section the major issues of MINCO’s PMO from a KM perspective will be discussed
accordingly.
Knowledge Management challenges in MINCO 7.4.1.3
The interview data was used as the main source to recognise issues of MINCO’s PMO from
a KM perspective. In addition, the research framework was followed in which interviews’
transcriptions were uploaded to the Nvivo, as data analysis software. Then the process of
coding, both open coding and axial coding, was managed, as it has been advised by similar
qualitative research (Charmaz 2014; Corbin and Strauss 2008; Wiewiora, et al. 2010). In the
first stage of the open coding process, more than 64 nodes were developed in Nvivo. These
codes or comments have directly or indirectly mentioned the current challenges from a KM
point-of-view. Following are some of the examples of the coded comments:
“…Ideally it shouldn’t be like that but we need some knowledge in that part because
those people are gone and before they …nobody has thought to put some lessons learned
or something like that into place…”, quoted by In.Mc.2.
“…So getting that knowledge passed over from one study manager to the next one is
very difficult unless people actually file it in the correct locations…”, quoted by In.Mc.4.
“…A lot of this information is locked away and people keep it on their hard drives or
they don’t keep them in shared folders and so you can’t access it…” quoted by In.Mc.1.
The similar process of previous cases, was followed to determine the current challenges of
MINCO from a KM point-of-view and eventually the following categories of KM issues have
been developed:
184 Chapter 7 | Case Study Analysis: MINCO
1) Inadequate practices to support knowledge transferring process
2) Issues with current systems to fully support knowledge capturing process
3) Unsatisfactory practices to appropriately support knowledge reusing process, and
4) Lack of training for current systems and applications
Table 7-7 is an example to present how participants’ quotes were related to open codes, and
also, how axial codes were developed accordingly.
Chapter 7 | Case Study Analysis: MINCO 185
Table 7-7 Example of Axial and Open coding in MINCO’s PMO (developed for this study)
Axial coding Open coding Quote’s samples
Inadequate practices to support knowledge transferring process
Challenges of transferring knowledge form project stakeholder
“…Ideally it shouldn’t be like that but we need some knowledge in that part because those people are gone and before they …nobody has thought to put some lessons learned or something like that into place…”, quoted by In.Mc.2. “…So getting that knowledge passed over from one study manager to the next one is very difficult unless people
actually file it in the correct locations…”, quoted by In.Mc.4. “…A lot of this information is locked away and people keep it on their hard drives or they don’t keep them in shared
folders and so you can’t access it…” quoted by In.Mc.1. Better communication…earlier communication with the project manager and supervisor who are going to do the job,
quoted by In.Mc.3.
Issues of transferring knowledge from study managers at planning phase
Lack of transparency of the exciting information
Lack of practices to facilitate stakeholder communications
Issues with current systems to fully support
knowledge capturing process
Issues of capturing of lesson leaned “…And I guess one of the things that we’re looking at is hopefully there’s a risk management process might start capturing that so we can whilst we’re not involved we can access those lessons learned without imposing upon the
project progress…”, quoted by In.Mc.1 . “…That’s the problem in our process it’s not easy to find old projects and go in and create those documents…”, quoted
by In.Mc.3. “…I’m talking more about the capture and the storage, there’s a, it’s a broken step between capture and storage… So the
storage mechanisms or the story, there is no clear framework for rules on storage…”, quoted by In.Mc.2. “…Had the potential though to cost money, quite a lot of money because we didn’t investigate the risk controls
better…” , quoted by In.Mc.5.
Challenges of findings old process and information
Issues of storing knowledge
Issues of capturing risk management information
Unsatisfactory practices to appropriately support
knowledge reusing process, and
Lack of engagement of project manager at initiation stage
“…My personal opinion is your execution project managers and construction supervisors should be engaged earlier in the process…”, In.Mc.1.
“…And as far as reusing knowledge goes I mean it seems to me that it only really gets reused when you’ve got the same people there that actually created it in the first place…”, quoted by In.Mc.3.
“… Selection phase is about exploring options and alternatives and then coming up with the most preferred alternative. So that might be preferred based on previous projects…” , quoted by In.Mc.2
Issues of knowledge reusing is worse than other KM process
Lack of exploring options and choosing the preferred alternative
Lack of training for current systems and
applications
Training for current systems is not satisfactory “…I mean when I first started I got they say here you are, this is hummingbird this is (?) off you go. So the training side
is probably not there…”, quoted by In.Mc.5. “…So for example the manager, the business owner for this project changed three times in planning, we had three
different managers…”, quoted by In.Mc.3 “…They’ve got the documentation that says this is how you do things. The problem comes with people’s discipline in
actually following…”, quoted by In.Mc.2
Induction does not cover all applications
Lack of appropriate course for at the job trainings
Chapter 7 Case Study Analysis: MINCO 187
Figure 7-6 The current KM challenges in MINCO’s PMO (developed for this study)
In order to analyse the above mentioned challenges, the developed codes were employed,
alongside the research framework. In addition, the frequency of codes and comments was used
as the main criteria for this part of the investigation. As depicted in Figure 7-6, more than 49
percent of coded data has indicated the issue of knowledge transferring. This means that
participants believe that the current KM practices do not appropriately support the processes of
knowledge transferring during the project lifecycle. Further analysis revealed that the majority
of the recognised knowledge transferring issues occurs at Planning and Execution phase. For
instance, participants complained about poor knowledge transferring from the initiation phase,
as they believe that inadequate information is given to commence a planning phase.
“…So getting that knowledge passed over from one study manager to the next one is very
difficult unless people actually file it in the correct locations…”, quoted by In.Mc.5
In addition, respondents have mentioned some issues related to knowledge transferring in the
execution phase, such as lack of transparency and appropriate communication practices. This
means that the issue of knowledge transferring not only is the main concern for MINCO’s
employees, but also it is a significant challenge for the existing project, as could be inferred
from the following comments:
“…I’m not included in initiation phase. However, the knowledge transfer form initiation
is not enough for us to get accurate information form stakeholders…”, quoted by In.Mc.2
“…Lack of communication between different people who are doing the definition,
execution and studies…”, quoted by In.Mc.3
“…Stakeholders were changing all the time and one of the things that could have been
done better was stakeholder knowledge transfer…”, quoted by In.Mc.1
49%
32%
22%
7%
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Unsatisfactory practices to appropriately support Knowledge reusing process
Lack of trainings for current systems and applications
Issues with current systems to fully support knowledge capturing process
Inadequate practices to support knowledge transferring process
188 Chapter 7 | Case Study Analysis: MINCO
“… Transparency, better transparency, A lot of this information is locked away and
people keep it on their hard drives or they don’t keep them in shared folders and so you
can’t access it…”, quoted by In.Mc.5
The second most significant challenge is the current issues with existing systems for
capturing project knowledge. As can be found in Figure 7-6, more than 32 percent of the
recognised issues are associated with capturing knowledge. In order to pin down this issue,
further analysis was conducted, and eventually three sub-issues were recognised: knowledge
storage, lessons learnt and insufficient practices, especially in the closing phase. This means that
respondents believe the current practices can be improved to enhance the quality of knowledge
capturing at closing phase. Following are some of the concerns in this regard:
“…So we lose this big opportunity of gathering information progressively through a
project so we got involved up the front, we get involved sort of in the planning and at the
end. But that assumes the people at the end are actually providing us with knowledge that
will happen in the execution phase and that doesn’t tend to happen very well. So it’s that
capturing of the lessons learnt progressively that we miss it…”, quoted by In.Mc.1.
“…In the execution phase. And I guess one of the things that we’re looking at is
hopefully there’s a risk management process might start capturing that so we can whilst
we’re not involved we can access those lessons learned without imposing upon the project
progress. And that’s the hard part…”, quoted by In.Mc.2.
“…So the storage mechanisms or the story, there is no clear framework for rules on
storage…”, quoted by In.Mc.3.
According to the research framework, capturing project knowledge should be the most
important KM process at closing phase (Owen and Burstein 2005). On the other hand, the direct
observation revealed that despite the existence of some tools such as Hummingbird and Galileo,
these systems are yet to be integrated to appropriately address knowledge capturing and
transferring during the project lifecycle. In other words, integration among the current systems
is an issue which needs to be addressed by PMO.
Lack of training for current systems has been recognised as the third most frequent
challenge, with more than 22 percent of the obtained data. According to the research
framework, training has been classified as one of the practices for supporting knowledge
transferring. In other words, this issue is associated with issues of knowledge transferring but
because of its frequency, it has been classified as a main issue. According to the research
findings through collected data from direct observation and document analysis, numbers of
training courses are managed for MINCO’s employees. In addition, there is a comprehensive,
three day induction program in order to make new staff familiar with current systems and tools.
Chapter 7 Case Study Analysis: MINCO 189
Also, there is budget for training for each employee by which he/she could be nominated for
various types of required training classes.
On the other hand, as discussed earlier, there are numbers of applications and tools in
MINCO, which should be employed during the project lifecycle. The main concern is the
appropriate usage of the right application for associated purposes. Participants believe that on
some occasions they are not quite sure which system should be utilised, due to lack of training.
For instance, both Galileo and Hummingbird should be used for capturing project knowledge,
but there is limited guidance to address how and when these systems should be employed. This
means that lack of training courses to assist employees with suitable usage of the current
applications is a significant challenge, and some of quotes address this issue:
“…They’ve never actually been showed it, which may well be it. I mean when I first
started I got they say here you are, this is hummingbird…off you go. So the training side is
probably not there…”, quoted by In.Mc.4.
“…they’ve got the documentation that says this is how you do things. The problem comes
with people’s discipline in actually following…”, quoted by In.Mc.5
“…Well there’s obviously a gap because the framework is there for how you do it. It’s
just that people don’t, a lot of people don’t bother…”, quoted by In.Mc.2
The fourth most frequently mentioned challenge is the associated concerns about knowledge
reusing with more than 7 percent, as shown at Figure 7-6. According to the research
framework, knowledge reusing should be the last concern, as it is strongly dependent on other
knowledge processes, specially transferring and capturing. As discussed earlier, the initial
findings indicate that there are numbers of KM processes in place to support knowledge
capturing and transferring, such as data bases, procedures, and other applications, therefore
there are some bases for knowledge reusing. In other words, only in this case participants
directly have mentioned a number of concerns about lack of practices to facilitate knowledge
reusing, as could be seen one of the comments as following: “…I was saying it gets worse and
worse as you go through. And as far as reusing knowledge goes I mean it seems to me that it
only really gets reused when you’ve got the same people there that actually created it in the first
place…”, quoted by In.Mc.3.
This means that MINCO’s employees are aware of the importance of knowledge reusing, as
they expect to see some KM practices in place to facilitate this KM process. In order to shed
more light on this issue, the coded comments were analysed, and eventually three main sub-
issues were recognised in regards to knowledge reusing. First, the created knowledge at
initiation [identification] phase is not used because of lack of communication between study
group and project managers. Second, the nature of MINCO’s projects are similar, so
experienced PMs should transfer their knowledge for future usage purposes, but there are few
190 Chapter 7 | Case Study Analysis: MINCO
practices in place to support this process. And third, the current systems and their different
usages make some unambiguity for MINCO’s employees to capture and reuse previous
knowledge.
In summary, four challenges have been recognised in MINCO’s PMO from a KM point-of-
view. According to the research findings, issues of knowledge transferring is the most frequent
challenge from respondents’ point-of-view, and knowledge capturing is faced with a number of
issues, as the second most frequent challenges. Also, lack of training and KM practices to
support knowledge reusing have been recognised as third and fourth frequent-mentioned KM
challenges in MINCO. In this section, the initial part of the first research question (RQ1- How
are KM practices and processes employed in the PMOs?) has been addressed. In order to
answer the parts, the importance of the required knowledge types will be discussed in the next
section.
Types of required knowledge at project life cycle in MINCO 7.4.1.4
According to the research framework, there are eight types of knowledge at the project
environment: Project Management Knowledge; Knowledge about Procedures; Technical
Knowledge; Knowledge about Clients; Costing Knowledge; Legal and statutory Knowledge;
Knowledge about suppliers; and Knowledge of who knows what. In this step, the importance of
each type of knowledge will be discussed accordingly. To do so, survey forms were distributed
among the eleven participants and, eventually, eight completed forms were returned (about 72
% response rate). In the survey, respondents were asked to rank the above mentioned types of
knowledge from 1, the least, to 8, the most important knowledge during four phases of the
project life cycle. After collecting and organising data, similar to the previous case study, an
Analytical Hierarchy Process (AHP) was employed to analyse survey responses. Eventually, the
importance of eight types of project knowledge in MINCO’s PMO has been ranked in the
project lifecycle, as shown at Figure 7-7.
According to MINCO’s respondents at the Initiation phase, following are the three most
important types of knowledge: 8) project management knowledge, 7) technical knowledge, and
6) knowledge of who knows what. This is in line with current PM practices, as PMBOK (2012)
advises to have adequate knowledge of PM and technical knowledge at initiation phase. In
addition, respondents mentioned that finding the right person who has knowledge about similar
projects is important at this phase. As discussed earlier, one of the KM challenges in MINCO is
lack of practice for knowledge reusing. According to the research framework “knowledge of
who know what” contributes to reusing the existing knowledge. Therefore, this is one of the
reasons why participants have mentioned this type of knowledge as an one. On the other hand,
participants ranked the subsequent knowledge types as the less important ones: 3) knowledge
about procedures, 2) Legal knowledge, and 1) knowledge about supplier. This ranking is again
Chapter 7 Case Study Analysis: MINCO 191
is not contradictory with the research framework since there is no indication of having these
types at initiation phase, in the current KM standards.
Figure 7-7 Types of required knowledge at MINCO’s PMO (developed for this research)
At the planning phase the knowledge of PM still keeps its spot as the most important one,
but “knowledge about procedure” and “knowledge about clients” were chosen as second and
third most important knowledge. According to PM standards, “PM knowledge” and “knowledge
about procedures” are vital at the planning phase by which project plans are developed (Bentley
2009; Kerzner 2013; Project Management Institute 2013). In addition, knowledge about clients
is an important entity, since clients’ expectations play an important role for planning project
deliverables. On the one hand, respondents believe that knowledge costing is not as important as
technical knowledge and knowledge about who knows what. The first impression was that this
finding is not consistent with PM standards, however, more investigation revealed that since the
budget and cost of project is decided at higher levels of MINCO, then participants have less
concerns about it. In addition, choosing “knowledge about supplier” and “legal knowledge’ as
the least important types of knowledge is not against the PM standard, as they should be mostly
considered at execution phase (Project Management Institute 2013).
8
3
7
4 5
2 1
6
Initiation 8 7
4
6
3
2
1
5
Planning
8
4
7
1
5
3
7
2
Execution 8
7
3
6
4
2
1
5
Closing
192 Chapter 7 | Case Study Analysis: MINCO
At execution phase, the importance of “PM knowledge” has still been emphasised by
participants, while knowledge about procedure loses its spot to technical knowledge. In
addition, as was predicted earlier, knowledge about supplier was ranked as the second most
important knowledge at the execution phase. All three mentioned types of knowledge are
advised to be appropriately provided at the execution phase by the current PM standards, as they
are very important to implement the project plans (Project Management Institute 2013).
According to PMBOK (2013), after commencing the execution phase, clients have less
influence in the project. Consistently, participants have ranked “knowledge about client” as the
least important knowledge type at this stage.
According to PM standards, the closing phase is about to formally finish the project through
verifying the project deliverables and terminating the contract (Project Management Institute
2013). Therefore, knowledge of PM is mandatory to professionally follow the closing steps,
and, also, it is very important to have a good knowledge of organisational procedures to
formally finish the projects in accordance with organisational policies. As shown in Figure 7-7,
in a consistent manner both mentioned knowledge types have places as the most important types
of knowledge in the closing phase. Interestingly, “knowledge about client” has jumped from the
least important knowledge at execution, to the third most important knowledge at closing phase.
According to PM practices, one of the most important activities in the closing phase is to sign
off all deliverables and get the clients’ satisfaction, therefore it is very important to have a good
knowledge of clients and their expectations at this phase. In addition, technical knowledge and
legal knowledge have been placed as the least important types of knowledge, which is in line
with the purposes of the closing phase.
Table 7-8 Types of required knowledge in MINCO (developed for this research
Types of Knowledge \ Project Phase
Individual Rank Total weighted Rank
Initiation Planning Execution Closing Rank Percentage
Project Management Knowledge 8 8 8 8 8 19.5% Technical Knowledge 7 4 7 2 7 13.1%
Costing Knowledge 5 3 5 4 6 12.9%
Knowledge about Procedures 3 7 4 7 5 12.8%
Knowledge of who knows what 6 5 2 5 4 12.6%
Knowledge about Clients 4 6 1 6 3 12.2%
Legal and statutory Knowledge 2 2 3 3 2 8.5%
Knowledge about suppliers 1 1 7 1 1 8.4%
In the next stage of investigation, overall ranks of eight types of knowledge have been
analysed, regardless of project lifecycle phases. Similarly, AHP analysis was conducted by
giving the appropriate weight to each type of knowledge. Also, some other statistical
techniques, such as “mode”, were considered in the case of similar weight for some of the
Chapter 7 Case Study Analysis: MINCO 193
entities. The main aim of this process was to generally recognise the importance of each
knowledge type. The outcomes of this analysis have been illustrated in Table 7-8.
According to research findings, “project management knowledge”, “technical knowledge”,
and “costing knowledge” are the most important types of required knowledge during the project
lifecycle, while ”knowledge about suppliers”, “legal and statutory knowledge”, and “knowledge
about client” are not as important as the other types of knowledge. These findings are not
inconsistent with PM standards as they generally recommend project managers to follow the
current PM practices in order to provide technical and costing knowledge (Kerzner 2013). One
of the explored inconsistencies between the research findings and the PM standard is the rank of
“knowledge about clients” in this analysis. In other words, the current PM standards emphasise
the importance of recognising clients’ expectation, but from MINCO’s participants’ point-of-
view, this knowledge type is not as important as others. As discussed earlier, MINCO mainly
undertakes internal projects, therefore MINCO does not deal in general with the client.
In summary, the importance of knowledge types in MINCO’s PMO could be ordered as
following: 1) Project Management Knowledge, 2) Technical Knowledge, 3) Costing
Knowledge, 4) Knowledge about Procedures, 5) Knowledge of who knows what, 6) Knowledge
about Clients, 7) Legal and Statutory Knowledge, and 8) Knowledge about suppliers. These
findings are consistent with the research framework and the PM standards. In this section, the
second part of the first research question has been discussed. The next section aims to
completely answer the first research question as well as the second research question (RQ2-
How do KM practices contribute to improve maturity level of the PMO?), through discussing
four knowledge management processes and their subsequent KM practices.
Knowledge management processes and practices in MINCO 7.4.2
As discussed in previous chapters, four KM processes were adopted, in which each process
has numbers of KM practices. Also, it was assumed that all four KM processes are employed
throughout the project lifecycle (PLC) except closing phase, as depicted in Table 7-9. This
means that all KM processes should be utilised during PLC, however, knowledge capturing is
the only KM process which should be used at closing phase. This assumption will be examined
during the case study analysis.
Table 7-9 KM processes and PLC (adopted from Owen and Burstein (2005))
Initiation Planning Execution
& monitoring
Closing
Knowledge Creation √ √ √
Knowledge Capturing √ √ √ √ Knowledge Transferring √ √ √
Knowledge Reuse √ √ √
194 Chapter 7 | Case Study Analysis: MINCO
In this section the second research question (RQ2- How do KM practices contribute to
improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so the
followings steps have be managed: 1) investigating the utilisation of KM practices and KM
processes at four phases of PLC, 2) examining the above-mentioned assumption about KM
processes at project lifecycle, and 3) ranking the importance of four KM practices at each phase
of project lifecycle. To do so, the research framework and research methodology were followed
thoroughly, as explained in Chapter 5, Section 5.5.2. After following all required processes, the
obtained information was entered into Nvivo and eventually similar categories have been
developed, as depicted in Figure 5-9.
Similar to the previous case studies, frequency was used as the main criteria to explore the
current status of knowledge management in MINCO. During the process of coding interviews,
more than two hundred and fifty-four (254) comments and quotes, which have been directly
mentioned to explain the usage of KM practices, were recognised and then coded accordingly.
After analysing MINCO’S employees’ comments, it was revealed that more thirty five percent
of KM practices are employed at execution and monitoring phase, while only less than fourteen
percent of KM practices are utilised at initiation phase, as depicted in Table 7-10. This is an
indication of the importance of KM practices at the execution phase. In addition, the closing and
planning phases are the next important phases from a KM point-of-view. These findings are not
contrary to both current PM and KM literature as the majority of project activities are being
done at execution and planning phases (Project Management Institute 2013). Also during the
project closing phase, numbers of KM practices should be managed to prevent any knowledge
lost or leakiness (Owen and Burstein 2005).
Table 7-10 The usage of KM processes in MINCO (developed for this research)
Initiation Planning Execution &
monitoring Closing
13.9% 22.6% 35.7% 27.8% Knowledge Creation 25.8%
Percentage of KM processes Knowledge Capturing 62.6%
Knowledge Transferring 8.4% Knowledge Reuse 3.2%
From a KM process perspective, it was found that more sixty percent of current practices are
utilised for knowledge capturing, while only about three percent are employed for facilitating
project knowledge reusing. In addition, knowledge creation with about 26 percent and
knowledge transferring with about nine percent, are the second and third most utilised KM
practices in MINCO’s PMO. This means that the majority of the current KM practices have
been developed to support KM capturing and creation, while transferring and reusing are yet to
be developed. As discussed earlier, from a respondent’s point-of-view, knowledge transferring
and reusing are the most challenging KM processes in MINCO’s PMO (see section 7.4.1.3).
Chapter 7 Case Study Analysis: MINCO 195
This is consistent with the new findings as it was realised that knowledge transferring and
reusing should be appropriately addressed. In other words, both findings not only are in line but
also they indicate the importance of developing of reliable KM practices to support transferring
and reusing knowledge.
From respondents’ points-of-view, knowledge creation is the second most utilised KM
process with more 26 precent of the analysed data, as shown in Table 7-10. As discussed earlier,
MINCO operates projects to develop its business capabilities and competitive advantage. Also,
the majority of projects in MINCO are managed for exploring and discovering new coal mines.
This entails creating significant knowledge during a project’s life cycle, which needs to be
managed appropriately. MINCO’s senior managers have realised the importance of facilitating
and capturing the created knowledge, therefore, this process is supported through numbers of
practices which will be discussed in detail.
According to the research framework, only knowledge capturing practices should be
employed at the closing phase. This assumption has not been completely confirmed in MINCO,
as it was revealed that numbers of transferring practices are employed at the closing phase, as
shown Figure 7-8. This means that this assumption is faced with some challenges; the research
findings explored that there are a number of KM practices in place to support project knowledge
transferring at closing phase. For instance, respondents believe that at the end of each project,
when it is ready to be signed off, a workshop is held to discuss a project from initiation to
closing, in which participants are being asked to have some input, so this contributes to both
knowledge transferring, and also capturing lessons learned. As one of the project managers
explains: “…Well that’s a function of the PMO. They used to do lessons learned or lessons
learnt workshops after every project…”, quoted by In.Mc.5
Figure 7-8 KM processes at project lifecycle in MINCO (developed for this research)
Investigating theKM at project
stages
Initiation Planning Execution &Monitoring
Closing
40
10
18 12
0
97
13
23 29
32
13
2 3 7
3 5
0 2 2 0
Creation Capturing Transferring ResuingReusing
196 Chapter 7 | Case Study Analysis: MINCO
The most frequently mentioned KM process in MINCO is the knowledge capturing
process, as shown at Figure 7-8. This means respondents believe that the majority of the current
KM practices facilitate the process of knowledge capturing. As could be found in Figure 7-8,
during all phases of project lifecycle, knowledge capturing is the most frequent mentioned by
participants, which indicates the use of numbers of KM practices that support knowledge
capturing. In order to get better understanding of this KM process, it will be discussed in the
next section.
In summary, MINCO’s PMO has a reliable system to support KM activities. Knowledge
capturing and creation are the most developed KM processes, while knowledge transferring and
reusing are yet to be developed. According to the research framework, knowledge capturing is
an important process by which other KM processes are facilitated. In other words, a strong and
robust knowledge capturing system is an essential part of a KM system, which supports
knowledge transferring, creation and reusing. Therefore, it could be inferred that MINCO’s
PMO has an appropriate knowledge capturing system in place in order to develop other KM
processes, especially knowledge reusing and transferring. In addition, the research framework
assumes that only knowledge capturing should be managed at the closing phase, however, in
this case it was revealed that numbers of knowledge transferring practices are used at closing
phase. In this section, four KM processes have been discussed in general. In the next sections
each knowledge process will be individually discussed to answer the second research question
(RQ2. How do KM practices contribute to improve maturity level of the PMO?).
Knowledge Capturing in MINCO’s Project Management Office 7.4.2.1
According to the research framework, knowledge capturing should be employed during all
the phases of project life cycle, from beginning to the end of project lifecycle (Owen and
Burstein 2005). The previous findings have indicated that knowledge capturing not only is the
most frequent–mentioned KM process, but also it consists of a number of KM practices to
support the process of project KM, as depicted in Table 7-11. This table comprises three
columns in which the first table shows KM categories based on the research framework, the
second column represents the customised practices or systems to support the main categories,
and the third column displays the associated frequency to the KM categories.
The research findings revealed that document management system (DMS) is the most
frequent practice among other knowledge capturing, and it comprises a number of sub-
practices and applications, as shown in Table 7-11. This is a strong indication of the importance
of a document management system in MINCO’s PMO, by which project staff are advised to
follow the existing DMS for capturing project knowledge. There are numbers of documents in
various formats, forms and templates, such as project reports, meeting minutes, technical
designs, post project review and lessons learned. During the direct observation and document
Chapter 7 Case Study Analysis: MINCO 197
analysis stages, more than eighty documents and forms were found through which knowledge of
projects could be captured in various formats. In fact, the research outcomes explored that
knowledge capturing is significantly facilitated through the existing DMS in MINCO’s PMO.
The second and fourth most frequently mentioned practices in MINCO’s PMO are
database (DB) and management information system (MIS), as depicted in Table 7-11 and
Figure 7-9. According to Eriksson (2013), an advance form of data base is MIS, in which data
could be analysed and interpreted. This capacity has been developed in MINCO, in which the
current data bases are used to make business analysis and decision making. In other words, data
bases and MIS in MINCO’s PMO are employed for both knowledge capturing and knowledge
creation, which is the advance form of data and information management (Eriksson 2013).
There are couple of DBs in MINCO, such as Gbiz for coal exploration purposes, Galileo for
project repositories, and Hummingbird to capture project knowledge. According to the research
findings, the collaboration of current DBs and MISs is the next step to be addressed by
MINCO’s PMO.
Table 7-11 Knowledge capturing categories and practices: MINCO (developed for this research)
Knowledge Capturing categories Associated Practices at MINCO Frequency
Data base
• Galileo • Gbiz • Hummingbird • Lesson learnt database
20
Document Management System (DMS)
• Technical design • stakeholder mgmt. plan • Scope mgmt. plan • Risk assessment form • Project Reports • Project close out report • preliminary budget and schedule • Post project review • Opportunity statement for initiation • Meeting minutes • Lessons learned • End of the months report • close out report
85
Expert locator • Active directory 2 File Management System (FMS) • Windows base system 2
Formal or Informal events • E. room • Regular meeting • Workshops
16
Frequently Ask Questions (FAQ) • None 0 Intranet • A customised web-based intranet 3
Knowledge detection tools • None 0 Knowledge inquiry system • None 0
Knowledge repositories • Galileo 1
Management Information System (MIS)
• SAP • Gbiz • Galileo
15
198 Chapter 7 | Case Study Analysis: MINCO
The third most frequent-mentioned knowledge capturing process in MINCO’s PMO is
formal and informal events. This KM practice is supported through numbers of methods such as
meetings, e-rooms and workshops. According to the research framework, KM practices such as
forums and workshops could be used for both knowledge capturing and knowledge transferring
purposes. MINCO’s respondents believe that during these events not only they could get,
formally or informally, some answers to their questions, but also these events help them to
transfer some of their knowledge to other colleagues and project team members. As one of the
respondents comments: “…So we would have, oh not weekly it would be nearly daily catch ups
between the planner, project manager, myself cost controller and the supervisor when he was
free to discuss aspects of the project…”, quoted by In.Mc.4
Figure 7-9 Knowledge Capturing in MINCO’s PMO (developed for this research)
A customised intranet, expert locator, and an internal file management system and
knowledge repository are the other KM practices in the MINCO’s PMO for facilitating the
capture of project knowledge. As discussed earlier, MINCO has a robust server-client system by
which each client connects to MINCO’s server farms and gets access to the appointed
applications, so the file management system is another useful environment by which the
required knowledge is captured or stored. In addition, some of the current DBs such as yellow
page and contact list have been developed in separate environments. This is another indication
of the importance of integrating the current documents. On the other hand, some of the proposed
knowledge capturing practices in the framework, such as frequently asked question (FAQ),
knowledge detection tools (KDT) and knowledge inquiry (KI) system have not been recognised
in MINCO. This means that developing these practices could be the next step of the PMO for
improving the current KM system.
0
5
10
15
20
Management Information System(MIS)
Knowledge repositories
Knowledge inquiry system
Knowledge detection tools
Intranet
Frequently Ask Questions (FAQ)
Formal or Informal events
File Management System(FMS)
Expert locator
E-rooms
Document Management System (DMS)
Data base
Chapter 7 Case Study Analysis: MINCO 199
In summary, knowledge capturing is the most frequently mentioned KM process with more
than 62% of the associated comments in MINCO’s PMO. As discussed, document management
system, data bases, management information systems and formal and informal event are the
most frequently mentioned KM practices to support knowledge capturing, while some other
practices, such as intranet and expert locators are yet to be developed. In addition, three KM
practices, FAQ, KDT, and KI, have to be explored in MINCO. This means that MINCO’s PMO
has not completely addressed all the proposed KM practices. In other words, MINCO’s PMO
not only should address the mentioned KM practices, but also it should integrate the current
systems and applications, in order to improve the quality of project management. According to
the research framework, this will contribute to both the quality of project knowledge
management and also, improving the maturity level of MINCO’s PMO.
Knowledge Creation in MINCO’s Project Management Office 7.4.2.2
The second most frequently mentioned KM process in MINCO is knowledge creation,
with more than sixty times frequency out of more than two hundred and fifty. This means
MINCO’s respondents believe that there are a number of reliable practices to assist them with
creating knowledge during a project life cycle. According to the research framework,
knowledge creation could be facilitated through a number of practices, as shown in Table 7-12.
The frequency number of each associated KM practice has been pointed out in the following
table which is based on the research findings. From a respondent’s perspective, community of
practices and the existing research services are the most usable practices to create knowledge
in projects. On the other hand, they believe that some practices such as data mining and expert
systems are yet to be developed in MINCO’s PMO.
Table 7-12 Knowledge creation categories and pratices: MINCO (developed for this research)
KM creation categories Associated practices Frequency
Best Practice Cases • None 1
Community of practices • None 24 Data mining • None 0
Decision support system (DSS) • None 0
Deductive & Inductive thinking • Brainstorming 4
Documentation search • None 1
Experience Report • None 0
Expert systems (ES) • Expert Interview • Expert judgment
0
Informal and formal Event • Formal face to face meeting • Workshops & seminar
11
Knowledge Broker • None 6
Research services
• Simulation • Use of Metaphors • Market research • Data analysis
13
200 Chapter 7 | Case Study Analysis: MINCO
As discussed, the community of practice is the most frequently mentioned practice to
support knowledge creation. According to the research framework, a community of practice is a
group of experts with different specialities, which gather together to discuss a subject(s) from
various points-of-view (Bell 2010). The research findings revealed that this practice is common
in MINCO and there are a number of procedures to support a community of practice. For
instance, when an issue or unresolved subject occurs, then a project manager invites different
experts from various divisions to discuss it, whether via phone or face-to-face meeting. In fact,
internal processes in MINOC strongly support the facilitation of this KM practice. Following
are some of participants’ comments in this regard:
“…the opportunity statement was based on the knowledge of processing engineers,
chemists, coal experts …”, “…We took we got all of the experts together in at the mine site
for about four to six hours we sat down and we went through an opportunity framing
workshop if you like…”, quoted by Im.Mc.2.
“…So you’ve got the two different mindsets are starting to meet and fill in the blanks on
the project…”, quoted by In.Mc.4.
“…So you get the right people around you that know the stuff that you don’t know and
then you go down that track. Workshops, it doesn’t even have to be a formal thing…”,
quoted by In.Mc.5.
Figure 7-10 Knowledge Creation in MINCO (developed for this research)
From respondents’ points-of-view, research services are reasonably facilitated in the
MINCO’s PMO, as it has been ranked as the second most frequently mentioned practice for
knowledge creation. There are a number of research services such as market research,
simulation and data analysis in place, by which project team members are enabled to create
knowledge for both making proper decisions and adding more value on project deliverables. For
instance, market research is conducted when an opportunity is recognised, so its potential
0
1
2
3
4
5
6
7
8
9
10
11
12
Initiation Planning Execution& Monitoring Closing
Best Practice Cases
Community of practices
Data mining
Decision support system (DSS)
Deductive & Inductive thinking
Documentation search
Experience Report
Expert systems (ES)
Informal and formal Event
Knowledge Broker
Research services
Chapter 7 Case Study Analysis: MINCO 201
profitability is investigated, as In.Mc.2 explains: “…So at initiation phase there was a lot of
research market research and specialist coal producer research that showed this new
technology …will greatly improve coal product…”. According to the research findings research
service is managed during the planning and initiation phase, as shown at Figure 7-10.
The third most frequent KM practice for knowledge creation is “informal and formal
event”. MINCO’s respondents believe that the PMO contribute to manage various types of
formal and informal events. According to KM theories, “formal and informal events” is a
practice to support both socialisation and externalisation process for creating knowledge
(Nonaka and Takeuchi 1995). In other words, participating in seminars and workshops are
useful to create knowledge during the project lifecycle. These kinds of workshops are conducted
at various stages of projects for different purposes. For instance, project managers run a
workshop at the planning phase to discuss the project risk management with team members
and/or external advisors, as In.Mc.4 explains: “…So the initial documents that were provided
were the justification for the idea, the safety stats to help support the idea and a highlight of the
risks of not following through on this project…”. The research outcomes revealed that formal
and informal events are also employed to manage some other KM practices such as a
community of practice and brainstorming.
According to research findings, “knowledge broker” is another KM practice, which is used
to facilitate knowledge creation in MINCO’s PMO. According to Barclay and Osei-Bryson
(2010), the PMO is considered as a knowledge broker in which it has the responsibility to
facilitate communication among employees for knowledge creation purposes. From
respondents’ points-of-view, the PMO contributes to being a knowledge broker as it supports
KM through numbers of practices, such as transferring knowledge from external consultants,
and making reliable communications among different divisions of MINCO in order to capture
the required knowledge for projects. Following is the comment of PMO’s knowledge manager
in this regard: “…I believe for delivering projects and it’s what their expectations are that
you’ll go through and you know making sure that you engage the right people”. This means the
senior managers of MINCO’s PMO have realised that important role pf PMO as the project
knowledge broker.
The other KM practices for supporting knowledge creation such as expert system, decision
support systems, and data mining are yet to be developed, as little evidence was observed in this
regard. This means that despite the existence of numbers of reliable KM practices to support the
process of knowledge creation, however, there are numbers of KM practices yet to be addressed
in the MINCO’s PMO, which could be improved in order for achieving the next level of
maturity.
202 Chapter 7 | Case Study Analysis: MINCO
From a project lifecycle perspective, knowledge creation is conducted at initiation, planning
and execution phases, while there is no sign of creating knowledge at closing phase, as shown at
Figure 7-10. This finding again confirms one of the research framework premises, which
assumes that only knowledge capturing should be managed at closing phase. Also it revealed
that in MINCO’s PMO, knowledge is created during the three other phases, however, numbers
of improvements are yet to be done to improve the maturity level of PMO. This might be a good
guidance for PMOs with the same maturity level to focus on improving their knowledge
creation practices at planning and initiation phases, as there is no need to create knowledge at
closing phase.
In summary, knowledge creation is the second most frequent KM process in the
MINCO’s PMO. There are some reliable practices for knowledge creation such as research
services, community of practices, and formal and informal event by which MINCO’s employees
could create knowledge during initiation, planning and execution phases. However, some useful
KM practices, such as data mining and decision support systems need to be addressed in
MINCO’s PMO. In other words, the PMO should consider improving its level of maturity
through both developing the existing KM practices, and also establishing new KM practices.
This means that for the next level of maturity, MINCO’s PMO should develop its capability not
only from the PM point-of-view, but also through improving the current status of project
knowledge management. According to the research framework, developing KM practices in the
PMO contributes to improve the quality of project management, and maturity level of PMO.
Knowledge Transferring in MINCO’s Project Management Office 7.4.2.3
Knowledge transferring is the third most frequently mentioned KM process, with less
than 9 percent of total comments for KM practices, as shown in Table 7-10. This means
respondents believe that knowledge transferring is supported not as well as knowledge creation
and capturing. In other words, the current KM practices need to be improved to support
knowledge transferring process in MINCO. This is consistent with previous findings as it was
discovered that the majority of current challenges are related to knowledge transferring (see
section 7.4.1.3). As shown in Table 7-13, more than forty percent of the knowledge transferring
practices have not been recognised in MINCO’s PMO.
Table 7-13 Knowledge transferring pratices in MINCO (developed for this research)
KM transferring categories Associated System/Practices in MINCO Frequency
Communication channels • Chat rooms • Email 11
Database • Wikis 2 Discussion forums • None 2
Electronic bulletin board • Project bulletin and reports 0 Formal and informal events • Seminar and workshops 16
Intranet • None 1
Chapter 7 Case Study Analysis: MINCO 203
Knowledge directories • None 0 Knowledge list • None 0
Training& mentoring • Induction • Mentoring 19
Video and Tele Conference meeting • None 0
Yellow page • None 0
According to the research findings, Training and Mentoring are the most frequent KM
practices in MINCO, as depicted in Table 7-13. The research findings recognised numbers of
training courses, such as induction and SAP training in MINCO for facilitating the usage of
some of the current systems. However, participants believe the offered training courses do not
cover their current needs. As discussed in section 7.4.1.3, lack of training was found as one of
the current challenges in MINCO as respondents have numbers of concerns in this regards. This
means that MINCO’s PMO should improve their training services to both enhance the project
KM and also achieve the next level of maturity. Following are some of evidence in this regard.
“…So beforehand you have to operate that… train and put the training package in so everyone
can use. Not only training those people but also put the training package in as well…”, In.Mc.3.
“…And that’s from all stages of projects down to the point where site engineering take over. So
we have a learning tool …”, quoted by In.Mc.4
The research findings revealed that “formal and informal events” are the second most
frequent practice for transferring project knowledge. This means that some practices such as
informal conversation and workshops contribute to transfer knowledge from the owner to other
project team members, as In.Mc.4 explains: “…we had with the contractors involved, me
getting them into the office to sit down and discuss it with them. I found that a face-to-face
discussion achieved more…”. According to the research framework, this practice could be used
for knowledge capturing and creation as well, but the tone of interviewees’ explanation have
guided this researcher to put it in the right KM process. Discussion forums, workshops and
seminars as well as face-to-face conversation are employed to facilitate formal and informal
events, however, respondents have mentioned some issues in this regard. For instance,
participants believe that the current instructions for discussion forums and workshops are not as
productive as they had expected.
The third most frequently quoted practices for knowledge transferring are
“communication channels”. According to the research framework, communication channels
such as phone and chat room could be useful during the project life cycle. MINCO has a strong
phone system by which conference calls among project stakeholders is easy to manage. Also,
email is widely used among project staff and is one of the main communication practices. In
addition, during the direct observation stage, it was explored than both email and phone are used
productively among MINCO’s employees. In fact, the current email has provided a reliable
204 Chapter 7 | Case Study Analysis: MINCO
system for project team members in MINCO to make the required communications alongside
MINCO’s PMO offices. In addition, MINCO’s respondents have mentioned there are some
tools to support using databases and the intranet for knowledge reusing purposes. As can be
found in Table 7-13, the frequency of these practices is not significant, which means that they
are not significantly able to contribute to the process of project knowledge transferring, from
participants’ points-of-view. According to the research framework, both DBS and Intranet are
useful tools for knowledge management purposes, especially for transferring project knowledge
(Ajmal, et al. 2010; Julian 2008). This means that MINCO’s PMO should consider the
development of these two practices, as they significantly contribute to knowledge management.
Figure 7-11 Knowledge transferring in MINCO (developed for this research)
From a project lifecycle perspective, most of the knowledge transferring activities happen at
closing, execution, and planning phases, while only a little evidence was found to support
knowledge transferring at initiation, at shown at Figure 7-11. In fact, this is one of the existing
challenges in MINCO, in which respondents believe that the created knowledge as an initiation
phase is not appropriately transferred to the next phases, as the following comment explains:
“…so getting that knowledge passed over from one study manager to the next one is very
difficult unless people actually file it in the correct locations…”, quoted by In.Mc.5. This means
that knowledge transferring faces some issues in MINCO, especially in the initiation phase. This
is consistent with previous research findings, as it was revealed that knowledge transferring is a
significant challenge in MINCO.
In summary, knowledge transferring is the third most frequent KM process from a
participant point-of-view. According to the research findings, “training and monitoring”,
“formal and informal events”, and “communication channels” are the most frequent KM
practices to support knowledge transferring. As discussed earlier, knowledge transferring is one
of MINCO’s major challenges, which needs to be appropriately addressed. According to the
0
1
2
3
4
5
6
7
8
9
10
Initiation Planning Execution&Monitoring
Closing
Communication channels
Database
Discussion forums
Electronic bulletin board
Formal and informal events
Intranet
Knowledge directories
Knowledge list
Training& mentoring
Video and Tele Conferencemeeting
Chapter 7 Case Study Analysis: MINCO 205
research findings, knowledge transferring is employed in all four project phases as well as
closing phase, as depicted at Figure 7-11. This is not consistent with the adopted assumption in
the research framework. This means that from MINCO’s participants’ perspective, there are
some practices in place to support knowledge transferring at closing phase, such as workshops
and mentoring to prevent any knowledge leakiness or stickiness. This is a significant finding in
this case study and will be discussed further in the next chapter.
Knowledge Reusing in MINCO’s Project Management Office 7.4.2.4
The least frequent KM process in MINCO is knowledge reusing, with less than four
percent of total coded comments. This means MINCO’s participants believe that there are
limited numbers of KM practices in place to facilitate project knowledge reusing. As shown in
Table 7-14, the usage of the only four KM practices: databases; lessons learnt ( part of DMS);
expert system; and formal and informal events are fairly mentioned participates, while limited
evidence was found to support the employment of other 7 KM practices in MINCO. In other
words, knowledge reusing needs to be improved comprehensively, from the participant point-
of-view. Also, it was previously explored that MINCO’s employees have mentioned knowledge
reusing as one of the significant challenges in MINCO. Therefore, this is an obvious indication
for MINCO’s PMO to improve the current activities of knowledge reusing.
Table 7-14 Knowledge Resing practices in MINCO (developed for this research)
KM reusing categories Associated Practices Frequency
Data base • DB 7 Data mining • None 0
Document Management System • Mentioned in lesson learnt 0 Electronic notice board • None 0
Expert systems • None 2 Formal or informal meetings • None 1
Intranet • None 0 Knowledge detection tools • None 0
Knowledge map • None 0 Lesson learnt • None 4 Yellow page • None 0
According to the research finding, the importance of knowledge reusing has been realised by
both senior managers and project staffs in MINCO. In other words, the role of knowledge
reusing to reduce project costs, and risk in order to improve project quality has been emphasised
by participants, as the following have been mentioned by interviewees:
“…there any kind of process within the PMO which tells you okay for reusing
knowledge go to this…”, quoted by In.Mc.4.
206 Chapter 7 | Case Study Analysis: MINCO
“…experience like all the documents but it’s not like a web base that you can go and
filter for those similar projects. But they are starting to make it like that. Not mature
enough yet…”, quoted by In.Mc.3
As Figure 7-12 depicts, the majority of the current knowledge indicated that reusing
activities are managed at initiation, and planning, while there was limited evidence of applying
knowledge reusing practices at the closing phase. This is consistent with the research
framework as it is assumed that knowledge reusing should be employed at all three project
phases, except closing phase (Owen & Burstein, 2005). This also consistent with the current PM
practices as they advise managing activities such as signing off project contracts and handing
over project deliverables at closing phase (Project Management Institute, 2012).
Figure 7-12 Knowledge reusing at project lifecycle: MINCO (developed for this research)
In summary, knowledge reusing is the least frequently mentioned KM process in
MINCO’s PMO. According to research findings, only four out of eleven KM practices have
been mentioned by MINCO’s employees. This means they believe that the current KM practices
do not significantly support the knowledge reusing process. According to Love, et al. (2003)
“rework” is one of the significant challenges for projects in Australian companies in which
“reworks” cost up to fifty percent of overrun costs. According to the research framework,
employing knowledge reusing practices significantly reduces rework. This indicates the
importance of knowledge reusing for increasing the project success rate. As discussed earlier,
knowledge reusing is considered as one of the major MINCO challenges. This means that
MINCO’s PMOs should focus on developing KM practices to improve the knowledge reusing
process, in order to achieve the level of maturity.
Summary 7.4.2.5
In conclusion, the first research question (RQ1- How are KM practices and processes
employed in the PMOs?) and its sub-questions have been answered in this section. According to
0
1
2
3
Initiation Planning Execution &Monitoring
Closing
Data base
Data mining
Document Management System
Electronic notice board
Expert systems
Formal or informal meetings
Intranet
Knowledge detection tools
Knowledge map
Lesson learnt
Yellow page
Chapter 7 Case Study Analysis: MINCO 207
research findings, the recognised challenges in MINCO are mainly related to knowledge
transferring and reusing. In order to answer the third sub-question (RQ 1.3 What kinds of KM
practices are utilised in each maturity level of PMO?), all four KM processes were analysed,
and, eventually, it was realised that knowledge capturing and creation are the most frequently
used KM processes in which more than sixty-two percent of comments support knowledge
capturing. In addition, knowledge transferring and reusing, together, are supported by only less
than thirteen percent of the collected data.
According to the research framework, only knowledge capturing should be employed at
closing phase. The research findings revealed that there are a number of knowledge transferring
practices in place, which are used at closing phase. This means that the mentioned assumption
has not been confirmed in MINCO as respondents believe they employ knowledge transferring
and capturing at closing phase. In addition, research data revealed that the majority of KM
activities are undertaken at Execution and monitoring phases, which is in line with PM
literature, since PMBOK explicitly addresses numbers of PM processes to support KM at the
planning and execution phase (Project Management Institute 2013).
According to the above mentioned findings, the following propositions could be proposed to
address the KM at the second level of maturity: 1) Knowledge capturing and creation are the
most important processes to be improved at third level of maturity, which means that PMO
should firstly focus on improving current practices for capturing knowledge and then creation,
2) Knowledge reusing is the least important KM process at this level, and it is dependable on
capturing and transferring. So it is recommended to focus on this knowledge process at the next
levels of maturity.
The importance of knowledge management processes in MINCO 7.4.3
This section aims to answer the second research question (RQ2-How do KM practices
contribute to improve maturity level of the PMO) and its sub-questions. Similar to previous case
studies, the survey–questionnaire was used at the main source of data in order to determine the
importance of four KM processes; Creation; Capturing; Transferring and Reusing at project
life cycle, i.e. Initiation; Planning; Execution and Monitoring; and Closing. As discussed
earlier, AHP technique is a suitable and accurate method for ranking the priority of competing
phenomena (Lindner and Wald 2011; Stam and Silva 1997), therefore, this technique was used
to rank KM processes in MINCO’s PMO.
According to the data analysis, knowledge reusing and creation were placed as first and
second important KM processes at the initiation phase, while knowledge capturing and
transferring have got the third and fourth rank, as depicted at Figure 7-13. This shows the
importance of knowledge reusing and creation at this phase, from a respondent point-of-view.
The direct observation revealed that in the initiation phase, the main focus in MINCO is to
208 Chapter 7 | Case Study Analysis: MINCO
investigate the project idea and analyse the different options. In other words, research data
indicates that knowledge is significantly created at this phase. In addition, due to the similarity
of projects in MINCO, project managers are strongly advised to use the knowledge of previous
projects as well as lessons learnt. This means that participants believe that it is important to have
appropriate KM practices for reusing knowledge at the initiation phase. This is consistent with
the current PM practices as they recommend to use previous projects’ knowledge in the
beginning of a project definition (Project Management Institute 2013). According to PMBOK
(2013), information about similar projects could contribute to better provision of project charter,
scope statement, and planning materials. In addition, PMBOK assumes that knowledge is
significantly created during initiation and planning phases, while during the execution and
closing phase, knowledge capturing has become more important (Reich and Wee 2006).
Figure 7-13 The importance of KM processes in MINCO (developed for this research)
In a consistent manner, knowledge creation is ranked as the second and first important KM
process during the initiation and planning phase, while it is the lowest one at closing phase.
This means that participants confirm the above mentioned theory and emphasised the crucial
role of knowledge creation at the planning and initiation phase. Having said that, the main aim
of the planning phase is to develop the required detail plans to achieve project objectives
(Project Management Institute 2013). In fact, planning consists of creating plans, technical
designs, budget analysis and other related knowledge to make sure that all activities have been
defined and appropriately planned for the execution phase (Project Management Institute 2013;
0
1
2
3
4
Initiation Phase
Capturing CreatingTransferring Reusing
0
1
2
3
4
Planning Phase
0
1
2
3
4
Execution and Monitoring Phase
0
1
2
3
4
Closing Phase
Chapter 7 Case Study Analysis: MINCO 209
Reich and Wee 2006). This finding is another confirmation of the importance of knowledge
creation at the planning and initiation phase.
Moreover, at planning phase, knowledge transferring is ranked as the least important KM
process. This finding is not inconsistent with the research framework, as the project is still at the
initial steps of creating knowledge. In other words, knowledge could be transferred when the
created knowledge is captured and ready to be used by others. Therefore, participants
consistently have put the knowledge transferring in the fourth spot as they believe that the other
KM processes are more useful at the planning phase. This means that knowledge transferring
should get a better ranking spot at execution and closing phase. This assumption is confirmed as
it was realised that knowledge transferring has become the second most important KM process
at both closing and execution phase, as depicted in Figure 7-13.
At the execution phase, knowledge capturing and transferring were ranked as the first and
second most important KM processes, as shown at Figure 7-13. On the other hand, knowledge
creation and reusing have got the third and fourth positions. According to the PMBOK (2013),
at the execution phase the majority of activities should be undertaken through following the
provided plans, so project activities should be reported and measured regularly. This means that
knowledge capturing is the most important activity from KM point of view. Also, employees
should be trained, mentored or taught in order to undertake their assigned job. The research
findings are consistent with the current literature as MINCO’s respondents have ranked the
importance of KM processes. This means that MINCO’s employees believe that in the
execution phase, most of the KM activities should be focused on knowledge capturing and
transferring, while knowledge reusing is the least important process in this phase. In addition,
respondents believe that knowledge creation is more important than knowledge reusing at
execution phase. According to the findings from document analysis during the execution phase,
a number of PM activities are employed in MINCO, such as change management, and risk
management processes.
Figure 7-14 The general ranking of KM processes: MINCO (developed for this research)
As discussed earlier, the research framework assumes that knowledge capturing should be
the only KM process to be employed at closing phase (Owen and Burstein 2005). This means
0
1
2
3
4
Capturing Creating Transferring Reusing
210 Chapter 7 | Case Study Analysis: MINCO
that at closing phase, knowledge capturing should be the most important KM process. As shown
in Figure 7-13, MINCO’s employees consistently have ranked knowledge capturing as the most
important KM process at the closing phase. In addition, they have ranked knowledge
transferring as the second most important KM process. As discussed earlier, some evidence was
found that MINCO’s PMO advises knowledge transferring practices at the closing phase. This
finding is in line with previous findings as participants believe that some KM practices should
be employed at the closing phase to transfer knowledge to other MINCO employees.
After discussing the KM processes at each project phase, the next level of analysis was
conducted to investigate the rank of KM processes in the project lifecycle regardless of
individual phases. Similar to other cases, the same processes of employing the AHP technique
has been managed, and eventually the following rank of KM processes has been determined: 1)
knowledge capturing, 2) knowledge creation, 3) knowledge transferring, and 4) knowledge
reusing. According to the research findings, MINCO’s employees believe that knowledge
capturing and creation are the most important KM processes, while knowledge transferring and
reusing are not as important as the other two processes, as depicted at Figure 7-14.
In the previous section, i.e. section 7.4.2, KM processes and their usage have been analysed
to answer the first research question. The research findings revealed the following ranking of
KM processes, from data frequency point of view: 1) knowledge capturing, 2) knowledge
creation, 3) knowledge transferring and 4) knowledge reusing. As can be inferred from both KM
rankings, they are following the same order in which knowledge capturing and creation are the
most important KM processes in MINCO’s PMO, while knowledge transferring and reusing
have been ranked at third and fourth of the KM processes. This means that consistent outcomes
have been obtained from different data collection methods, which contributes to the quality of
the data collection methods as well as research outcomes.
In summary, findings from the survey, interview analysis, documents analysis, and direct
observation all emphasised that knowledge capturing and creation are the most important KM
processes in MINCO’s PMO, while knowledge transferring and reusing have not been
recognised to be as important as the other two KM processes. Therefore, it could be concluded
that at the third level of maturity the current KM practices should support KM in the following
order: Capturing, Creating, Transferring, and Reusing. In addition in could be concluded that,
at the third level of maturity, since PMOs have developed basic practices for supporting
knowledge capturing and creation, then the focus should be on improving knowledge
transferring and reusing through developing appropriate KM practices such as knowledge
detection tools, knowledge map, and electronic notice board. This not only will improve the
quality of KM process in the PMO but also it contributes to achieve better maturity levels.
Chapter 7 Case Study Analysis: MINCO 211
DISCUSSION AND IMPLICATIONS 7.5
In the previous sections of this case study, the two first research questions, i.e. how are KM
practices and processes employed in the PMOs, and how do KM practices contribute to improve
maturity level of the PMO, have been answered. In addition, during the data analysis stage, both
the importance of KM processes and the existence of challenges have been discussed in
MINCO’s PMO. In this section, each KM process will be discussed to investigate its
relationship with both KM associated sub-processes. and the following KM challenges: 1)
Inadequate practices to support knowledge transferring process, 2) Issues with current systems
to fully support knowledge capturing process, 3) Unsatisfactory practices to appropriately
support knowledge reusing process, and 4) Lack of training for current systems and
applications.
Knowledge transferring’s sub-processes and practices in MINCO 7.5.1
As discussed earlier, both knowledge transferring and reusing have been ranked as the third
and fourth most important KM process, among four KM processes. In addition, it was
recognised that the majority of the current KM practices in MINCO support knowledge
capturing and creation, while there are few KM practices to facilitate knowledge reusing and
transferring. Also it was revealed that MINCO’s respondents believe that majority of KM issues
are related to knowledge transferring and reusing, as discussed in section 7.4.1.3.
All these findings consistently confirm that knowledge transferring is one of the challenges
in MINCO’s PMO. In other words, knowledge transferring has been faced with numbers of
challenges in MINCO’s PMO, specifically challenges number one and four. According the
research findings, issues such as transparency and lack of access to the current knowledge are
some of the KM challenges in MINCO, as In.Mc.3 explains “…We need better transparency at
execution. A lot of this information is locked away and people keep it on their hard drives or
they don’t keep them in shared folders so you can’t access…”. In order to analyse the issue of
knowledge transferring in MINCO, the research framework was employed accordingly.
Table 7-15 Knowledge transferring sub processes in MINCO (developed for this research) K. Transferring Sub Processes
Practices for Knowledge Transferring
Associated Challenges Current Status
Knowledge Distribution and
forwarding
• Project bulletin and reports
• Communication channels
• Knowledge list
• Video and Tele Conference meeting
• Yellow page • Intranet • Data base
1 and 4
Except communication channels such as email
and, other practices should be developed
Knowledge Sharing
• Discussion forums
• Formal and informal events
• Mentoring • Training 4
Training and formal and informal events are
mostly used
212 Chapter 7 | Case Study Analysis: MINCO
According to the research framework, knowledge transferring consists of two-sub processes:
distribution & forwarding; and sharing knowledge, as shown in Table 7-15 (Lytras and
Pouloudi 2003; Nissen, et al. 2000). The communication channels (such as email, chat), and
intranet are an example of “knowledge distribution”, and, training, discussion forums, and
mentoring are instances of “knowledge sharing”. As a matter of fact, for distribution process
technologies are more influential, while for knowledge sharing procedures and people play an
influential role (Hurt and Thomas 2009; Nonaka and Takeuchi 2011; Wiewiora, et al. 2010). In
Table 7-15 both sub-processes and their associated practices have been illustrated clearly.
According to the research findings formal and informal events as well as training and
mentoring are the most frequently mentioned practices for facilitating knowledge sharing, while
only communication channels have been recognised to support knowledge distribution and
forwarding. This means that MINCO’s PMO has developed some practices for sharing
processes, but, there are some gaps in place to support knowledge transferring from a
technological point of view. In other words, MINCO should develop some practices such as
project bulletin or yellow page to improve the knowledge transferring, and consequently to
address some of the current challenges, such as lack of transparency.
Further analysis revealed that knowledge distribution faces two challenges (1 and 4), while
knowledge sharing encounters the fourth challenge, i.e. lack of training for current systems and
applications. This is consistent with the previous findings as it was discussed that the current
knowledge transferring mostly facilitates knowledge sharing, so knowledge sharing should face
less of an issue, in comparison to knowledge distribution. This means that MINCO’s PMO
should develop the missed KM practices, such as knowledge list and yellow pages, in order to
address the current challenges, and ultimately improve the quality of project knowledge
management.
Knowledge reusing’s sub processes and practices in MINCO 7.5.2
The research findings explored that knowledge reusing is the second KM process, in terms of
KM challenges. In other words, after knowledge transferring, the majority of the recognised
KM challenges are related to knowledge reusing. On the other hand, knowledge reusing has
been ranked as the first and second most important KM process in initiation and planning
phases, as depicted at Figure 7-13. This means that participants have picked up the importance
of knowledge reusing for project planning and initiation purposes, and consistently they believe
that knowledge reusing faces some challenges, specifically at the two mentioned phases.
Table 7-16 Knowledge reusing sub-processes in MINCO (developed for this research)
K. Reusing Sub Processes
Practices for Knowledge Reusing Comments
Chapter 7 Case Study Analysis: MINCO 213
Knowledge Adapting
• Electronic notice board • Documents management
system (DMS) • Intranet
• Data base • Yellow page • Knowledge detection tools • Formal or informal events
Majority of the mentioned KM
practices are yet to be addressed for knowledge
reusing purposes Knowledge Applying • Expert systems • DMS
Knowledge Integrating • Knowledge map • Data mining
In order to drill down these issues, the next level of analysis has been managed to investigate
knowledge reusing practices against the recognised challenges. According to the research
framework, knowledge reusing has strong collaboration with knowledge capturing and
transferring. In other words, knowledge reusing is the process in which captured and/or
transferred knowledge is utilised for future or similar projects (Tan, et al. 2007). According to
the research framework, knowledge reusing comprises three sub-processes: adapting, applying,
and integrating, as shown in Table 7-16.
According to the research findings, knowledge reusing is the least frequently mentioned KM
process in MINCO, with less than four percent of the total coded comments. This means
MINCO’s employees believe that there are few practices to support knowledge reusing. For
instance some applications such as Galileo for project history, and some experienced reports,
are used for knowledge reusing purposes, however, they are not enough to significantly support
knowledge reusing in MINCO’s PMO. The research analysis confirms that knowledge adapting
and applying are somehow employed at MINCO, however, knowledge integration is a
significant issue from a knowledge reusing point-of-view. This means that both knowledge
integration practices, i.e. data mining and knowledge map, are yet to be addressed in MINCO’s
PMO. In fact, MINCO’s PMO should focus on improving the recognised KM challenges to
improve the quality of project KM and, ultimately to achieve the better maturity level.
On the other hand, according the research framework, reusing project knowledge is
dependent on a reliable capturing and transferring system. This means that knowledge reusing
could not be improved without the existence of a robust KM system, especially transferring and
capturing. In other words, MINCO’s PMO should focus on addressing the existing challenges of
knowledge transferring and capturing. This is also is consistent with the research framework, as
it is advised to focus on improving knowledge transferring and capturing, prior to knowledge
reusing.
Knowledge capturing’s sub processes and practices in MINCO 7.5.3
As discussed, knowledge capturing is the most important KM process in MINCO, from
participants’ points-of-view. On the other hand, the research analysis revealed that after
knowledge transferring and reusing, knowledge capturing is the third frequently mentioned KM
process, in term of the recognised KM challenges in MINCO. In other words, participants
214 Chapter 7 | Case Study Analysis: MINCO
believe that knowledge capturing faces issues such as access to the required knowledge.
According to the research framework where knowledge capturing has been classified into four
sub-processes: Identification, Storing, Classification, and Selection, as shown in Table 7-17
(Lytras and Pouloudi 2003; Nissen, et al. 2000).
The research outcomes indicate that document management system (DMS), Database (DB),
formal and informal events, and management information system (MIS) are the most frequent
practices among other KM practices for knowledge capturing. This means that knowledge
storing is the most frequent mentioned KM sub-process in MINCO. In other words, participants
believe that the majority of the current KM practices have been developed to improve
knowledge capturing through storing sub-process. After knowledge storing, knowledge
classification is the second most frequent knowledge sub-process in MINCO. According to the
research findings, MINCO has strong systems and tools to store and classify the project
knowledge. In other words, the majority of the current KM practices facilitate the knowledge
storing and coalification part of knowledge capturing.
On the other hand, there is little evidence to appropriately support knowledge identification
and selection. This means that MINCO’s PMO is yet to improve the mentioned two sub
processes of knowledge capturing. For instance, limited practices were recognised to address the
KIS and FAQ, which both facilitate knowledge selection. In addition, knowledge detection tools
and expert locater are other KM practices which are yet to be addressed in MINCO’s PMO.
However, some practices for knowledge identification have been recognised in MINCO, such as
formal and informal interview and knowledge repositories, but they need to be improved to
appropriately address the knowledge capturing process.
Table 7-17 Knowledge capturing sub-processes in MINCO (developed for this research)
K. Capturing Sub Processes
Practices for Knowledge Capturing Comments
Knowledge Identification
• Expert locator • Formal and
informal event
• Knowledge detection tools
• Knowledge repositories
This is the second most frequent mentioned sub
process
Knowledge Storing
• Data base • Formal and
informal event
• Document Management System (DMS)
Most of the current system support this
process
Knowledge Classification
• Document Management System (DMS)
• Frequently ask questions
• File management system
• Management information system(MIS)
• Intranet
This is the most frequent mentioned KM
sub process.
Knowledge Selection
• Knowledge inquiry system (KIS)
• Data base • Frequently asked
questions (FAQ)
The current status is not satisfactory as is yet to be addressed
Chapter 7 Case Study Analysis: MINCO 215
Knowledge creation’s sub processes and practices in MINCO 7.5.4
The research findings have recognised “Knowledge Creation” is the second most frequently
mentioned KM process in MINCO’s PMO. According to Nonaka and Takeuchi (1995)
knowledge is created through four sub-processes (SECI) : Socialisation, Externalisation;
Combination; and Internalisation. The SECI model was adopted in the research framework as
the main sub-processes of knowledge creation, as shown in Table 7-18.
According to the research findings, a community of practice is the most frequent of the KM
practices, and respectively research services and formal and informal events are the second and
the third KM practices for supporting the process of project knowledge creation in MINCO, as
depicted in Table 7 12. Similarly, the research analysis recognised the utilisation of other
practices, such as knowledge broker, deductive and inductive thinking, best practices and
documentation searching in MINCO’s PMO, by which knowledge creation is facilitated.
According to the research framework Socialisation is the process of creating tacit knowledge
through various types of communications (Nonaka and Teece 2001) in which it is facilitated
through some practices such as formal and informal events, and community of practice, as
shown in Table 7-18. Hoegl and Schulze (2005) explain that formal and informal events are
good tools for supporting Socialisation through which tacit knowledge is discussed and
sometimes transferred among individuals. The research findings revealed that all three KM
practices for Socialisation have been recognised in MINCO. This means MINCO’s employees
believe that “formal and informal events”, community of practices”, and workshops and
seminars are conducted during the project lifecycle. In other words, the knowledge creation
process is significantly supported through the Socialisation sub-process.
Table 7-18 Knowledge creation sub procesess in MINCO (developed for this research) K. Creation
Sub Processes Practices for
Knowledge Creation Comments
Socialisation
• Formal and informal event
• Workshops & seminar
• Community of practices
Most of them have been put in place and utilised
Externalisation
• Workshops & seminar
• Deductive & Inductive thinking
• Experts system • Experience Report • Community of
practices
Most of them have been put in place and utilised but some of them such as expert system should be
improved
Combination
• Community of practices (COP)
• Best Practice Cases (BPC)
• Knowledge Broker • Data mining • Documentation
search
Except the community of practices, other are yet
to be addressed
Internalisation • Research services • Simulation
• Experimentation This is the second most facilitated KM practices
Externalisation is the process to transform tacit to explicit knowledge (Nonaka and Teece
2001). According to the research framework there are a number of practices that could be used
to support externalisation, as depicted in Table 7-18. The research findings showed that some of
216 Chapter 7 | Case Study Analysis: MINCO
the mentioned practices, such as community of practice, are significantly addressed in MINCO,
while there are number of KM practices, such as expert system and deductive and inductive
thinking, that are yet to be developed in MINCO. This means that transformation of tacit
knowledge to explicit knowledge is yet to be improved in MINCO’s PMO. In other words,
MINCO’s PMO should develop the externalisation process in order to achieve the next level of
maturity. In fact, externalisation is an important process to prevent knowledge leakiness in the
projects (Nonaka and Teece 2001).
Nonaka and Teece (2001) define the combination as the process of transforming explicit
knowledge to more complicated explicit knowledge. According to the research framework, the
process of combination is satisfied when there is a system in place for developing current
manuals, instructions, procedures, methodologies and as such (Alavi and Leidner 2001; Nonaka
and Teece 2001). According to the research findings, the combination process has been fairly
developed in MINCO as some of its associated KM processes, such as data mining and
documentation search, are yet to be developed in MINCO. This means that MINCO’s PMO
should focus on addressing the recognised gap in order to improve the quality of the KM.
According to Nonaka (1994) Internalisation is the process of knowledge creation by which
a new tacit knowledge is developed through using existing explicit knowledge. As can found in
Table 7-18, there are a number of practices such as research services, simulation, and
experimentation to facilitate knowledge creation through internalisation. The research findings
revealed that internalisation is the second most utilised KM process to support the knowledge
creation process. In other words, a number of practices such as simulation, alternative analysis
and market research are managed, especially at initiation and planning phases, in order to create
accurate knowledge for decision making purposes. This means that internalisation significantly
contributes to the process of knowledge creation developed in MINCO.
Tacit Knowledge TO Explicit Knowledge
Tacit Knowledge
From
Socialisation (has been addressed in
MINCO)
Externalisation (is yet to be developed in
MINCO)
Explicit Knowledge
Internalisation (has been addressed in
MINCO)
Combination (is yet to be addressed in
MINCO)
Figure 7-15 The SECI in MINCO’s PMO (Nonaka and Teece 2001)
In a nutshell, knowledge creation has been significantly addressed in MINCO, but, there are
some issues that are yet to be addressed accordingly. According to Nonaka (2001) the SECI
model follows a spiral method in which all four sub-processes should be interconnected, as
illustrated in Figure 7-15. According to the research findings both Socialisation and
Internalisation have been appropriately addressed in MINCO so they significantly contribute to
the process of knowledge creation, while Externalisation and Combination are yet to be
Chapter 7 Case Study Analysis: MINCO 217
developed in MINCO’s PMO. This means that MINCO’s PMO should address the missing KM
practices in order to improve the quality of KM, and consequently the level of PMO maturity.
CONCLUSION 7.6
This chapter aims to answer the first and second research questions (RQ1. How are KM
practices and processes employed in the PMOs, and RQ2. How do KM practices contribute to
improve maturity level of the PMO), and their associated sub-questions (what are the current
challenges of the PMO from KM perspective, What types of knowledge are required at each of
following project phases, What kinds of KM practices are utilised in each maturity level of
PMO, What is the importance of knowledge processes at each phase of project, How PMO
should contribute for managing the project knowledge). As it was explored, the selected case
study, MINCO, is an international mining company, which developed a PMO with the third
level of maturity. In order to answer the research questions in this case, the research framework
(Chapter 3) has been employed through following the research methodology (Chapter 4). In the
section, a summary of the research findings has been succinctly presented.
The research findings revealed that the following are the main challenges of MINCO from a
KM perspective: Inadequate practices to support knowledge transferring process, Issues with
current systems to fully support knowledge capturing process, unsatisfactory practices to
appropriately support knowledge reusing process, and Lack of training for current systems and
applications. These findings are useful indications for MINCO in order to improve the quality of
the project KM and, consequently to enter the next maturity level of PMO.
The research findings revealed the following order, from participants’ points-of-view, for the
required types of knowledge: 1) Project Management Knowledge, 2) Technical Knowledge, 3)
Costing Knowledge, 4) Knowledge about Procedures, 5) Knowledge of who knows what, 6)
Knowledge about Clients, 7) Legal and statutory Knowledge, and 8) Knowledge about
suppliers. This is a clear indication for MINCO, or PMOs with similar maturity levels, to
prioritise the importance of their required knowledge.
Furthermore, the importance of KM processes has been discussed through analysing both
interviews and survey, and consistently both revealed the following order: 1) Knowledge
Capturing 2) Knowledge Creation 3) Knowledge Transferring, and 4) Knowledge Reusing. This
means that knowledge capturing and creation are the most important KM practices, while
transferring and reusing are not as important as the other two. In addition, informal and formal
events are the most utilised KM practices that contribute to all four KM processes. These are
valuable findings for the PMO to improve this practice, as it plays a significant role for project
knowledge management.
218 Chapter 7 | Case Study Analysis: MINCO
In the last section, i.e. 7.5, the relationship between KM challenges and KM processes, has
been investigated. It was found that knowledge reusing and transferring are the most
challenging KM processes. These findings shall contribute to prioritise the development of KM
processes, sub-processes and practices. In other words, the research findings address appropriate
KM practices and processes with regards to their associated challenges and issues. These
findings also address appropriate practices to improve the quality of project knowledge
management, and consequently the maturity level of PMO.
In the end, the following have been summarised in MINCO’s PMO, with a third level of
maturity:
• At the third level of maturity the project KM is supported by senior managers and there
are significant numbers of KM practices in place to facilitate the project KM,
• There is a unit in the PMO to address and develop the project KM,
• Knowledge capturing and creation are the most important KM processes and the
majority of current PM practices support them,
• At the third level of maturity, there is a comprehensive PM methodology in place, so it
is recommended to improve the current PM standards through integrating with KM
practices.
Chapter 7 | Case Study Analysis: MINCO 219
220 Chapter 8 | DISCUSSION and RESULT
Chapter 8
DISCUSSION and RESULT
INTRODUCTION 8.1
In the previous chapters, three cases were individually discussed to investigate from a KM
point-of-view. The research framework was employed to outline KM practices for each
organisation. The main objective of the analysis in the last three chapters was to get insightful
information about each case as a standalone entity, in order to use the collected data for
conducting the cross-case analysis phase. In the previous chapters, the process of “within-case
analysis” was managed to answer the first two research questions, while in this chapter the
process “cross-case analysis” will be conducted to compare the collected data from each in
order to answer the third research question, as shown in Table 8-1.
Table 8-1 The research questions (developed for this study)
1. To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from KM perspective?
1.2. What types of knowledge are required at each phase of project lifecycle?
1.3. What kinds of KM practices are utilised in each maturity level of PMO?
2. How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project? 2.2. How PMO can contribute for managing the project Knowledge?
3. How can knowledge be integrated in the PM maturity model? 3.3. How is knowledge created, captured, transferred and reused in PMOs?
3.4. How can KM practices be employed in each maturity level of PMO?
In this chapter, first the analytical procedures will be discussed followed by an overview of
the three cases. Second, the research questions will be answered through comparing the
collected data from each case. Third, the framework will be scrutinised through discussing the
theoretical assumptions and the collected data from cross case analysis. Finally, the research
findings will be summarised accordingly.
THE ANALYSIS PROCEDURE 8.2
The aim of cross case analysis is to look for differences and similarities of various cases in
order to explain the reasons behind them (Yin 2009). According to the current literature, the
pattern matching technique is a useful and efficient way to undertake cross case analysis
(Creswell 2009; Eisenhardt and Graebner 2007; Yin 2009). Also, Grounded theory is reliable
Chapter 8 | DISCUSSION and RESULT 221
method to make plausible conclusions based on findings of pattern matching and other cross-
case analytical techniques (Corbin and Strauss 2008).
A range of Nvivo techniques such as matrix queries, relationship nodes, figures, and
diagrams have been employed to follow both pattern matching and Grounded theory techniques
to explain the phenomena. This means that the research framework that has been employed for
this investigation by the research findings has been compared to the research framework for
following pattern matching processes. In the case of inconsistency of the collected data, the
Grounded theory has been used to make a plausible explanation for the recognised phenomena.
These investigations and activities have been managed to explore the role of knowledge
management at various maturity levels of the PMO in order to make a number of plausible
propositions. The proposed theories will be discussed in the next section in order to compare
research findings with the current literature.
AN OVERVIEW OF CASE STUDIES 8.3
As stated in Chapter 4, the following criteria were employed to select suitable cases for this
research : 1) the organisation should have an office, centre or unit for managing their projects
which could be called a PMO, or similar name, 2) The organisation should have a project
management methodology in place for managing projects, which could be very abstract or
comprehensive, 3) The PMO maturity model for improving the quality of PMO functionality
should be adopted or followed, (If there is none, assessment will be implemented), and 4) PM
unit or office is supported by top managers. As discussed, the three following cases were
selected and investigated in the last three chapters:
• SCIENCO is a research organisation which has a PMO with first level of maturity,
• GOVCO is a governmental organisation which has a PMO with second level of
maturity, and
• MINCO is a mining company which has a PMO with third level of maturity.
As depicted in Table 8-2 and Table 8-3, three cases have been compared through considering
the following criteria: 1) Nature of business, 2) Types of organisational chart, 3) Interviewees
and their position, 4) Functionality of their PMO, 5) PMO’s maturity level, 6) their current PM
systems, 7) their PM methodology, and 8) their challenges from a KM point of view. Both
tables present a snapshot of three cases to understand their general characteristics from a project
management point-of-view. As discussed earlier, the selected cases have various natures of
business which contribute to provide unbiased information for this research (Creswell 2009;
Gray 2009; Yin 2009).
The research findings revealed that each of the three cases have their own characteristics
from both KM and PM perspectives, by which they manage their project knowledge. For
222 Chapter 8 | DISCUSSION and RESULT
instance in SCIENCO, knowledge management is part of their activities as it is a research
organisation, however, some of the KM practices for managing project knowledge, especially
for reusing and transferring, are yet to be developed. On the other hand in GOVCO, awareness
of project knowledge management has been raised among project managers and senior staffs in
which they are developing useful systems to improve the quality of project through managing
the project knowledge. In addition, in the MINCO project, knowledge management is in the
priority in which there is an assigned employee in the PMO, i.e. project knowledge manager, to
develop and maintain the current systems for improving quality of project knowledge
management. These details will be discussed further in the next sections.
ORGANISATIONAL STRUCTURE 8.4
According to the research findings, each of the three case studies has adopted a matrix
organisation structure by which project staff could be managed by both project manager and
their functional manager (Project Management Institute 2013). In the weak matrix structure, the
functional manager’s authorities overrule the project manager, which means that the project
could be impacted by functional managers. The collected data from SCIENCO revealed that
the current structure is similar to a weak matrix, as functional managers have more power. This
means that the project could face challenges from a resource management point of view as the
project manager or coordinator has inadequate authority (Project Management Institute 2013).
The GOVCO has a balanced matrix structure in which responsibilities of resources are
equally shared between project manager and functional manager (Project Management Institute
2013). The research findings confirm this assumption in which some projects, functional
managers are assigned as project managers, as they get appropriate PM trainings. In addition, a
developed roles and responsibility document has defined the role of resources during project life
cycle. This means that in the GOVCO, with second level of maturity and a balanced matrix
structure, the issue of resource management among functional managers and project managers
has been addressed.
In a strong matrix structure, the project manager has adequate authorities for assigning
project staff in different projects, which means that one of the functional manager’s
responsibilities is to provide resources for project managers (Project Management Institute
2013). According to the research findings in MINCO, project managers have access to their
required resources as there are numbers of functions to assist them with preparing project
resources. This means that in MINCO with a third level of maturity and strong matrix structure,
the project resource management has appropriately been addressed in which few issues have
been recognised in this regard. In addition, the position of project knowledge manager has been
found in the MINCO PMO structure.
Chapter 8 | DISCUSSION and RESULT 223
According to the PMBOK (2013) there is a relationship between project management
authority and type of organisational chart, in which the stronger the matrix structure, the more
the project manager’s authority. The research findings revealed in the weak matrix structure, i.e.
SCIENCO with the first level of maturity, the authority of project managers was low, while in a
strong level of maturity, i.e. MINCO with third level of maturity, project managers have
adequate power to control the project resources. This means that in PMOs with a better maturity
level it should be expected there are fewer challenges from a resource assignment point of view.
These outcomes have led researchers to develop another research proposition as following:
There is correlation between project management maturity level, project managers’ authorities
as well as organisational types, as shown at Figure 8-1.
Figure 8-1 PMO level of maturity and project managers authorities (developed for this research)
Level of maturity • From first to fifth level of matuirty
Organisational chart
• Weak Matrix • Balance Matirx • Strong Matrix
project manager's Authrity
• Weak • Balance • Strong
224 Chapter 8 | DISCUSSION and RESULT
Table 8-2 A snapshot of three case studies (developed for this research)
Case study SCIENCO GOVCO MINCO
Nature of business Research Organisation State-Government Organisation Resource and Mining Enterprise
Type of organisational
chart Weak matrix Balance matrix Strong matrix
Numbers of Interviewees and
their position
Seven interviewees included one senior
manager, one program manager, two project
managers, one project staff, PMO staff, and
PMO coordinator
Seven interviewees included one senior manager,
one program manager, two project managers, one
project staff, PMO coordinator, and PMO manager
Six interviewees included one senior manager, one
program manager, two project managers, one project
planner, and PMO knowledge manager
Functionality of PMO
PMO has been developed in the last two years
to support organisational projects. PMO unit is
under the middle management level, with an
appointed PMO coordinator. PMO is
responsible to develop PM practices, however,
it has less authority to direct organisational
projects as well as project resources assignment
PMO has been established 4-5 years ago to be a
work as the centre of excellence PMO to provide
adequate services to projects to increase the quality
of project management. This means that PMO does
not directly manage projects. This PMO has a
manager who reports directly to senior manager. As
a centre of excellence, PMO controls quality of PM
as well.
PMO was established more six years ago and it has
been developed since then. The current PMO works
under senior managers and CEO of company with
numbers of staffs and managers. Also there is a KM
manager in place to oversee project knowledge
management. PMO has numbers of authorities on
behalf of company’s CEO and it could intervene to
change direction of project
Current systems that contribute to
project management
• SAP • Enterprise Opportunity Pipeline • Wiki • Off System Tools • Common Costing Framework
• SAP, • PMMate • Intranet • Risk Management system • AConnect • PM software such as MS project
• SAP • Hummingbird • Galileo • Intranet • Global Network • PM software such as MS project and
Primavera
Chapter 8 | DISCUSSION and RESULT 225
Table 8-3 A snapshot of three case stuides (continued )
Case study SCIENCO GOVCO MINCO
Level of PMO maturity and its characteristics
SCIENCO’s PMO maturity level is one which means:
• Benefits of project management yet to be
recognised, • No unique PM framework in place, • lack of PM tools and techniques, • Lip Services to project managers so they
have to manage project with different methods,
• PMs’ self-interest comes before organisational best Interest, and
• lack of investment for PM trainings
GOVCO’s PMO maturity level is two which means:
• Benefit of PM has been recognised by senior managers,
• There are some common processes for supporting PM,
• There are some PM guidelines in place, but a unique PM standard are yet to be developed,
• Importance of project cost, scope and quality have been recognised , and
• Training for project management has become an important need.
MINCO’s PMO maturity level is three which means :
• There is a unique - integrated PM methodology in place to demonstrate successful execution,
• Organisation has totally committed to the concept of project management,
• There is a corporate-wide culture to support informal project management and multiple-boss reporting,
• There is a developed sense of shared responsibility and accountability for the principles of project management
Current PM methodology
There is no unique PM methodology so
project managers are free to choose their own
method as they are not obligated to any
methods
There is a customised PM methodology in place but
it is not comprehensive enough to be forced ,
however, the process of developing unique
methodology is being managed
There is a unique and comprehensive PM
methodology which has been developed by PMO and
it should be followed during the management of all
organisational projects and PMO is responsible to
oversee all processes.
Challenges of PMO from KM methodology
1) Difficulties of searching and detecting required knowledge
2) Issue of locating and accessing right information and/or right expert
3) Lack of KM practices and processes during project life cycle
4) Lack of appropriate systems to support project KM
5) Issue of appropriate access to the existing systems
1) Lack of integration among current processes and systems
2) Issue of locating and accessing right information and/or right expert
3) Lack of KM practices KM processes during project life cycle
4) Issue of appropriate access to the existing systems
1) Inadequate practices to support knowledge transferring process
2) Issues with current systems to fully support knowledge capturing process
3) Unsatisfactory practices to appropriately support knowledge reusing process, and
4) Lack of training for current systems and applications
226 Chapter 8 | DISCUSSION and RESULT
PROJECT MANAGEMENT MATURITY LEVEL IN THREE CASE STUDIES 8.5
As depicted in Table 8-2, numbers of interviewees have been mentioned; for both SCIENCO
and GOVCO, 7 interviews were conducted, while six interviews were managed for MINCO.
The main criteria to finish conducting interviews was reaching “the redundancy of information”,
when the researcher was realising that the same information was being provided, then the
interview process was terminated. For both SCIENCO and GOVCO redundancy was observed
after 7 interviews, while in MINCO after 6 interviews the researcher realised that no new
information was added. This means that when interviewees started to repeat the similar
explanations, researcher preferred to stop interviews to prevent any redundancy issues in data
collection.
From the PMO maturity and functionality points of view, all three cases have different
characteristics. As shown at Figure 8-2, from a project lifecycle point-of-view, in general
MINCO has the most mature PMO, while SCIENCO’s PMO has the lowest maturity level. This
means that PM practices in SCIENCO have not been appropriately developed to support project
lifecycle, in comparison to MINCO and GOVCO. In addition, MINCO’s PMO has the best
maturity level, from project lifecycle point-of-view, among all three cases, which indicates that
the current PM processes in MINCO significantly impact on quality of projects.
Figure 8-2 Maturity of PMOs from project lifecycle perspective (developed for this study)
From a project knowledge area perspective, the research findings revealed similar outcomes
in which the maturity of MINCO is the best among all three cases, while SCIENCO has the
lowest maturity level. According to PMI (2008b), nine areas of project knowledge should be
assessed to examine the level of maturity in the PMO. The research findings indicated that the
0.64 2.14
1.71
1.21
2.50
2.79
2.00
2.29
2.07
3.93
3.29
2.79 0.0
1.0
2.0
3.0
4.0
5.0Initiation
Planning
Execution andmonitoring
Closing
SCIENCO GOVCO MINCO
Chapter 8 | DISCUSSION and RESULT 227
current PM practices in MINCO have been appropriately developed, in comparison to
SCIENCO and GOVCO. In other words, the existing PM practices in MINCO support all nine
knowledge areas, as shown in Figure 8-3. For instance, risk management is the most developed
PM practice in MINCO, while the current PM practices for procurement management are not as
developed as other knowledge areas. In addition, as it could be seen in Table 8-2, MINCO’s
PMO has developed a comprehensive project management methodology, while GOVCO is still
in the stage of uniting the existing PM methodologies, and SCIENCO’s PMO faces significant
challenges in this regard.
Figure 8-3 Maturity of PMOs from knowledge area perspective (developed for this research)
In general, the PMO maturity level in three cases indicates their status of project
management development. The research findings confirmed that from both the project lifecycle
and knowledge area, MINCO has the higher maturity level, i.e. three, GOVCO’s PMO has the
second level of maturity and SCIENCO has the lowest maturity level, i.e. one. According to the
current PM maturity models the higher level of maturity is a significant indication of the
advanced PM practices by which projects are supported through robust and reliable systems
(Kerzner 2005; Project Management Institute 2008b). In other words, MINCO’s projects
receive better support in comparison to GOVCO and SCIENCO’s projects. However, it should
be examined whether the PMO maturity level impacts on project knowledge management or
not. This means that if the research findings endorse the relation between PMO level of
maturity and project KM, then it could be claimed as one of the significant contributions of this
research. This hypothesis will be examined at the end of this chapter.
0.6 2.6
1.6
1.4
0.9
2.4
1.0
1.5
1.3
1.9 2.6
2.1
1.9
2.8
2.8
2.0
2.3
2.4
3.0 3.2
3.0
3.1
2.9
4.2
3.3
2.8
3.1
0.0
1.0
2.0
3.0
4.0
5.0Project Scope
Project Cost
Project Time
HRmanagement
Project QualityProject Risk
ProjectCommunicatio
n
ProjectProcurement
ProjectIntegration
SCIENCO GOVCO MINCO
228 Chapter 8 | DISCUSSION and RESULT
KNOWLEDGE MANAGEMENT PRACTICES IN VARIOUS LEVELS OF PMO 8.6
The first research question (RQ 1.How are KM practices and processes employed in the
PMOs) comprises three sub questions as followings: 1) what are the current challenges of the PMO
from a KM perspective, 2) what types of knowledge are required at each of following project phases, and
3) what kinds of KM practices are utilised in each maturity level of PMO). In this section each
question will be answered through integrating and analysing findings from the previous
chapters. At the end of this section the first question will be answered, as well as the first
research objective.
The Challenges of PMO from knowledge management perspective 8.6.1
As discussed in the previous chapters, numbers of challenges were recognised in all cases
from a KM point-of-view, which should be addressed by PMOs. As depicted in Table 8-3, in
total, the 10 following KM challenges have been developed through analysing more than one
hundred and sixty comments by using open and axial code technique: 1) Lack of appropriate
systems to support project KM, 2) Difficulties of searching and detecting required knowledge,
3) Issue of appropriate access to the existing systems, 4) Issue of locating and accessing right
information and/or right expert, 5) Lack of KM practices and processes during project life cycle,
6) Lack of integration among current processes and systems, 7) Issues with current systems to
fully support knowledge capturing process, 8) Inadequate practices to support knowledge
transferring process, 9) Unsatisfactory practices to appropriately support the knowledge reusing
process, and 10) Lack of training for current systems and applications.
1) Lack of appropriate systems to support projectKM
2) Difficulties of searching and detecting requiredknowledge
3) Issue of appropriate access to the existingsystems
4) Issue of locating and accessing right informationand/or right expert
5) Lack of KM practices and processes duringproject life cycle
6) Lack of integration among current processes andsystems
7) Issues with current systems to fully supportknowledge capturing process
8) Inadequate practices to support knowledgetransferring process
9) Unsatisfactory practices to appropriatelysupport knowledge reusing process
10) Lack of trainings for current systems andapplications
Chapter 8 | DISCUSSION and RESULT 229
Figure 8-4 Challenges of KM at different maturity levels (developed for this study)
In the next step, these challenges were examined in the Nvivo through employing queries
and relation functions. At this phase of analysis, some other factors such as level of maturity
and the current systems and procedures were taken into consideration, by which numbers of
valuable outcomes have been obtained, as shown at Figure 8-4. According to the research
findings, some of the current challenges are common among these cases which confirm the
same issues from a KM point-of-view, for instance, the issue of locating the right information
and lack of KM practices. In addition, some of the KM challenges in the PMO with a low level
of maturity have been addressed in the next or upper level of maturity. For instance, in
SCIENCO’s PMO with the first level of maturity the first two challenges (Lack of appropriate
systems to support project KM; and Difficulties of searching and detecting required knowledge)
were recognised, while these issues have been addressed in both GOVCO and MINCO. In a
similar manner, while both SCIENCO and GOVCO face issues number 3, 4, 5 ( Issue of
appropriate access to the existing systems; Issue of locating and accessing right information
and/or right expert; and Lack of KM practices and KM processes during project life cycle),
these challenges have been resolved in MINCO.
Furthermore, the research analysis revealed that both SCIENCO and GOVCO have faced
three common challenges, while SCIENCO and MINCO do not share any common challenge.
This means that the current practices in MINCO’s PMO have contributed to address those
issues that SCIENCO has still been challenged with, and similarly, the existing practices in
GOVCO have addressed the first and second challenges of SCIENCO. In addition, challenges 7
to 10 have been explored neither in SCIENCO nor in GOVCO, but they are main issues of
MINCO at a third level of maturity. This means that MINCO has gone to the level of maturity
in which it deals with new types of issues that are not the main concerns of other two cases.
In the next level of analysis, the types of challenges have been considered to shed more light
on the existing KM challenges in various levels of maturity. The first four mentioned challenges
are mostly associated with the current systems and procedure. This means that SCIENCO and
GOVCO, with low levels of maturity, are dealing with issues such as applications, tools, and
access to the current systems, while MINCO, with a higher maturity level, have addressed these
kinds of issues and currently it faces other types of challenges such as the collaboration of the
current systems and database. In addition, both SCIENCO and GOVCO’s employees have
generally mentioned their concerns about lack of practice for all KM process (challenges
number 4 and 5), while in MINCO, knowledge transferring and reusing have been especially
mentioned as their current issues. This is another finding to claim that PMOs with a higher level
of maturity deal with various types of KM challenges.
230 Chapter 8 | DISCUSSION and RESULT
The required types of knowledge in Project Management Offices 8.6.2
According to the research framework, eight types of project knowledge are important during
the project lifecycle: project management knowledge, knowledge about procedures, technical
knowledge, knowledge about clients, costing knowledge, legal and statutory knowledge,
knowledge about suppliers, and knowledge of who knows what. In the previous chapters, it was
discovered that the importance of each type of knowledge varies from one phase to another
phase. In this chapter, the general ranking of knowledge types will be discussed to analyse the
similarities and differences of required knowledge types at various levels of maturity.
Figure 8-5 Importance of knowledge types in various maturity level (developed for this research)
As can be seen in Figure 8-5, project management knowledge is the most important type of
knowledge at MINCO and GOVCO, while is the third one in SCIENCO. With regards to the
maturity level of the three cases, SCIENCO has the lowest and MINCO has the highest.
According to the research framework, at the lowest level of PMO maturity, the importance of
project management knowledge has been raised and there is no PM methodology in place, while
in the next level of maturity a PM framework should be in place to address the knowledge of
project management. This means that in SCIENCO’s PMO the importance of PM knowledge
has not been appropriately realised due to its level of maturity, while knowledge of project
management is the most important type of knowledge in both MINCO and GOVCO, as they
have a PM method in place. This could be an indication of increasing the importance of project
management knowledge at a higher level of maturity. In addition, one of the PMO’s
responsibilities is to oversee the employment of PM methodology in the organisational project
SCIENCO (ML=1)GOVCO (ML=2)MINCO (ML=3)0
2468
ProjectManageme
ntKnowledge
Knowledgeabout
Procedures
TechnicalKnowledge
KnowledgeaboutClients
CostingKnowledge
Legal andstatutory
Knowledge
Knowledgeabout
suppliers
Knowledgeof who
knows what
SCIENCO (ML=1) 6 3 3 8 5 3 4 7
GOVCO (ML=2) 8 7 5 6 3 2 1 5
MINCO (ML=3) 8 5 7 3 6 2 1 4
Chapter 8 | DISCUSSION and RESULT 231
to control how PM knowledge is applied in various projects, which increases the importance of
PM knowledge.
Knowledge about procedures is the next type of knowledge which could be used with
project knowledge management. As depicted at Figure 8-5, this type of knowledge is the second
most important one in GOVCO, while it is the fourth in MINCO and sixth in SCIENCO.
According to Kerzner (2009) the second level of maturity is called “common process”, in which
the PMO focuses on providing practical processes and procedures to improve the quality of
project management. The direct observation findings revealed that there are more than sixty
processes in the GOVCO which justifies the importance of the type of knowledge in this case.
In other words, the importance of procedure knowledge in the second level of maturity is
consistent with both the research framework and the current literature. However, in SCIENCO,
procedures are not important as the PMO has just been established and it has not gone to the
next level to raise the importance of knowledge about procedures. In addition, since MINCO
has passed the second level of maturity, knowledge about procedures is not as important as it
was before.
Technical knowledge is the second most important type of knowledge in MINCO, while it is
fourth in GOVCO and sixth in SCIENCO. The ranking of technical knowledge is somehow
similar in MINCO and GOVCO, but in SCIENCO, participants believe that this type of
knowledge is not as vital as other knowledge types such as costing or PM knowledge. This
means that SCIENCO’s employees have fewer concerns about technical knowledge as they
believe that it exists in the organisation. In other words, SCIENCO is a research organisation
with numbers of scientists and researchers which they could trust with their own technical
knowledge. Therefore, they prefer that the PMO assist them with provision of other types of
knowledge, as they have fewer challenges with technical knowledge.
Knowledge about client is the most important type of knowledge in SCIENCO, and the third
one in GOVCO, while it has been ranked as the sixth most important knowledge type in
MINCO. According to the PMBOK (2013) knowledge about client is the crucial element to
increase the rate of project success. This assumption has been confirmed in both SCIENCO and
GOVCO, but in MINCO, participants believe that there are other priorities ahead of knowledge
about client. In order to shed more light on this issue, types of PMO were considered, and it was
revealed that both SIENCO and GOVCO have numbers of clients from outside of organisations,
while the majority of MINCO’s projects are undertaken to improve and maintain organisational
business. In other words, external clients do not play a crucial role in MINCO’s projects, while
in GOVCO and SCIENCO, clients are the main resource of organisational income.
Costing knowledge is the third and fourth important type of knowledge in MINCO and
SCIENCO, while it is the sixth in GOVCO. This is the first time that both MINCO and
232 Chapter 8 | DISCUSSION and RESULT
SCIENCO have similar rankings of knowledge type in which both emphasise the importance of
costing knowledge in their projects, while GOVCO’s respondents do not have the same
thoughts. To analyse this difference, the types of PMOs have been taken into consideration in
which both SCIENCO and MINCO have a PMO which intervene in the projects, while
GOVCO’s PMO is the centre of excellence so it is not responsible for project implementation.
This means that in GOVCO, the PMO is not responsible during project implementation so cost
of project is not as important as other types of knowledge, while in MINCO and SCIENCO both
have many concerns about costs of project, as project managers are responsible for project
failure or success. In other words, types of PMO could impact on the ranking of project
knowledge types, as the research findings revealed.
Both legal knowledge and knowledge about suppliers have been similarly ranked as the
lowest important types of knowledge in all three cases. This means that participants in the
selected cases have consistent thoughts in ranking these two types of knowledge. In other
words, they believe that the provision of other types of knowledge is more important for them at
this stage. In addition, it could be inferred that in the higher level of maturity, i.e. four and five,
the PMO could focus on facilitating the access of legal knowledge as well as knowledge about
suppliers, as other types of knowledge have been addressed appropriately.
Knowledge about who knows what is the second most important type of knowledge in
SCIENCO, while it is fifth in MINCO and equal to fourth in GOVCO. This means that for
SCIENCO’s employees it is a crucial issue to find the right person with right information. As
discussed in the previous section, “Issue of locating and accessing right information and/or right
expert” is one of the challenges that SCIENCO and GOVOC are faced with. This is consistent
with their ranking of knowledge types as they believe that finding the right person is a
significant challenge, so the PMO should assist them with accessing “knowledge of who knows
what”. This means that SCIENCO’s PMO could address one of the recognised challenges
through facilitating the access to “knowledge of who knows what”. In addition, direct
observation revealed that both MINCO and GOVCO have addressed this issue through
providing a reliable system and procedures.
In summary, it could be concluded there are two important factors which significantly
impact on importance of knowledge types: 1) level of PMO maturity and the existing systems,
and 2) types of PMO, whether it is a centre of excellence or practical. This means that a higher
level of maturity is an indication of the current system efficiencies by which some of knowledge
types have been appropriately addressed. In addition, type of PMO is another influential factor
for ranking required knowledge type. For instance in the centre of excellence, the PMO does not
intervene in projects and it is not responsible for project success and failure, while the practical
PMO is the opposite. Therefore, some types of knowledge are very important in PMOs, such as
Chapter 8 | DISCUSSION and RESULT 233
costing knowledge, while it is not important in the centre of excellence. This means that above
mentioned factor should be considered for ranking the importance of types of knowledge.
KM PROCESSES AND KM PRACTICES AT VARIOUS LEVELS OF MATURITY 8.7
This section aims to answer one of the sub-questions of the first research question, i.e. what
kinds of KM practices are utilized in each maturity level of PMO, through analysing and
comparing the research findings from the previous chapters. To do so, each KM process has
been considered alongside its KM practices, and then they have been investigated through
employing the research framework. In addition, Nvivo and MS Excel were used as the main
tools for this part of analysis. This analysis consists of discussing four KM processes in separate
categories to get insightful information about KM practices in various levels of maturity.
Figure 8-6 Numbers of the coded comments for KM processes (developed for this study)
In a nutshell, as shown in Figure 8-6, from a knowledge capturing perspective MINCO and
GOVCO have the highest number of codes, while SCIENCO has the lowest one. On the other
hand, the number of MINCO and SCIENCO’s KM practices for supporting knowledge creation
is more than GOVCO. In addition, the data analysis shows that GOVCO has the most comments
for knowledge transferring while SCIENCO has the lowest. Also, knowledge reusing has the
best situation in MINCO among other two cases. In general, MINCO has the highest number of
KM practices for supporting the KM process, while SCIENCO has the lowest. In other words,
the research findings revealed the PMO with higher maturity has better KM practices in place,
in comparison to the PMO with lower maturity level. This could be a significant finding for this
research which will be examined later. In the next sections each KM process will be discussed,
accordingly.
Knowledge Capturing 8.7.1
According to the research framework, knowledge capturing is facilitated through employing
numbers of KM practices, as depicted in Figure 8-7. As discussed in the previous chapters,
KnowledgeCapturing
KnowledgeCreation
KnowledgeTransferring
KnowledgeReusing
SCIENCO (ML=1) 75 56 39 6
GOVCO (ML=2) 132 31 83 6
MINCO (ML=3) 129 60 51 14
0
20
40
60
80
100
120
140
234 Chapter 8 | DISCUSSION and RESULT
these practices were examined in each case individually. In this section each KM practice will
be discussed to explore the process of project knowledge creation in various levels of maturity.
The research analysis revealed that DMS in the most frequently mentioned KM practices for
facilitating knowledge capturing. Document management system (DMS) is a set of forms,
software and procedures to record and track organisational documents (Spalek 2012). It is a
recommended practice to capture project knowledge by which project information could be kept
appropriately (Project Management Institute 2013). The comparison among cases explored that
all participants believe that this practice is the most utilised KM practice for knowledge
capturing, as depicted in Figure 8-7. This means that all cases have realised the importance of
DMS for knowledge capturing, but they are in different situations in this regard. In MINCO’s
PMO, there is a robust and reliable DMS, which is supported through a number of software and
processes, while in SCIENCO it is yet to be improved, as the majority of the current DMS has
not been electronically facilitated.
Figure 8-7 Knowledge capturing in various levels of maturity (developed for this study)
Formal and informal events, such as meetings and any kinds of gathering, are the second
most frequently mentioned KM practice among other KM practices. According to the research
framework, these practices could be used for all KM processes and they are practical events to
support “communication and networking” (Julian 2008; Nissen, et al. 2000). In other words,
formal and informal events are one of the most influential practices for managing project
knowledge. The research analysis revealed that all three cases have realised the importance of
formal and informal events for project KM, however, the usage varies from one case to another.
For instance, in SCIENCO, formal and informal events are mostly employed for knowledge
creation, while in GOVCO and MINCO they are used for knowledge transferring and capturing
0
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30
40
50
60
70
80
Data base
Document Management System (DMS)
Expert locator
File Management System (FMS)
Formal or Informal events
Frequently Ask Questions (FAQ)
Intranet
Knowledge detection tools
Knowledge inquiry system
Knowledge repositories
Management Information System (MIS)
Chapter 8 | DISCUSSION and RESULT 235
purposes. In other words, a PMO with higher maturity level has various usages of formal and
informal events, as they are facilitating project communications through formal and informal
networking.
The third frequently mentioned KM practice for knowledge capturing is both MISs and DBs.
Management information system (MIS) is the advanced level of database (DB) by which
decision making is facilitated (Koskinen 2010). This means that the DB includes raw
information, while the MIS comprises the processed information to be used for decision
making. The research findings revealed that numbers of DBs in SCIENCO are more than in
MINCO and GOVCO. On the other hand, both MINCO and GOVCO have developed numbers
of MISs in place, while SCIENCO is yet to develop appropriate MIS to manage project
knowledge. This confirms that the maturity of a PMO has significant impact on addressing
MISs through developing the existing DBs. In other words, a PMO with higher level of maturity
should have robust MISs for knowledge capturing process, while a PMO with a lower maturity
level should focus on improving MISs through developing the current DBs.
Intranet is the fourth most frequently mentioned KM practice in this study, which is used by
all three cases; however, its frequency is not as strong as the previously discussed practices. An
intranet is an internal web-based network to share information within an organisation (Aubry, et
al. 2010). According to the research framework, the intranet could be utilised for all KM
process except knowledge creation. The research findings revealed that this practice is used by
all three cases for various purposes, specifically knowledge capturing and transferring.
However, SCIENCO’s intranet is not as robust as the other two cases. In addition, MINCO has
developed a reliable intranet which could be accessed from all around the globe. In other words,
PMOs with better maturity levels have developed a more useable intranet to facilitate project
knowledge management.
Some of the proposed KM practices such as expert locater have not been recognised in
PMOs with a lower maturity level. As discussed earlier, “finding the right person or
information” was recognised as a challenge in SCIENCO and GOVCO, while it has been
addressed in MINCO. Expert locator is a practice to resolve the mentioned issue in which it was
addressed in MINCO, which is yet to be addressed in SCIENCO. This shows the consistency
between the current challenges and PM practices. On the other hand, there are three practices
which have not been recognised in any case: knowledge detection tools; knowledge inquiry
system; and frequently asked question (FAQ). This finding indicates that the missing KM
practices will be addressed in the next levels of maturity. In other words, KM practices should
be developed based on maturity of the PMO and the readiness of the organisations.
In conclusion, DMS, formal and informal events, DBs, and MISs are the most frequently
mentioned KM practices for facilitating knowledge capturing, which are employed in all three
236 Chapter 8 | DISCUSSION and RESULT
cases. According to the research findings, some KM practices either have not been recognised,
such as the expert locator, or are yet to be developed, such as the intranet, in SCIENCO with
first level of maturity. In addition, there are three practices that have not been addressed in any
of the cases. This means that maturity level of a PMO has a significant relationship with
utilising KM practices, in which the higher the level of maturity the stronger and reliable are
the KM practices.
Knowledge creation 8.7.2
The research framework advises eleven practices to support knowledge creation, as shown in
Figure 8-8. Knowledge creation has received the highest data frequency in SCIENCO, while it
is lowest in the GOVCO, as depicted in Figure 8-6. This is consistent with the nature of
SCIENCO’s business as a research organisation which manages projects to create knowledge.
On the other hand, GOVCO’s PMO, as the centre of excellence, does not interfere in projects
which means that it has less contribution for creating knowledge in projects. In other words,
SCIENCO and MINCO’s PMO significantly contributes to knowledge creation, while
GOVCO’s PMO is a centre of excellence so knowledge creation is not the first priority.
According to the research findings, formal and informal events are the most frequently
mentioned practices for knowledge creation in all three cases. According to Nonaka (2001) this
practice is used for knowledge creation through socialisation in which the owner of knowledge
communicates with others to create or transfer his/her knowledge. Formal and informal events
are the most frequently mentioned KM practices for knowledge creation in SCIENCO in which
participants believe that knowledge is mostly created through their social gathering or friendly
events. During direct observation, it was explored that SCIENCO’s PMO does not have a
significant role to facilitate these kinds of events, while in GOVCO and MINCO, the PMO
contributes to manage social events through facilitating forums or social gatherings. This means
that PMOs with higher maturity have realised the importance of formal and informal events to
manage project knowledge, which is consistent with the research framework.
Chapter 8 | DISCUSSION and RESULT 237
Figure 8-8 Knowledge creation at various levels of maturity (developed for this study)
The community of practices is the second most frequently mentioned KM practice for
facilitating knowledge creation. Community of practice is a group of experts with various
specialties which gather together to form a team for different purposes (Yazici 2009).
According to the research outcomes, community of practice is the most frequent-mentioned KM
practice for knowledge capturing in MINCO and GOVCO, while it is the fifth one in
SCIENCO. This means that community of practice has not been appropriately developed in
SCIENCO, with a lower maturity level. As discussed earlier, expert locator is a challenge for
SCIENCO, therefore it could be an issue to find the right experts in order to manage the
community of practices for knowledge creation purposes. This means that a community of
practices should be improved at the lower levels of maturity, while it is considered as an
important practice for knowledge creation at higher maturity levels.
The research findings revealed that research service and deductive and inductive thinking are
the fourth and fifth most frequently mentioned KM practices in total, however, both are yet to
be developed in GOVCO. In others words, little evidence was found to support these two
practices in GOVCO. As discussed, GOVCO’s PMO has been deigned to operate as the centre
of excellence, which means that it doesn’t involve project implementation. This means that
GOVCO’s PMO does not significantly contribute to knowledge creation at execution phase,
while both MINCO and SCIENCO’s PMOs, as practical PMOs, are involved in all project
phases, so they contribute to the knowledge creation process. In other words, in practical PMOs,
knowledge creation is facilitated through a number of practices such as community of practice
and research services. For instance, research services play a crucial role at the initiation phase in
MINCO by which the project feasibility study is managed to decide whether the project is
viable or not. Also, deductive and inductive thinking methods, such as brain storming and think-
tank, are managed to discuss project risk management in order to create the knowledge of risk
05
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25
30
Best Practice Cases
Community of practices
Data mining
Decision support system (DSS)
Deductive & Inductive thinking
Documentation search
Experience Report
Expert systems (ES)
Informal and formal Event
Knowledge Broker
Research services
238 Chapter 8 | DISCUSSION and RESULT
treatment plans. So, it could be concluded that a PMO with higher level of maturity should
facilitate both mentioned practices to contribute to the knowledge creation process.
According to Barclay and Osei-Bryson (2010), the PMO is a knowledge broker which could
facilitate creation of knowledge through facilitating the communication among knowledge
owners. The research findings explored that both MINCO and GOVCO’s PMOs have realised
their role as a knowledge broker in organisational projects, however, this is yet to be addressed
in SCIENCO’s PMO. In other words, a PMO with higher level of maturity has found their role
as an agent through which knowledge could be communicated among different groups of
project stockholders, while this role is yet to be realised.
There are a number of KM practices such as data mining and decision support systems
(DSS) that are yet to be addressed in the current case studies. In other words, little evidence was
found to support the mentioned practices in the selected cases. According to the current
literature, data mining and DSS are the advanced level of MIS and DBs which takes time for an
organisation to transform the current MIS to DSS (Koskinen 2010). This means that these
practices could be developed in the next level of maturity, as the current level is not capable
enough for such a development.
In summary, informal and formal events and community of practice are the most frequent-
mentioned KM practices in the selected cases for the purpose of knowledge creation. The
research findings revealed that type of PMO is an influential factor for facilitating knowledge
creation in which if a PMO is a centre of excellence, then it could not interfere in a project, and
consequently it will have less influence on facilitating the knowledge creation process. In
addition, the PMO maturity level impacts on selecting the type of KM practices in which the
higher the level of PMO, the more advanced the KM practices.
Knowledge Transferring 8.7.3
According to the research framework, eleven KM practices are employed to transfer project
knowledge, as depicted at Figure 8-9. The research findings explored that knowledge
transferring has obtained the highest data frequency in GOVCO, while it is lowest in
SCIENCO, as shown in Figure 8-6. In other words, despite the fact that GOVCO has the second
level of maturity, it has better knowledge transferring in comparison to MINCO and SCIENCO.
As discussed earlier, GOVOC’s PMO has the lowest rank in knowledge creation because of the
nature of PMO as the centre of excellence. So this means that GOVCO’s PMO has focused on
developing knowledge capturing and transferring, since it does not interfere in organisational
projects. It could be included that if the PMO has been designed to be a centre of excellence,
then the main focus of PMO should be on facilitating knowledge capturing and transferring
processes, at low or medium level of maturity.
Chapter 8 | DISCUSSION and RESULT 239
Figure 8-9 Knowledge transferring at various levels of maturity (developed for this study)
The research outcome revealed that formal and informal events are the most frequently
mentioned KM practices to support knowledge transferring, in three cases. The research data
analysis explored that GOVCO’s PMO has the strongest system to support these kinds of events
through managing some methods such as lunch forums, while both MINCO and SCIENCO are
yet to be developed from this point-of-view. In other words, GOVCO’s PMO, as a centre of
excellence, has focused on developing more practices for knowledge transferring at this level of
maturity. This means that knowledge transferring is considered as the second most important
KM process in GOVCO, after knowledge capturing, while it is the third most important KM
process in both MINCO and SCIENCO.
As shown in Figure 8-9, communication channels are the second most frequently mentioned
KM practices to facilitate knowledge transferring in all three cases. Similar to formal and
informal event, GOVCO has the highest frequency to support communication channels. This
means that numbers of tools such as email, video conference and phone are mainly used at these
organisations for knowledge transferring purposes. In addition, participants in MINCO and
GOVCO believe that there are numbers of communication channels in place to facilitate
knowledge transferring, while in SCIENCO, communication channels are not as developed as
the other two cases. It could be concluded that communication channels should be gradually
improved, as one of basic and fundamental tools for knowledge transferring, from lower to
higher levels of maturity.
Training and mentoring are the third most frequent mentioned KM practices for knowledge
transferring. The research findings revealed that the importance of training for transferring
project knowledge that has been realised by all cases, depends on their maturity level. For
instance, in MINCO and GOVCO, training and mentoring procedures have been appropriately
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Communication channels
Database
Discussion forums
Electronic bulletin board
Formal and informal events
Intranet
Knowledge directories
Knowledge list
Training& mentoring
Video and Tele Conference meeting
Yellow page
240 Chapter 8 | DISCUSSION and RESULT
developed, while in SCIENCO this KM practice is yet to be appropriately developed. Direct
observation that explored training and mentoring in MINCO is supported through some tools
such as induction and mentoring programs, while in SCIENCO participants believe the current
training system does not meet their expectation. In addition, training is still a challenge for all
cases, specifically MINCO (see section 8.6.1). In other words, training and mentoring still need
to be developed in higher levels of maturity, i.e. fourth and fifth.
As Figure 8-9 represents, data bases and intranet are the fourth most frequently mentioned
practices to facilitate knowledge transferring. As discussed earlier, according to the research
framework, DBs and intranet could be used for supporting both knowledge capturing and
transferring. The research findings revealed that MINCO and GOVCO have developed their
DBs, while in SCIENCO’s PMO the current DBs are yet to be appropriately developed.
According to the study, outcomes from the current DBs in all cases have not been appropriately
utilised for knowledge transferring purposes, as all cases are still faced with the issue of system
integration. In other words, all three cases have different situations in this regard in which
MINCO’s DBs are fairly stronger than other cases but they have not been collaborated with
current systems, while GOVCO and SCIENCO both are in the stage of developing the current
DBs to satisfy business requirements.
According to the research findings, the other KM practices for knowledge transferring have
not been either developed or addressed in the selected cases. For instance, little evidence was
found to support knowledge list, yellow page, and knowledge directories which means these two
practices should be addressed in the next level of maturity. In addition, little evidence was
recognised to support discussion forums and video conference meeting which means they
should be developed to satisfy current expectations. This is another reason to advise that KM
practices should be developed with regards to PMO’s capability, and consequently PMO
maturity level.
In summary, formal and informal, training and mentoring, and communication channels are
the most frequently mentioned practices to facilitate the knowledge transferring processes. As
discussed earlier, formal and informal events could facilitate all KM processes, so it should be
one of the most important priorities for PMOs to improve the quality of project knowledge
management. The research findings confirmed all cases have realised the importance of formal
and informal events; also this is consistent with the findings of similar research in SCIENCO by
Wiewiora, et al. (2010). Training and mentoring are other KM practices which are used by all
three cases, however, they are yet to be developed in all cases, specifically in SCIENCO. In
general, six out of eleven practices for knowledge transferring are yet to be developed or
addressed in the selected cases. This means that knowledge transferring need to be improved in
the next level of maturity.
Chapter 8 | DISCUSSION and RESULT 241
Knowledge Reusing 8.7.4
According to the research framework a number of practices could be used to manage the
project knowledge reusing process, as depicted at Figure 8-10. As can be found in Figure 8-10,
knowledge reusing has some common practices with other KM processes such as capturing and
creation. For instance, data mining could be used to support knowledge creation and reusing,
which means that knowledge reusing has relationships with other KM processes. According to
Owen, et al. (2004), knowledge reusing is dependent on knowledge transferring and capturing,
so this assumption has been adopted in the research framework. According to the research
findings, knowledge reusing has the minimum data frequency among other KM processes. As
Figure 8-10 depicts, a small number of knowledge reusing practices have been recognised in the
selected cases. Having said that, their frequency indicates that they are yet to be developed
accordingly. This is consistent with other research findings as it was revealed that knowledge
reusing has been mentioned as the main issue in three cases, especially in the MINCO
(section 8.6.1).
According to the research framework, a robust knowledge reusing process requires a reliable
knowledge transferring and capturing system. The research findings have explored that all
selected cases have been in the processes of developing other KM processes, therefore it could
be expected that knowledge reusing should be their next priority. Specifically in the MINCO’s
PMO it was realised that participants have directly mentioned their issues with knowledge
reusing as they believe that other KM processes have been appropriately developed.
Figure 8-10 Knowledge reusing at various levels of maturity (developed for this study)
In summary, knowledge reusing is the least frequently mentioned KM practices which is yet
to be developed in all three cases. In fact, some evidence was recognised in the selected cases
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Data base
Data mining
Document Management System
Electronic notice board
Expert systems
Formal or informal meetings
Intranet
Knowledge detection tools
Knowledge map
Lesson learnt
Yellow page
242 Chapter 8 | DISCUSSION and RESULT
for the purpose of supporting knowledge reusing, however, respondents believe that knowledge
reusing is not appropriately supported through current KM practices. According to the research
framework, knowledge capturing and transferring provide the required basics to facilitate
knowledge reusing process. This means that PMOs should focus on developing other KM
processes such as knowledge creation and knowledge capturing before initiating the knowledge
reusing process. Consequently, development of knowledge reusing should be considered at
fourth or higher maturity level.
PMO’S CONTRIBUTIONS TO KNOWLEDGE MANAGEMENT 8.8
In the last section the first research questions have been discussed. In this section the second
research question will be answered through discussing the importance of KM processes and
addressing the appropriate KM practices for three maturity levels. Similar to previous sections,
Nvivo and Ms Excel were used as the analysis tools alongside Grounded theory.
The importance of KM processes in various levels of PMO 8.8.1
The first part of the second research question aims to rank the importance of KM processes.
In the first level of analysis the rank of KM processes was managed, regardless of the various
project phases. According to the research findings knowledge capturing has been ranked as the
most important KM process in all three cases, while knowledge reusing has received the lowest
ranking order, as depicted in Figure 8-11. As discussed in the previous section, knowledge
capturing is the most frequently mentioned KM process and on the contrary knowledge reusing
is the least frequently mentioned process in all three cases. These two findings show similar
outcomes in three selected cases in which the ranking of KM processes are consistent with
research outcomes in terms of data frequency.
In addition, knowledge creation is the second most important KM process in SCIENCO and
MINCO, but it is the third important process in GOVCO. In a similar manner, knowledge
transferring is the third important process in SCIENCO and MINCO, while it is the second in
GOVCO. The research findings revealed similar ranking in both SCIENCO and MINCO; on the
contrary, ranking of knowledge creation and transferring in GOVCO is different from the two
other cases. In other words, the importance of knowledge creation and knowledge transferring
in SCIENCO and MINCO is similar, while they have different rankings in GOVCO, as shown
in Figure 8-11.
Chapter 8 | DISCUSSION and RESULT 243
Figure 8-11 Importance of KM processes in project lifecycle: All cases (developed for this study)
As discussed, GOVCO’s PMO is a centre of excellence so it is not practically involved in
project execution phase, while the PMO is involved at the execution phase in both projects in
SCIENCO and MINCO. Therefore, according to the findings, knowledge creation is the second
most important KM process in practical PMOs, while knowledge transferring is considered as
the second most important KM process when the PMO operates as a centre of excellence. In
other words, in the centre of excellence, importance of knowledge capturing and reusing
remains the same, i.e. first and forth, while knowledge transferring and creation are the second
and third most important KM process.
In a consistent manner these findings are similar to the previous findings in terms of data
frequency. As discussed earlier, knowledge creation and transferring are the second and third
most frequently mentioned KM processes in SCIENCO and MINCO, while they are the
opposite in GOVCO. In other words, knowledge transferring has been ranked as the second
most frequently mentioned KM process in GOVCO, which is similar to its ranking from a
knowledge importance point-of-view. Therefore, the research findings revealed similar ranking
from both a data frequency point of view, and the importance of KM perspective.
As discussed in section 8.6.1, the types of PMO challenges vary from one case to another.
For instance in SCIENCO knowledge capturing is a major concern, while MINCO’s
participants have mentioned their issues with knowledge reusing and transferring. This means
that maturity of PMO has correlation with the recognised issues. In other words, a PMO with
higher maturity level has addressed some of the concerns which still exist in a PMO with lower
maturity level. This is consistent with the research framework, as it advises to improve the
quality of KM in a gradual and steady manner. Therefore, the mentioned ranking of the KM
process should be employed through considering both the PMO maturity level and type of KM
challenges.
Capturing
CreatingTransferringReusing
01234
SCIENCO(ML=1) GOVCO
(ML=2) MINCO(ML=3)
SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Capturing 4 4 4
Creating 3 2 3
Transferring 2 3 2
Reusing 1 1 1
Project Lifecycle
244 Chapter 8 | DISCUSSION and RESULT
For instance, in SCIENCO’s PMO, with first level of maturity, knowledge capturing was
ranked as the most important and frequently mentioned KM process (see section 8.7.1
and 8.8.1). In addition, SCIENCO faces significant issues in regards to the current systems for
capturing project knowledge (see section 8.6.1). According to the research framework,
knowledge capturing should be developed in the first level of maturity. This means that
SCIENCO’s PMO should focus on improving the knowledge capturing practices as the first
priority, as knowledge capturing is in the first priority and the current challenges are mostly
related to lack of KM practices in this regard.
On the other hand, in MINCO’s PMO, with the third level of maturity, knowledge
transferring and reusing were ranked as the third and fourth most important and frequently
mentioned KM processes. The research findings revealed that MINCO faces some significant
issues for reusing and managing project knowledge (see section 8.6.1). This means that in
MINCO there is a reliable system in place to facilitate knowledge capturing and creation,
however, knowledge reusing and transferring should be addressed. According to the research
framework, all KM processes should be developed in the third and fourth level of maturity.
Therefore, MINCO’s PMO should focus on improving knowledge transferring and reusing
practices, in order to increase the level of maturity.
How PMO can contribute for managing the project knowledge 8.8.2
In this section the second research question will be completely answered through discussing
the PMO’s contributions to manage project knowledge. To do so, four KM processes and their
sub-processes will be investigated to explore project KM in various level of maturity. Data
frequency will be used as the main analysis input through using Nvivo and Ms Excel in order to
compare project KM in the three selected cases.
According to the research framework, knowledge capturing comprises four KM sub-
processes, as shown in Table 8-4. As discussed earlier, knowledge capturing is the most
frequent and important KM process in all three cases. In addition, it was explored that
knowledge capturing still faces some issues in the mentioned cases (see section 8.6.1). So on
one hand knowledge capturing is the most developed KM process, and on the other hand it
needs to be improved from some other aspects. In order to explore the priority for development
of knowledge capturing, the sub-processes of knowledge capturing were considered, as depicted
in Table 8-4. As it can be found from the following table, data frequency and maturity level are
consistent and the PMO with higher maturity level has better data frequency to support KM
practices.
Table 8-4 Knowledge capturing's sub-processes in various PMOs (developed for this study)
Sub-process Associated Practices SCIENCO (ML=1)
GOVCO (ML=2)
MINCO (ML=3)
Chapter 8 | DISCUSSION and RESULT 245
Knowledge Identification
• Expert locator • Formal and informal
event
• Knowledge detection tools
• Knowledge repositories
16 32 19
Knowledge Storing
• Data base • Formal and informal
event
• Document Management System (DMS)
56 100 118
Knowledge Classification
• Document Management System (DMS)
• Frequently ask questions
• Intranet
• File management system
• Management information system(MIS)
49 95 105
Knowledge Selection
• Knowledge inquiry system (KIS)
• Data base
• Frequently ask questions (FAQ) 18 6 17
The data frequency analysis revealed that both knowledge storing and knowledge
classification have been relatively developed in the three selected case studies, while knowledge
selection and identification are yet to be improved, as shown in Table 8-4 and Figure 8-12. This
means than more than 80% of the current KM practices facilitate knowledge storing and
classification. In other words, the majority of the PMOs’ activities have been focused on
addressing knowledge storing and classification. Therefore, it is plausible to face some
challenges in regards to the other two sub-processes, i.e. knowledge selection and identification.
For instance, participants have mentioned their concerns about finding the right expert, in both
SCIENCO and GOVOC. This is a strong indication for the PMOs in order to focus on
addressing the undeveloped KM processes, identification and selection, in order to address the
current issues from a KM point-of-view.
In addition, data analysis revealed that knowledge storing has higher frequency in the three
cases, in comparison to knowledge classification. This means participants believe that
knowledge storing practices, such as DBS and MISs, are important as they are employed to
support other KM capturing practices such as Internet and FAQ. Similarly, the research analysis
revealed that knowledge identification has the higher frequency in comparison to knowledge
selection. So, it could be concluded that development of knowledge identification should be
prioritised before developing the knowledge selection.
246 Chapter 8 | DISCUSSION and RESULT
Figure 8-12 Knowledge caprtuing's sub-processes (developed for this study)
According to the research findings it could be recommended that in order to develop
knowledge capturing in a PMO with first level of maturity, the development of knowledge
storing should be the first priority. At the same time, basic practices shall be addressed to
improve the knowledge classification process. In the second level of maturity, both knowledge
classification and storing should be constantly improved, but the development of knowledge
identification should be the first priority. At the same time, some basic practices to address the
knowledge selection should be considered. In the third level of maturity, knowledge
classification, storing and identification should be continuously improved, however, knowledge
selection should be significantly developed to address all four sub-processes of knowledge
capturing. These recommendations have been graphically represented in the following figure
and they will be used as the research propositions to develop KM processes in the PMOs.
Knowledge Identification
Knowledge Storing
Knowledge ClassificationKnowledge Selection
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
SCIENCO(ML=1) GOVCO
(ML=2) MINCO(ML=3)
SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Identification 11.51% 13.7% 7.3%
Knowledge Storing 40.29% 42.9% 45.6%
Knowledge Classification 35.25% 40.8% 40.5%
Knowledge Selection 12.95% 2.6% 6.6%
Chapter 8 | DISCUSSION and RESULT 247
Figure 8-13 K. capturing’s sub processes in various level of maturity (developed for this study)
248 Chapter 8 | DISCUSSION and RESULT
As discussed, knowledge creation is the second most important KM process in SCIENCO
and MINCO, but is the third in the GOVCO. According to the research framework, knowledge
creation has four sub-processes, as depicted in Table 8-5. These processes were investigated in
the selected cases and it was found that Socialisation and Externalisation are the most
frequently mentioned processes; in contrary the data frequency for Combination and
Internalisation is not as strong as for the other two processes. This means that from participants’
points-of-view the current KM practices mostly support Socialisation and Externalisation, while
Combination and Internalisation are yet to be developed.
Table 8-5 Knowledge creation’s sub-processes in various PMOs (developed for this study)
Sub-process Associated Practices SCIENCO (ML=1)
GOVCO (ML=2)
MINCO (ML=3)
Socialisation • Formal and informal event
• Workshops & seminar
• Community of practices
32 16 32
Externalisation
• Workshops & seminar • Deductive & Inductive
thinking
• Experts system • Experience Report • Community of
practices 21 13 28
Combination
• Community of practices (COP)
• Best Practice Cases (BPC)
• Knowledge Broker • Data mining • Documentation
search
5 14 32
Internalisation • Research services • Simulation • Experimentation 12 0 13
On the other hand, it was revealed that there are numbers of issues in regards to knowledge
creation in all cases, especially in MINCO and SCIENCO. For instance, SCIENCO’s
participants believe that PMO does not strongly contribute to project management and it needs
to be developed in this regard. In addition, some practices such as Expert systems and Data
mining have not been recognised in the selected cases. This means that knowledge creation
needs to be improved in project environments through addressing appropriate practices. To do
so, knowledge creation’s sub-processes have been analysed to propose suitable KM practices
for each level of maturity.
According to the research framework, knowledge Socialisation is the most frequently
mentioned practice to facilitate knowledge creation, as shown in Table 8-5 and Figure 8-14. The
data analysis indicated that some practices such as formal and informal events, and community
of practice have been developed in the three cases, but knowledge creation through seminars
and workshops needs to be improved in SCIENCO. Therefore, SCIENCO should focus on
addressing the mentioned practices for the next level of maturity. So it could be proposed that in
order to facilitate knowledge creation in PMO at the first level of maturity, Socialisation should
be the first priority. In addition, formal and informal events and community of practices shall be
Chapter 8 | DISCUSSION and RESULT 249
addressed in the first level of maturity, while seminars and workshops should be developed in
the second level of maturity.
Figure 8-14 Knowledge creation's sub-processes in three case studies( developed for this study)
The research findings revealed that Externalisation is the second most frequently mentioned
practice to support knowledge creation in the three cases, as presented in Table 8-5 and
Figure 8-14. Further analysis explored that “community of practice” and “deductive and
inductive thinking” have been relatively developed in the selected cases, while seminars and
workshops need to be improved in SCIENCO, with first level of maturity. In addition, both
expert system and experience report have not been recognised in the PMOs. This means
participants believe that the mentioned practices have not been addressed in the selected case
studies, so they could be addressed in the next levels of maturity. So it could be proposed that
Externalisation should be developed from the first level of maturity in which “community of
practice” and “deductive and inductive thinking” should be addressed at this level. In a
consistent manner, “workshops and seminars” should be addressed at the second level of
maturity, and then Expert systems and experienced report should be initiated at third and/or
fourth level of maturity, as depicted at Figure 8-15.
According to the research findings Combination is the third most frequently mentioned sub-
process to support knowledge creation in the selected cases in which SCIENCO has the lowest
and MINCO has the highest frequency in this regard, as shown in Table 8-5 and Figure 8-14.
Further investigation explored that only community of practice has been recognised in all three
cases. In addition, knowledge broker, another KM practice, was observed in MINCO and
GOVCO. Also, little evidence was found to support “documentation search” in MINCO,
Socialisation
Externalisation
Combination
Internalisation
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
SCIENCO(ML=1) GOVCO
(ML=2) MINCO (ML=3)
SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Socialisation 45.71% 37.2% 30.5%
Externalisation 30.00% 30.2% 26.7%
Combination 7.14% 32.6% 30.5%
Internalisation 17.14% 0.0% 12.4%
250 Chapter 8 | DISCUSSION and RESULT
however, the other two KM practices, i.e. data mining and best practices, have not been
recognised during the data collection stage. This means that they should be addressed in the
third or fourth level of maturity. Therefore, it could be proposed that in the first level of
maturity community of practices should be developed to address the Combination, and then
PMO should operate as knowledge broker in the second level of maturity. In the third level of
maturity, a documentation search should be developed, alongside the best practices. In the
fourth level of maturity data mining should be addressed to complete the Combination process,
as shown at Figure 8-15.
The research findings revealed that Internalisation has the lowest frequency among all
knowledge creation sub-processes, in which only some evidence was found to support this
process in MINCO and SCIENCO. In addition, the number of recognised practices for
supporting Initialisation in MINCO is slightly more than SCIENCO, despite the fact that
SCIENCO is a research organisation. In other words, SCIENCO has developed a number of
research practices in place as a research company, regardless of its level of maturity. According
to current literature, basic PM practices should be developed in the first level of maturity
(Kerzner 2009; Kerzner 2013). This means that in SCIENCO, as a PMO with first level of
maturity, it was expected to explore a few practices to support KM, specifically the knowledge
creation process. However, the nature of SCIENCO’s business contributes to improve the KM
in the PMO. On the other hand, GOVCO’s PMO is a centre of excellence where knowledge
creation was ranked as the third most important KM process. In other words, it is plausible to
find some evidences for supporting internalisation process in GOVCO.
Therefore it could be proposed that Internalisation should be the lowest priority for
developing knowledge creation in the PMO. Since limited evidence was found in GOVCO, it
could be advised to initiate the process of internalisation from the second maturity level through
developing simulation practices. Then, using metaphors and experimentation should be
developed in the third level of maturity. In the fourth level of maturity all related research
activities should be developed to address the process of Internalisation, as presented at
Figure 8-15.
Chapter 8 | DISCUSSION and RESULT 251
Figure 8-15 K. creation’s sub processes in various levels of maturity (developed for this study)
252 Chapter 8 | DISCUSSION and RESULT
Knowledge transferring is the third most frequently mentioned KM process in MINCO and
SCIENCO, while it is the second in GOVCO, as shown in Table 8-6. As discussed, this
difference is because of the type of GOVCO’s PMO as a centre of excellence. According to the
research framework, knowledge transferring comprises two sub processes: knowledge
distributing and forwarding, and knowledge sharing. As it can be found in Table 8-1 and
Figure 8-16, the frequency of knowledge sharing is more than knowledge distribution not only
in each case individually, but also from a frequency aggregation point-of-view. This means that
from participants’ points-of-view the current KM practices mostly support the knowledge
sharing process, while knowledge distribution is yet to be developed in the three cases.
Table 8-6 Knowledge transferring’s sub-processes in various PMOs (developed for this study)
Sub-process Associated Practices SCIENCO (ML=1)
GOVCO (ML=2)
MINCO (ML=3)
Knowledge Distribution
and forwarding
• Project bulletin and reports
• Communication channels
• Knowledge list
• Video and Tele Conference meeting
• Yellow page • Intranet • Data base
18 34 14
Knowledge Sharing
• Discussion forums • Formal &informal
events
• Mentoring • Training 19 49 37
According to the research findings formal and informal event is the most frequently
mentioned practice to support knowledge sharing, and ultimately knowledge transferring.
Communication channels, such as email and phone, and training & mentoring are the second
and third most frequently mentioned practices in the selected case studies. The research findings
explored that the majority of the current practices have focused on addressing the mentioned
KM practices, while the other practices either have not been addressed or are yet be developed
appropriately. For instance, some evidence supports the usage of Intranet or data bases to
facilitate the process of project knowledge transferring, while little evidence was found to
facilitate a knowledge list or knowledge directories. This means that the current systems in
PMOs need to be significantly developed to address knowledge transferring in project
environments.
As mentioned, it was revealed that knowledge sharing is the most frequently mentioned KM
practice to facilitate knowledge sharing. According to the research framework knowledge
sharing comprises three practices, as shown in Table 8-6. The research findings explored that
formal and informal events, and training and mentoring have been addressed in the three
mentioned cases, but discussion forums are yet to be addressed in the SCIENCO. This means
that SCIENCO with a lower level of maturity has not developed this practice. Therefore it could
be proposed that in the first level of maturity both formal and informal events, and training and
mentoring should be developed. In a consistent manner, the discussion forums should be
Chapter 8 | DISCUSSION and RESULT 253
developed in the second and third level of maturity in order to fulfil the knowledge sharing
practices, as depicted at Figure 8-17. All three practices should be improved in a higher level of
maturity.
Figure 8-16 Knowledge transferring's sub-processes case studies (developed for this study)
According to the research findings, knowledge distribution is the second most frequently
mentioned KM process to support knowledge transferring. As depicted in Table 8-6, there are
seven practices in the research framework to facilitate knowledge distribution. The research
findings explored that communication channels have the most data frequency among others
which has been addressed in three selected cases. This means that communication channels are
the basic practices for knowledge distribution in any PMOs, regardless of level of maturity.
Intranet and Data bases are the second and third frequently mentioned practices which have
been recognised in the three cases, but direct observation has revealed that MINCO and
GOVCO have developed better facilities in this regard. This means that the database and
intranet play stronger roles for knowledge transferring, in a PMO with higher maturity levels.
The research findings explored some evidence to support practices such as video conference and
yellow page in GOVCO and MINCO, however, they are yet to be developed to satisfy
participants’ expectations. In addition, little evidence was found to support practices such as
knowledge repository and knowledge list, which could be addressed in a higher maturity level.
Therefore, it could be proposed that communication channels and some basic features of DBS
should be addressed in the first level of maturity. In the second level of maturity, intranet and
video conference should be developed. In a consistent manner, yellow page and electronic
bulletin should be developed in the third level of maturity. Eventfully, a knowledge list and
directories should be developed in the fourth level of maturity to apply all knowledge related
practices, as shown in Figure 8-17.
Knowledge Distribution and forwarding
Knowledge sharing0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%80.00%
SCIENCO(ML=1) GOVCO
(ML=2) MINCO(ML=3)
SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Distribution and
forwarding 48.65% 41.0% 27.5%
Knowledge sharing 51.35% 59.0% 72.5%
254 Chapter 8 | DISCUSSION and RESULT
Figure 8-17 K. transferring’s sub-processes in various levels of maturity (developed for this study)
Chapter 8 DISCUSSION and RESULT 255
According to the research findings knowledge reusing has the lowest frequency among all
four KM processes. According to the research framework, knowledge reusing has three sub-
processes, as depicted in Table 8-7. The research analysis showed that knowledge reusing has
not been appropriately developed in the selected case studies, specifically in SCIENCO and
GOVCO. In other words, the current KM practices need to be improved to address the processes
of knowledge reusing in project environments. According to the research outcomes a majority
of associated practices to support knowledge reusing have not been observed in SCIENCO and
GOVCO, however, MINCO’s PMO has developed some practices to facilitate the mentioned
KM process, as depicted in Table 8-7 and Figure 8-18.
Table 8-7 Knowledge reusing’s sub-processes in various PMOs (developed for this study)
Sub-process Associated Practices SCIENCO (ML=1)
GOVCO (ML=2)
MINCO (ML=3)
Knowledge Adapting
• Electronic notice board • Documents
management system (DMS)
• Formal or informal events
• Data base • Yellow page • Knowledge
detection tools • Intranet
5 5 12
Knowledge Applying • Expert systems
• DMS 1 1 2
Knowledge Integrating • Knowledge map • Data mining 0 0 0
The research findings revealed that knowledge adapting has the highest data frequency
among knowledge reusing sub-processes, as shown in Table 8-7. According to the research
framework there are seven practices to facilitate knowledge reusing, in which some are used for
knowledge capturing and transferring as well. The way of applying these common practices,
determines whether they are utilised for knowledge reusing or/and capturing. For instance,
databases (DBs) could be used for knowledge capturing and reusing, however, some
preparations are required to develop DBs for knowledge reusing purposes (Newell, et al. 2006).
The research findings revealed that current DBs are often used to support knowledge reusing
processes, despite the fact that DBs are the most frequent practices to address knowledge
reusing in the selected cases. In a similar manner, a document management system (DMS) is
used to support knowledge capturing and reusing. As discussed earlier, this practice has been
appropriately developed for knowledge capturing purposes, however, limited evidence supports
the utilisation of DMS for reusing project knowledge. This means that the common systems
should be developed in a way that they could support knowledge reusing. The collected data
from case studies revealed that DBs are often used in the three cases, especially in MINCO. In
addition, intranet, formal and informal events, and DMS are fairly utilised by MINCO and
GOVCO, but limited evidence was found to support them in SCIENCO for knowledge reusing.
Also, the electronic notice board is only used by MINCO, while the other cases have not
256 Chapter 8 | DISCUSSION and RESULT
improved this practice for knowledge reusing purposes. The usage of other KM practices, for
supporting knowledge adapting, have not been observed during the course of data collection and
analysis. So it could be inferred that they should be addressed in the next level of maturity.
Therefore, it could be proposed that in the first level of maturity DBs should be developed to
address knowledge adapting, then to achieve the second level of maturity, DMS and intranet
should be addressed as presented in Figure 8-19. Electronic Notice board and yellow pages
should be developed in the third level of maturity, and eventually knowledge detection tools
should be addressed in the fourth level of maturity, in order to fulfil the process of knowledge
adapting. In the fifth level continuous improvement should be conducted to enhance the quality
of knowledge reusing.
Figure 8-18 Knowledge reusing’s sub-processes in three case studies (developed for this study)
According to the research findings, both knowledge applying and integrating are yet be
developed in the three cases, specifically SCIENCO and GOVCO, as shown in Table 8-7. This
means that there is limited evidence to address appropriate practices at each level of maturity.
Since the proposed practices for knowledge applying and integrating are mostly in common
with other KM processes, therefore the following could be proposed to address these two KM
sub-processes, as shown at Figure 8-19. Knowledge applying and integrating shall be developed
from the second level of maturity in which DMS should be addressed. In the third level of
maturity Expert system and data mining should be developed, and then a knowledge map should
be developed in the fourth level of maturity. Continuous improvement should be conducted in
the fifth level of maturity to enhance the quality of project knowledge reusing, and ultimately the
project KM.
Knowledge Adapting
Knowledge ApplyingKnowledge Integrating
0.00%20.00%40.00%60.00%80.00%
100.00%
SCIENCO(ML=1) GOVCO
(ML=2) MINCO(ML=3)
SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Adapting 83.33% 83.3% 85.7%
Knowledge Applying 16.67% 16.7% 14.3%
Knowledge Integrating 0.00% 0.0% 0.0%
Chapter 8 DISCUSSION and RESULT 257
Figure 8-19 K. reusing’s sub processes in various level of maturity (developed for this study)
Chapter 8 DISCUSSION and RESULT 259
In summary, the second research question, i.e. how do KM practices contribute to improve
maturity level of the PMO, has been discussed through analysing various KM practices in the
three levels of PMO maturity. In the last section, KM processes, their sub-processes, and
also associated KM practices were considered to investigate how they are utilised in various
levels of maturity. Based on the research findings, numbers of propositions have been
developed to address each KM process and sub-process in different maturity levels. These
propositions are part of this research’s contribution, by which a road map has been proposed
to develop KM processes in three levels of PMO maturity. In the next section, these findings
will be employed to answer the third research question in order to propose the
comprehensive framework to address KM processes in five levels of PMO maturity.
MODEL DEVELOPMENT 8.9
In this section, the final research framework will be developed through integrating the
research findings in the nominated case studies and the preliminary research framework.
Five maturity levels of PMO have been utilised to address appropriate KM processes and
practices. The research findings were used to develop the first three levels and for levels four
and five, numbers of suggestions and recommendations have been proposed. This part
answers the third research question and fulfils the research objectives.
Integration of KM practices at various level of maturity 8.9.1
The third research question (RQ.3 how can knowledge be integrated in the PM maturity
model?) comprises two research questions: how is knowledge created, captured, transferred
and Reused at PMO maturity levels; how should KM practices be employed in the each
maturity level of PMO. These questions will be discussed through integrating all the research
findings as well as the developed propositions. In addition, the developed research
framework (Chapter 3) will be considered and then refined, based on the research findings.
At the end of this section, numbers of propositions will be presented to address the project
knowledge management in various levels of maturity.
Knowledge management in the first level of maturity 8.9.1.1
According to the conceptual research framework (Chapter 3), in the first level of
maturity, the following criteria should be observed from a KM point of view: 1) PMO and
project team members are not appropriately aware of the importance of project knowledge
management, 2) There is little or no intention to formally manage project knowledge, 3)
There no specific KM technology or infrastructure in place, and 4) There is no formal
process to manage project knowledge. The research findings revealed that some of the
mentioned criteria do not conform to the current situation in SCIENCO’s PMO. For instance,
there are some formal processes in place to manage project knowledge. In addition, some
260 Chapter 8 | DISCUSSION and RESULT
infrastructure and technologies, such as the SAP and Intranet, were observed in SCIENCO’s
PMO.
On the other hand, SCIENCO is a research organisation, so it is plausible to find some
KM practices in place, despite its PMO having the first level of maturity. This means that the
above mentioned criteria should be slightly refined to satisfy the current situation of
SCIENCO’s PMO. Therefore, the following could be proposed as the main criteria of PMO
with first level of maturity:
• The importance of project knowledge management has not been significantly
realised by PMO and senior managers,
• There are limited KM technology and infrastructure to support project KM, and
• There are limited formal processes to manage project knowledge.
As discussed in Chapter 3, the research framework assumes that in the first level of
maturity there are some practices in place to support knowledge capturing and creation. The
research findings revealed that not only knowledge capturing and creation are the first and
second most frequently mentioned KM processes, but also they were ranked as the first and
second most important KM processes in SCIENCO. This means that the research findings
and the research framework are consistent in this regard. In addition, numbers of practices
were found in SCIENCO, which are used for knowledge transferring. Also, a few practices
were observed in SCIENCO which in some ways support knowledge reusing. This means
that both knowledge transferring and reusing could be initiated in the first level of maturity.
In addition, KM sub-processes have been discussed in the previous section, i.e. 8.8.2.
Therefore, the following recommendations have been developed to refine the conceptual
research framework through reflecting the research findings, in order to address the KM
process in the first level of maturity.
• Knowledge capturing is the most important KM process, so it should be
supported through developing basic practices to address subsequent sub-
processes: knowledge storing and classification,
• Knowledge creation is the second most important KM process, so it should be
supported through developing basic practices to facilitate the following sub-
processes: socialisation, externalisation and combination.
• Knowledge transferring is the third most important KM process, so it should be
facilitated through developing basic practices to support the following sub-
processes: knowledge sharing and knowledge distribution, and
Chapter 8 DISCUSSION and RESULT 261
• Knowledge reusing is the least important KM process, so it could be addressed
through develop basic practices to address the following sub-process: knowledge
adapting.
The mentioned propositions have been graphically represented in Figure 8-20. As can
found in this figure, four KM processes have been addressed, with their sub-processes. The
stronger colour represents the importance of the process.
Figure 8-20 KM sub processes in the first level of maturity (developed for this study)
According to the research framework, the KM development plan should be prepared in
the first level of maturity. The research findings revealed that this plan has been considered
in the PMO development plan, however, it needs to be refined with regards to the research
findings.
In summary, no inconsistency was explored between the conceptual framework (Chapter
3) and the research findings in the PMO with first level of maturity (Chapter 5), i.e.
SCIENCO. However, some refinements have been proposed to develop the preliminary
conceptual framework, which was discussed earlier. In other words, the theoretical research
framework was examined in the selected cases, and then refined based on the research
findings in SCIENCO. Therefore, the revised framework shall be a practical guideline to
address the KM in the first level of maturity.
262 Chapter 8 | DISCUSSION and RESULT
Knowledge management in the second level of maturity 8.9.1.2
According to the preliminary research framework (Chapter 3), following criteria should
be explored in the second level of maturity: 1) senior managers have realised the importance
of project KM, however, 2) There is no person or unit responsible for project KM in PMO,
3) The concept of KM has been understood by PMs and project team members, 4)
Knowledge capturing and creation are being managed through developing appropriate
systems, 5) There are some practices in place to support knowledge transferring and reusing.
These criteria were examined in GOVCO with the second level of maturity and two
inconsistencies were found during the course of data analysis. First, it was revealed that
knowledge capturing and transferring are the first and second most important KM processes.
Second, knowledge creation has not been appropriately developed in GOVCO, as the
research framework assumes. This means that GOVCO’s main priority has been on
development of knowledge capturing and transferring. On the other hand, it was revealed
that GOVCO’s PMO is a centre of excellence which means that it is not involved in project
implementation, therefore the PMO does not significantly contribute to knowledge creation.
In other words, GOVCO’s PMO focuses on addressing knowledge capturing and transferring
in the first place, then supporting knowledge creation. Apart from the mentioned
inconsistencies, the other mentioned criteria have been confirmed by the collected data from
GOVCO. In order to reflect on the research findings, the following have been proposed to
refine the preliminary research framework, in order to address the KM criteria in the second
level of maturity:
1) The importance of project KM has been realised and supported by senior managers,
2) The concept of KM has been understood by PMs and project team members,
3) Knowledge capturing is the most important KM process and knowledge transferring
and creation, should get the same priority,
4) There is no person or unit responsible for project KM in PMO, and
5) There are limited practices in place to support knowledge reusing.
According to the preliminary research framework, all KM processes should be employed
to some extent, in the second level of maturity. This assumption was confirmed as numbers
of practices were found in GOVCO by which knowledge capturing, creation and transferring
are facilitated, however, limited practices are in place to support knowledge reusing. It was
assumed that knowledge reusing has a few practices to be supported and this assumption was
confirmed through the collected data from GOVCO. As discussed, the major inconsistency
between the research findings and the preliminary research framework is the importance of
knowledge transferring over knowledge creation which was justified earlier. Therefore, the
Chapter 8 DISCUSSION and RESULT 263
following suggestions could be proposed to address project knowledge management in the
second level of maturity:
• Knowledge capturing is the most important KM process, so it shall be improved
through
o Developing basic practices to address subsequent sub-processes:
knowledge identification and selection,
o Developing advanced practices to improve knowledge storing and
classification,
• Knowledge creation is the second most important KM process, so it shall be
supported through
o Developing basic practices to facilitate the internalisation sub-process
o Developing advance practices to improve socialisation, externalisation
and combination.
• Knowledge transferring is the second most important KM process, so it shall be
facilitated through improving appropriate practices to support knowledge
sharing and knowledge distribution,
• Knowledge reusing is the least important KM process, so it shall be developed
through
o Addressing basic practices to facilitate knowledge applying,
o Developing appropriate practices to improve knowledge adapting.
The mentioned propositions have been graphically represented in Figure 8-21. As can be
found in this figure, four KM processes have been addressed with their sub-processes. The
stronger colour represents the importance of the process.
264 Chapter 8 | DISCUSSION and RESULT
Figure 8-21 KM sub processes in the second level of maturity (developed for this study)
In summary, there is no significant inconsistency between the research findings in the
PMO with a second level of maturity, i.e. GOVCO, and the research framework. However,
some refinements have been proposed to develop the preliminary research framework, which
was discussed earlier. In fact, the theoretical research framework was examined in the
selected case study, and then it was revised based on the research findings in GOVCO. The
revised framework shall be a useful method to address the KM in the second level of
maturity.
Knowledge management in the third level of maturity 8.9.1.3
According to the preliminary research framework (Chapter 3), in a PMO with the third
level of maturity, the following criteria should be observed from a KM point of view: 1)
PMO and top managers are aware of their role in encouraging project KM, 2) There is a unit
or person to take the responsibility and accountability of KM in the PMO, 3) KM is
systematically supported through appropriate systems and established standards, 4) There are
some incentives in place to encourage project team members to follow KM procedures, 5)
there are training courses to instruct KM in the PMO, and 6) Some of the developed KM
practices have been integrated at enterprise-level.
The mentioned criteria were examined in MINCO, as the case study with third level of
maturity. The research findings revealed that there is no significant inconsistency between
the preliminary research framework and the collected data from MINCO, however, some of
the criteria have been not completely observed in MINCO. For instance, there is a person
Chapter 8 DISCUSSION and RESULT 265
who is in charge of project knowledge management unit in MINCO’s PMO, but he is the
only person who teaches KM to the others. In other words, there is no specific course or
manual to formally instruct project knowledge management in MINCO. In addition, there
are numbers of KM systems, which are yet to be collaborated at the organisational level.
These findings explored that some of assumed criteria are yet to be completely addressed in
MINCO’s PMO. On the other hand, MINCO’s PMO has recently achieved the third level of
maturity so it takes time to fulfil all the mentioned criteria. However, the proposed criteria
have been refined as follows, to both conform to the MINCO’s PMO, and also satisfy the
research framework:
1) Senior executives, and PMO managers are aware of encouraging project knowledge
management,
2) There is a unit and/or person to take the KM responsibility in PMO,
3) Project KM is systematically supported through appropriate systems and procedures,
4) There are some incentives in place to encourage project stakeholders for following
KM procedures,
5) There is a plan to integrate the developed KM practices at the enterprise-level.
This advice should be used by PMOs with same maturity level in order to develop and/or
access the current level or maturity.
From a KM process point of view, the collected data from MINCO data has been
examined against the research framework. According to the research findings, KM processes
have the following order in terms of their importance: capturing, creation, transferring, and
reusing. This investigation revealed that, except for knowledge reusing, the collected data for
the other three KM processes are in line with the research framework. In other words,
knowledge capturing, creation and transferring are consistent with the proposed
functionalities in the preliminary research framework, while knowledge reusing’s data
showed some inconsistency in this regard. In fact, the research framework assumes that
knowledge reusing should be appropriately addressed in the third level of maturity, but the
collected information explored that knowledge reusing is yet to be developed in MINCO’s
PMO. As discussed, MINCO’s PMO is at the beginning of its journey at the third level of
maturity, so this gap might be addressed in the end of its journey to achieve the fourth level
of maturity. Having said that, the proposed assumptions for knowledge reusing have not
been confirmed in MINCO’s PMO. Therefore, some of the preliminary assumptions have
been revised to suit the collected data, as followings:
• Knowledge capturing is the most important KM process, so it should be improved
through developing advanced practices to improve knowledge storing,
classification, identification, and selection.
266 Chapter 8 | DISCUSSION and RESULT
• Knowledge creation is the second most important km process, so it should be
supported through developing advance practices to improve socialisation,
externalisation, combination, and internalisation
• Knowledge transferring is the third most important KM process, so it should be
facilitated through improving appropriate practices to support knowledge
sharing and knowledge distribution,
• Knowledge reusing is the least important KM process, so it should be developed
through
o Developing appropriate practices to improve knowledge adapting and
applying,
o Addressing basic practices to facilitate knowledge integrating.
The mentioned propositions have been graphically represented in Figure 8-22. As it can
be found in this figure, four KM processes have been addressed with their sub processes. The
stronger colour represents the importance of the process.
In summary, the research findings, in the PMO with third level of maturity, have not
shown any significant inconsistency against the preliminary research framework. However,
some refinements have been made to develop the research framework, which was discussed
earlier. In fact, the theoretical research framework was examined in MINCO, and then it has
been revised based on the research findings. The revised framework presents a practical
method to address the KM in the third level of maturity.
Chapter 8 DISCUSSION and RESULT 267
Figure 8-22 KM sub processes in the third level of maturity (developed for this study)
Knowledge management in the fourth and fifth level of maturity 8.9.1.4
According to the research framework in the fourth level of maturity, the following
should be observed from a KM point of view: 1) The role of project KM to improve
organisational competitive advantages has been realised by senior managers, 2) PMO, KM
practices and processes have been integrated with organisational KM activities, 3) Advance
trainings and workshops are being conducted to improve project KM, 4) Measuring the KM
utilisation on project productivity is being conducted, 5) Everybody is responsible for
managing project knowledge, 6 ) Numbers of quantitative index, critical success factors
(CSF), and metrics have been developed to measure the effectiveness of KM processes. As
discussed, only three cases were examined in this study, from level one to three, so the
mentioned criteria have not been examined in this study. However, these criteria could be
used by PMOs with fourth level of maturity as they have been developed based on the
current literature, but it is advised to be examined as a subject for future research.
From a KM process point-of-view, it is assumed that all KM processes should be
appropriately utilised in the fourth level of maturity. This means that at this level four KM
processes have been developed to be used by project stakeholders. As discussed in the
previous section, knowledge reusing was the only KM process that has not developed in the
third level of maturity. In other words, the research findings revealed that the development of
knowledge reusing has been initiated in the second level of maturity, while in the framework
it is assumed that knowledge reusing should be established from the first level of maturity.
Because of the recognised inconsistency between theory and practice, the framework has
been revised to satisfy the research findings. The same approach has been managed to
address knowledge reusing in the fourth level of maturity. In other words, the last sub-
process of knowledge reusing should be completely developed in the fourth level of
maturity, while it was assumed in that it should have been conducted in the previous
maturity level. Therefore, this is only change in the research framework to address
knowledge reusing in the fourth level of maturity, based on the research findings. This
means that the following should be followed to develop KM processes in the fourth level of
maturity, as shown at Figure 8-23:
• Knowledge capturing should be improved through developing complementary
KM practices,
• Knowledge creation should be supported through developing advance KM
practices,
• Knowledge transferring should be facilitated through improving advanced KM
practices,
268 Chapter 8 | DISCUSSION and RESULT
• Knowledge reusing is the only KM process which has not been completely
addressed, so it should be developed through
o Developing complementary practices to improve knowledge adapting
and applying,
o Addressing advance practices to support knowledge integrating.
According to the research framework in the fifth level of maturity the following should
be observed from a KM point-of-view: 1) The culture of sharing and knowledge transferring
has been institutionalised, 2) Both organisation and PMO utilise an integrated KM system, 4)
An audit unit has be developed to measure project KM, 5) Project KM is integrated into
organisation and it is continually improved, 6) KM procedures are integrated in the PM
methodology as well as organisational process-assets, and 7) Project KM and competitive
advantages have been collaborated to support organisational strategies. Similar to the fourth
level of maturity, these criteria have not been examined in this study, however, they have
been proposed based on the current literature of PM and KM. In addition, examining the
proposed criteria for the fourth and fifth level of maturity could be a potential subject for
future research.
From KM process perspectives, the conceptual research framework assumes that all KM
processes have been appropriately developed and customised in the fifth level of maturity. In
addition, the research framework advises to assess and continuously improve the developed
KM processes through managing research and development activities. This means that the
current KM practices should be enhanced based on researching the existing gaps to address
them appropriately. Figure 8-23 depicts the proposed activities to improve the KM in the
fifth level of maturity.
Chapter 8 DISCUSSION and RESULT 269
Figure 8-23 KM processes in the fourth and fifith level of maturity (developed for this study)
In summary, this section discussed the third and last research question. The research
findings have been used to address project knowledge management in the first three maturity
levels. The preliminary research framework has been refined based on the research findings
in the selected case studies. For the fourth and fifth level of maturity, the research framework
has not been significantly revised, as there was no data with which to do so. Therefore, this
could be a potential subject of the future research.
CONCLUSION 8.10
In this chapter, three cases and their results were analysed against both each other and the
conceptual research framework, to answer all three research questions. The first and second
research questions have been answered through conducting cross case analysis, while the
third question was answered via comparing the conceptual framework and the research
findings. Both within-case and cross-case data analyses have been conducted by using
numbers of techniques such as grounded theory and pattern matching. Grounded theory was
utilised to develop evolving phenomena through coding the data and analysing the data
behaviour. Other techniques were also conducted to explore other aspects such as similarities
and differences.
270 Chapter 8 | DISCUSSION and RESULT
Figure 8-24 Summary of the research findings (developed for this study)
This process contributed to uncovering numbers of patterns and behaviours in the
collected data to answer the research questions. Also it assisted with developing numbers of
suggestions and propositions to address the KM practices in the PM maturity models. As can
be seen in Figure 8-24, management of the project knowledge in the PMO was recognised as
the research gap (known-unknown). The collected data from three cases with three various
maturity levels were analysed by using Grounded theory and other analytical methods.
Numbers of unrevealed project knowledge management subjects have been explored during
the course of data analysis and they became “known” during this process, as shown in
Figure 8-24. However, numbers of questions were recognised during the data analysis which
could be answered through conducting another research study in the future.
Chapter 8 DISCUSSION and RESULT 271
Figure 8-25 KM challenges in PMOs (developed for this research)
In addition, the following propositions have been developed during the data analysis
stage:
• There is a significant relation between the level of PMO maturity and the utilised
KM practices,
• The importance of KM processes could be ranked as follows: Capturing,
Creation, Transferring and Reusing,
• The challenges of KM are different in various levels of maturity as depicted in
Figure 2-1, and Figure 8-25; also, the types of required knowledge have a
significant impact on the level of PMO maturity.
• Issues of both integration between knowledge management systems and
processes, and advanced challenges of knowledge reusing and transferring, could
be observed in the fourth level of maturity, and
• Collaboration of organisational knowledge management practices with PMO’s
knowledge management systems could be observed as the main challenge in the
fifth level of maturity.
In summary, this chapter has provided practical implications to address appropriate KM
practice in various levels of maturity. The developed framework in the previous section shall
be used by various types of organisation, specifically in PMOs with a one to three level of
272 Chapter 8 | DISCUSSION and RESULT
maturity. The proposed suggestions and propositions have been developed based on the
collected data and data analysis techniques. The obtained KM challenges should be
considered by all types of PMOs in order to be prepared for the next level of maturity. Also,
the types of required knowledge are good indications for PMOs to provide knowledge, based
on their importance. In the next chapter, the research conclusion will be presented to discuss
the highlights of the research findings, the developed propositions, research limitations, and
future research.
Chapter 9 | Conclusions 273
Chapter 9
CONCLUSIONS
OVERVIEW 9.1
Organisations manage projects to achieve diverse objectives such as technological
enhancement, customer satisfaction, service improvement, and organisational development.
Project Management (PM) is the combination of skills, knowledge, tools and techniques to
fulfil project objectives, and project management methodologies recommend appropriate
practices to manage projects. A Project Management Office (PMO) centrally manages and/or
controls organisational projects, and also institutionalises project management practices
within organisations. Due to the complexity of project management practices, Project
Management Maturity Models (PMMM) have been developed to address the development of
PMOs. In other words, PM maturity models contribute to improve the quality of PMO
services, and ultimately enhance the project success rate.
The management of project knowledge is another critical factor to improve the project
success rate, and contributes to the quality of project outcomes. According to the findings of
this research, the current PM maturity models have not appropriately addressed the
management of project knowledge in various levels of maturity. In fact, the existing PM
maturity models are yet to be developed from knowledge management perspectives.
Following a succinct introduction to outline the research structure in Chapter one, a
comprehensive literature review was undertaken in Chapter two, to investigate the current
debates in both project management and knowledge management fields. In Chapter three, the
conceptual framework, as a preliminary research framework, was developed through
identifying factors that potentially influence project knowledge management in PMOs. In
this framework, four knowledge management processes were adopted, i.e. Capturing;
Creation; Transferring; and Reusing, to address knowledge management in five levels of
maturity. To investigate the conceptual framework, a case study method was selected as the
research methodology alongside Grounded theory as the main analysis technique, which was
presented in Chapter four.
Three large organisations with diverse sectors were chosen for investigation. The within-
case analysis was conducted for each case, i.e. SCIENCO; GOVCO; and MINCO, in
conformance with the research methodology. The research findings were analysed and
presented in chapters five, six and seven. In Chapter five, SCIENCO’s PMO, with the first
274 Chapter 9 | Conclusions
maturity level, was discussed to explore the utilisation of knowledge management processes
and practices. Both research methodology and the conceptual framework were used to reveal
the management of project knowledge in SCIENCO. Similar processes were conducted to
investigate GOVCO and MINCO, and the outcomes of both investigations were presented in
chapters six and seven.
In Chapter eight, the cross case analysis was conducted to compare the research findings
from the selected case studies, and also overall discussions of the research findings were
presented accordingly. According to the research findings, in Chapter eight, MINCO with a
third level of maturity has more developed knowledge management practices in comparison
to GOVCO and SCIENCO. In a similar manner, the research findings revealed that GOVCO
with a second level of maturity has developed more knowledge management practices in
place, in comparison to SCIENCO, with the first maturity level. This means that there is a
relationship between project knowledge management, and the maturity level of the project
management office. At the end of this chapter, a number of suggestions and propositions
were discussed to address appropriate KM practices and processes in various levels of
maturity.
This chapter aims to succinctly summarise the research findings to address the research
questions. Also, it presents the research contributions and significance of this research,
followed by acknowledging the research limitations. At the end, a number of directions and
subjects have been proposed for future studies.
KNOWLEDGE MANAGEMENT CHALLENGES IN THE PMO 9.2
This research aimed to explore the management of project knowledge in the project
management office. To do so, numbers of questions and sub-questions were developed, as
discussed in section 2.5.4. The current challenges of PMOs, from a KM point of view, were
the first subject to be investigated. As presented in section 8.6.1, the following KM
challenges were explored in the selected case studies: 1) lack of appropriate systems to
support project knowledge management, 2) difficulties of searching and detecting required
knowledge (recognised in SCIENCO only), 3) issue of appropriate access to the existing
systems, 4) issue of locating and accessing right information and/or right expert, 5) lack of
knowledge management practices and processes during project life cycle (were revealed
only in SCIENCO and GOVCO), 6) lack of integration among current processes and
systems (explored in GOVCO only), 7) issues with current systems to fully support
knowledge capturing process, 8) inadequate practices to support knowledge transferring
process, 9) unsatisfactory practices to appropriately support the knowledge reusing process,
and 10) lack of training for current systems and applications (explored in MINCO only).
Chapter 9 | Conclusions 275
According to the research findings, in the lower levels of maturity (first and second
levels), the majority of knowledge management challenges are related to the current systems
and their access, while in higher levels of maturity the integration of current systems
becomes more challenging. In addition, in higher levels of maturity, knowledge transferring
and reusing are more challenging in comparison to knowledge capturing and creation. As
can be found in Figure 8-25, there is relationship between the level of maturity and type of
KM challenges in PMOs.
Practical Implications
It is suggested that a PMO with low levels of maturity (one and two) shall focus on
developing the required systems and applications, and also provide appropriate access to
project stakeholders. In addition, knowledge capturing and creation issues should be resolved
at lower levels of maturity. This means that in the third or higher level of maturity, issues
such as access to systems, or lack of required systems should be addressed. In the third and
fourth levels of maturity, the main focus should be on both integrating the current systems,
and developing appropriate knowledge management practices to address the existing issues
related to knowledge transferring and reusing. In other words, in the fourth level of maturity,
the PMO should not be faced with major challenges from knowledge management process
perspectives. In the fifth level of maturity, PMO should focus on addressing issues of
integrating and collaborating knowledge management with the organisational knowledge
management system.
THE REQUIRED TYPES OF KNOWLEDGE IN VARIOUS LEVELS OF MATURITY 9.3
According to the research findings, “project management knowledge”, “knowledge about
clients”, and “knowledge of who knows what” are the most important types of knowledge,
while “knowledge about supplier” and “legal knowledge” are ranked as the least important
types of knowledge. This research revealed that the importance of required knowledge is
changed when the maturity level of the PMO improves, since the PMO develops new
knowledge management practices in a higher level of maturity to address the recognised
needs. In addition, this study explored that the type of PMO and its level of maturity are two
important factors to determine the type of required knowledge, as discussed in section 8.6.2.
This means that in a practical PMO, such as SCIENCO, some types of knowledge (such as
costing knowledge) are important pieces of information, while in a centre of excellence
PMO, such as in GOVCO, costing knowledge is not as important as other types of
knowledge, as the PMO is not involved in project execution. In addition, in a PMO with a
low level of maturity, such as SCIENCO, providing some types of knowledge such as
“knowledge of who knows what” was ranked as the second most important type of required
knowledge, contrary to a PMO with a higher level of maturity, i.e. MINCO, where provision
276 Chapter 9 | Conclusions
of “knowledge of who know what” is not as important as in SCIENCO as it has been
addressed through numbers of practices.
Practical implications
A PMO with low levels of maturity shall focus on developing a comprehensive project
management methodology to address two types of knowledge: “project management
knowledge’ and “knowledge about procedures”. Also, according to the findings of this study
it is advised to develop appropriate practices to address “knowledge about who know what”,
and “knowledge about clients”. In the PMO with a higher maturity level the main focus shall
be on developing practical exercises to address “costing knowledge” as well as “technical
knowledge”, since they significantly impact on the quality of a project outcome. After
addressing the provision of the mentioned types of knowledge, the PMO shall focus on
facilitating the other types of knowledge such as legal knowledge and knowledge about
suppliers.
UTILISATION OF KNOWLEDGE MANAGEMENT PRACTICES IN PMO 9.4
Similar to the previous section, types of PMO and level of maturity are important factors
to determine the required knowledge management practices in a PMO. As discussed in
section 8.7, this research revealed that in a normal PMO (practical PMO), the majority of
KM practices should support knowledge capturing and creation, while in a centre of
excellence most of the KM practices should facilitate knowledge capturing and transferring.
In addition, numbers of KM practices in a PMO with low level of maturity, i.e. SCIENCO,
are less in a PMO with higher level of maturity, i.e. GOVCO and MINCO. This means that a
PMO with a higher maturity level has more knowledge management practices in place in
comparison to a low maturity level PMO. For instance, “expert locator” has not been
developed in SCIENCO, while it is used in GOVCO and MINCO. In a similar manner,
“expert system” has not been addressed in SCIENCO and GOVCO, but it is utilised in
MINCO. From a knowledge management process point-of-view, knowledge reusing is yet to
be addressed in SCIENCO and GOVCO, while MINCO has addressed some practices to
facilitate knowledge reusing. This means that in a PMO with low maturity levels (one and
two) knowledge capturing, creation and transferring, in order, have been addressed and
knowledge reusing has not be appropriately considered. Meanwhile, in a PMO with a higher
level of maturity, the mentioned three KM processes have been developed, hence knowledge
reusing gains more attention.
Practical implications
In a PMO with a first level of maturity, the development of appropriate practices to
address knowledge capturing and transferring shall be the first priority. In the second level of
Chapter 9 | Conclusions 277
maturity, it is recommended to improve the current practices, and develop new practices to
facilitate knowledge transferring. In the third level of maturity, addressing knowledge
reusing shall be the first priority alongside the improvement of other knowledge
management processes. In the fourth and fifth level of maturity, the PMO shall focus on
continually enhancing the four knowledge management processes through developing
advance knowledge management practices.
THE IMPORTANCE OF KNOWLEDGE MANAGEMENT PROCESSES IN PMO 9.5
As discussed in section 8.8.1, this research explored the notion that knowledge capturing
is the most important knowledge management process, while knowledge reusing is the least
important one. In addition, knowledge creation is the second most important knowledge
management process in SCIENCO and MINCO, which are both practical PMOs, but it is the
third important knowledge management process in GOVCO. In other words, in the centre of
excellence’s PMO, knowledge transferring is the second most important knowledge
management process, after knowledge capturing. This is another indication to determine the
type of PMO, as it impacts on knowledge management activities. In general, the following
order can be proposed to address the importance of the knowledge process: 1) Capturing, 2)
Creation, 3) Transferring, and 4) Reusing.
Practical implications
According to the research findings, PMOs shall focus on developing practices to address
KM processes in the following order: capturing, creation, transferring, and reusing. It is
advised to focus on developing capturing and creation practices, in a PMO with a first level
of maturity. In a similar manner, knowledge transferring and reusing shall be developed in
higher maturity levels. This is consistent with the research findings and implications in the
previous section.
PMO’S CONTRIBUTIONS TO KNOWLEDGE MANAGEMENT 9.6
As discussed in section 8.8, four knowledge management processes, their sub-processes
and associated practices were considered to address the development of knowledge
management in three levels of maturity. In addition, multiple propositions were developed
based on the research findings to address project knowledge management in the fourth and
fifth levels of maturity. This study explored that knowledge management processes should
be developed and improved based on three factors: Level of maturity, the importance of
knowledge management process (discussed section 8.8.1), and importance of the associated
sub-processes as well as practices (discussed in section 8.8.2). The PMO’s contributions to
develop knowledge management, in three levels of maturity, have been graphically depicted
278 Chapter 9 | Conclusions
in Figure 8-13 to Figure 8-19. In addition, Figure 8-23 has been provided to propose the
contributions of a PMO in levels four and five.
Practical implications
In the first level of maturity, knowledge capturing is the most important knowledge
management process, so in order to develop knowledge capturing, firstly knowledge storing
and classification should be established as the most important knowledge capturing sub-
processes. In other words, to develop knowledge capturing in the first maturity level, the
main focus should be on addressing knowledge storing and classification through
establishing associated knowledge management practices, such as document management
systems and databases. For the second maturity level, the other sub- processes, i.e.
knowledge selection and identification, should be developed through using some practices
such as expert locator and file management systems, as shown at Figure 8-13.
Similar process could be followed to develop other knowledge management processes, as
addressed in section 8.8.
KNOWLEDGE MANAGEMENT PROCESSES IN FIVE MATURITY LEVELS 9.7
This research revealed that the following factors should be considered in developing the
knowledge management in a PMO: level of maturity, type of PMO, the current knowledge
management issues and challenge, types of required knowledge, and the importance of
knowledge management processes. The maturity level of a PMO addresses the PMO’s
readiness and the types of issues that a PMO generally is faced with, as discussed in
sections 8.6.1. In addition, the types of required knowledge are addressed in regards to the
maturity level of a PMO, as presented in sections 8.6.2 and 9.3. The importance of
knowledge management processes addresses their priority to be developed in various level of
maturity, as discussed in sections 8.8.1, 8.8.2, and 9.6. Finally, the integration of all factors
addresses the development of knowledge management processes in the project management
office, as discussed in section 8.9.1. In addition, the integration of knowledge management
processes in five levels of maturity has been graphically addressed in the following figures:
Figure 8-20 to Figure 8-23. These figures address knowledge management processes in three
levels based on the research findings, and propose appropriate steps for improving the
quality of PM in the fourth and fifth levels of maturity.
Practical implications
The PMO in various levels of maturity, specifically the first three levels, shall develop its
knowledge management systems through the following steps: 1) recognising the current
challenges, and comparing them to the research findings in section 8.6.1, and 2) providing
the required types of knowledge, discussed in section 8.6.2, with regards to the level of
Chapter 9 | Conclusions 279
maturity, and 8.8, and 8.9.1. These steps shall improve the maturity of a PMO from a
knowledge management perspective.
RESEARCH CONTRIBUTIONS 9.8
General Contributions 9.8.1
This study aimed to make two following contributions: developing and applying a
framework to address KM practices at the current PMMM and PMO; and proposing new
criteria to assess the maturity of the PMO from a KM point-of-view. To achieve the
mentioned contributions, a conceptual framework was developed after a comprehensive
literature review. This was the first attempt to propose a framework for theoretically
addressing knowledge management processes and practices in five maturity levels of the
project management office, as presented in Table 3-11. In addition, for the first time in the
current literature, four KM processes and their associated KM practices have been discussed
in the proposed framework.
The conceptual framework was examined in three PMOs with various levels of maturity.
The empirical findings not only were consistent with the developed framework, but also they
contributed to reveal the following aspects of project knowledge management in PMO: the
importance of KM processes in various levels of maturity; the KM challenges of PMO in
various maturity levels; importance of the required knowledge in PMO. These findings were
utilised to refine the conceptual framework and reveal some of the unknown subjects in
PMOs from a knowledge management point-of-view, as shown in Figure 8-24. In addition,
numbers of suggestions and propositions have been developed to address knowledge
management in various maturity levels of the PMO, as discussed in section 8.9.
The researcher strongly believes the study outcomes significantly impacts on delivering
successful project through addressing practical advices on project KM. The recommended
KM practices address four KM processes, i.e. Creation; Capturing; Transferring; Reusing,
to bridge the recognised gap in the PMO. This research also has significantly contributed to
the existing discussions of the transformation of Tacit knowledge to Explicit knowledge in
the Project-Based Organisations. In addition, this is the first attempt to investigate PMO
maturity models from KM point of view, in order to address a road map for improving KM
capability in PMOs.
The developed framework is recommended to be employed by all types of PMOs
because: 1) it has a robust and reliable theoretical background, 2) it was examined in
different types of PMOs, 3) it was investigated in various types of organisations, and 4) it
has been refined based on the research findings in three organisations. To the best of this
researcher’s knowledge, this is the first attempt to address knowledge management processes
in the five maturity levels of project management office.
280 Chapter 9 | Conclusions
In addition, there are numbers of KM processes, sub-processes and practices in the
developed research framework. The utilisation of each practice and process is addressed in
various levels of maturity, as discussed in section 8.9 and shown in Table 3-11. The maturity
of PMO from a KM perspective shall be assessed through examining the addressed KM
practices in each level of maturity. This means that in a specific level of maturity, if the
proposed practices are not in place, they will need to be addressed to achieve the next level
of maturity. In other words, utilisation of the proposed framework shall be a strong
indication to address the maturity of PMO from a knowledge management point-of-view.
Theoretical Contributions 9.8.2
To the best of this researcher’s knowledge this is the first attempt to address knowledge
management processes and practices in various maturity levels of the Project Management
Office. The integration of knowledge management practices in the PM Maturity model is the
significant contribution of this research. Also, this study has developed a theoretical
framework to assess and address the maturity of project management environments,
specifically the PMO, from a knowledge management perspective. In addition, eight types of
project knowledge for the first time have been proposed and integrated in the proposed
framework. Finally, this research has provided a new direction for future studies to
investigate Project Management Office from a knowledge management point of view.
RESEARCH LIMITATIONS 9.9
The studies of knowledge management in project-based organisations have been recently
considered as an important subject, so there are still many aspects yet to be addressed in this
regard. This means that current literature is yet to be developed to address issues of project
knowledge management. In fact, the absence of adequate studies that discuss project
knowledge management was one limitation for this study. In other words, the proposed
theoretical framework would have been more comprehensive if the existing literature had
richer discussions from the associated field.
The selection of appropriate case studies was another limitation of this study. There are
five levels of maturity in the research framework, so it was initially planned to investigate
five organisations with various levels of maturity in order to examine the proposed
framework. After developing the preliminary research framework, it was realised that
finding case studies with high PM maturity is difficult, as PMO is relatively new for
industries, especially in Australia. In fact, the lack of information and evidence to undertake
this study in fourth and fifth levels of maturity forced this researcher to confine the scope of
study. Therefore, three organisations were finalised for this study to explore the utilisation of
knowledge management practices in the first three levels of maturity. However, this
Chapter 9 | Conclusions 281
researcher aims to investigate the developed framework in higher maturity levels in the
future.
The proposed research framework has been not been examined in fourth and fifth
maturity levels. This is another limitation of this study, as the research findings do not
discuss the PMO maturity level in the mentioned levels. In other words, the proposed
framework is yet to be examined in the highest maturity levels. This could be a subject for
another research project which will be discussed in the next section.
FUTURE RESEARCH 9.10
Several directions could be proposed from the emergent findings during the research the
data collection and analysis stage.
The research framework was examined in three large organisations from diverse sectors
and various levels of maturity. This research framework could be extended to numbers of
complementary studies. First, the framework could be examined in numbers of organisations
with similar maturity levels. For instance, PMOs with the second level of maturity could be
investigated through use of the developed framework. Second, the framework could be
examined through choosing PMOs in similar industries, such as research or mining. Third,
the combination of first and second levels could be managed as another direction for the
future study. This would significantly contribute to improving the proposed case study, by
either validating or refining the proposed framework.
Also, the four and fifth levels of maturity in the framework are yet to be examined. In
other words, this research did not cover the investigation of the highest maturity levels, due
to the existing limitations. This could be an interesting subject for another PhD project.
In addition, the outcomes of this study could be examined through appropriate methods in
order to validate the whole research framework. This is one of the directions that this
researcher intends to undertake in his future career.
Also, the proposed knowledge management practices could be examined through
conducting a number of comprehensive surveys. For instance, the proposed types of
knowledge and also the recognised KM challenges of PMO could be tested in various levels
of maturity.
In addition, integrating the research framework with the organisational KM systems could
be another research subject, by which project KM could be collaborated into an
organisation’s KM systems. In fact, this research project is another subject that this
researcher is interested in implementing in the near future.
This original research investigated Knowledge Management and PMO maturity levels in
one of the current major PM methodologies, i.e. PMBOK, developing deeper understanding,
282 Chapter 9 | Conclusions
and contributing new knowledge, and hence forms a strong foundation for future studies.
Future research may explore the study of Knowledge Management in other project
management methodologies and extend knowledge of these areas of concern in project
management.
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Bibliography 293
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APPENDICES
Appendix A - The Case Study Protocol
Background A.
Project Management Office (PMO) is a new approach to improve the quality of managing
projects. Knowledge Management (KM) is recognised as a crucial factor for delivering
successful projects. Contemporary organisations are strongly recommended to develop their
project activities through utilising PMO maturity models. The existing PMO Maturity
Models (PMMM) are process – based, which advise appropriate project management process
for each level of maturity.
Despite the importance of KM in a project, however, KM practices have not been
considered in the mentioned models. In other words, PMMM have not been addressed as to
how knowledge should be managed for each level of maturity.
In order to achieve research objectives the following research questions have been
proposed:
1. To what extent are KM processes and practices employed in the PMOs?
2. How do KM practices contribute to improve the maturity level of the PMO?
3. How can knowledge be integrated in the PM maturity model?
The Case study method has been chosen to cover the above-mentioned gap through
investigating the role of knowledge in different PMOs. The main criteria to select
appropriate cases are those organisations that:
I. Have an office, centre or unit for managing their projects; II. Utilise project management methodologies for managing projects, PMBOK or
PRINCE2; III. Use a methodology to develop their project management centre/unit; and IV. Show strong support of top managers for developing this centre/unit.
This protocol aims to explain key concepts, design of case study, data collection methods,
procedures and appropriate instruments for conducting case studies.
Key Concepts B.
The following specific terms will be regularly used during this research:
• PM is defined as the application of knowledge, skills, tools, and techniques to
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meet project objectives (Project Management Institute 2008a). • PMO, PM Unit/Centre is an organisational unit for developing PM
methodologies and practices through following proper PMMM (Project Management Institute 2008a).
• PMMM is a process-based model to establish and develop PM office or unit in five levels.
• KM is defined as a systemic and organisationally specified process for capturing, creating, organising, transferring, utilising and maintaining both tacit and explicit knowledge of project team members
• Explicit Knowledge is articulated knowledge that exists in current documents while
• Tacit Knowledge is embedded in individuals’ minds and it’s difficult to be transferred or documented.
• KM Practices are best practices or processes for Capturing; Creating; Organising; Transferring/Sharing; Utilising; and Maintaining that have been utilised and/or planned to be employed for managing knowledge within a project environment.
Case study design C.
In order to collect accurate as well as adequate information, multiple cases will be chosen
instead of one case. The ideal number of cases is 5 or 6 , however, we have planned to
undertake this research with at least 3 case studies. The units of analysis are PMOs, PM
centres or units within organisations. Also, holistic approach will be conducted instead of
embedded one.
For achieving quality outcomes, both data and methodological triangulations will be
managed. For methodological triangulation interview, observation, documents analysis
and questionnaire have been chosen while for data triangulation, multiple sources of data
such as organisational information and documents, current processes and procedure and
individuals’ thoughts or beliefs will be investigated.
Case study procedures D.
Followings steps will be preceded during case study implementation:
1. Getting formal agreement from organisational authorities; 2. Obtaining QUT’s Ethic Clearance; 3. Asking organisation to appoint liaison for communications during case study; 4. Assessing and determining the maturity of the PMO, if it is required ; 5. Conducting the in-depth interviews; 6. Undertaking focus interviews; questionnaires; document analysis and
observations; 7. Managing the obtained data; and 8. Analysing case study outcomes through utilising appropriate analysis methods.
Data collection methods E.
296 Appendices
The following methods will be employed for collecting data:
Interview F.
Two type of interviews will be undertaken: In-depth interview; and Focused interview:
For the in-depth one, numbers of questions, will be asked (please see attachment).
Afterward, the focused interview will be managed based upon findings of in-depth
interviews. Both conversational and two-way communications will be managed for all
interviews. This method will be undertaken through following steps:
1. Introducing researcher; the study and aims of interview ( approx. 2 mins) 2. Explaining concepts and key words: PMO, Maturity models; KM practices (
approx. 3 mins) 3. Requesting interviewee to study ,then sign the confidentiality and ethics form
(approx 5 mins); 4. Getting interviewee’s permission to record the whole interview; 5. Asking proposed research questions (approx. 45 mins); and 6. Terminating the interview and asking his/her contact for further clarification if
required.
Direct Observation G.
This method will be employed alongside the study implementation through observing and
recording what researcher notices during case. Participating in the project meetings, formal
and informal discussions, studying existing KM practices or applications in the PMO and
other type of observations will be part of this technique.
Questionnaire: H.
Alongside the other data collection methods, self-administered type of questionnaire will
be employed to improve the quality of research data. It will be conducted among targeted
respondents: Top managers; Project managers; PMO specialists; PMO staffs and PMO
consultant through utilising appropriate facilities, namely Key Survey software.
Documentations analysis I.
This source of evidence is the only explicit knowledge within project environments.
Researchers might obtain insightful information about targeted cases through investigating
administrative documents, work procedures and processes, instructions, reports and other
similar documents.
Managing obtained data J.
• Developing and maintaining Case study database through utilising NVIVO 7 and MS Excel in order to organise appropriate database for case study findings.
• Providing meeting minute for each interview and meeting, then, sending them to participant(s), and, documenting in word or PDF format.
• Providing A comprehensive list of interviewees
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• Analysing recorded voices then, confidentially, keeping them in appropriate places.
• Keeping organizations’ confidential documents then, returning them after investigations.
Providing comprehensive report for each data inquiry method.
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Appendix B - The research questions and Survey-questionnaire
SECTION A: INTRODUCTION TO THE RESEARCH (2-3 MINS)
1. Introducing myself and the research. 2. Explaining required concepts: Knowledge Management (KM), Project Management
and etc. 3. Ensuring that confidentiality and ethics consent form have been signed. 4. Asking for permission to record the interview. SECTION 1: DEMOGRAPHIC (5 MIN)
5. What is your current position in your organisation? 6. What is your education and background? 7. What is your professional background and how long is your experience in Project
management? SECTION 2: GENERAL INVESTIGATION QUESTIONS
8. Please explain what types of project your organization undertakes ( in terms of Research, Strategic, Client ordered, process improvement and etc)
9. Please elaborate how projects are started and finished at your organization (how they are initiated, planned, executed, monitored and closed)?
10. What are methodologies of PM utilized in your organizations? (PMBOK, PRINCE2, Agile and/or others)
11. Has your organization established/developed PMO or a unit to coordinate organizational projects?
12. How the PMO/PSO contributes for managing projects at your organization? 13. How you could find the required knowledge/information, during the project’s phases
(from Initiation to Closing)? Please elaborate it by providing an example(s). 14. How your PMO/PSO contributes to provide, organize and/or create the required
knowledge/information for projects? If you don’t believe so, please explain your expectations.
15. Do you know what the PMO’s level of maturity is? SECTION 3: INVESTIGATION BASED UPON THE MOST RECENT SUCCESSFUL PROJECT
At Initiation phase
16. What kinds of documents/information were required and how they were provided (practices or Technology)?
17. How did you provide the required resource, especially knowledge resources at this stage?
18. How did your PMO contribute to provide above mentioned resources and information?
19. What should have been done or developed to improve the quality of this phase? At Planning Phase
20. What kinds of documents/information were required and how they were provided
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(practices or Technology)? 21. How did you provide the required resource, especially knowledge resources at this
stage? 22. How did your PMO contribute to provide above mentioned resources and
information? 23. What should have been done or developed to improve the quality of this phase? At Execution Phase
24. What kinds of documents/information were required and how they were provided (practices or Technology)?
25. How did you provide the required resource, especially knowledge resources at this stage?
26. How did you manage changes during the execution and how the new knowledge managed?
27. How did your PMO contribute to provide above mentioned resources and information?
28. What should have been done or developed to improve the quality of this phase? At Monitoring and Control Phase
29. What kinds of documents/information were required and how they were provided (practices or Technology)?
30. How did you provide the required resource, especially knowledge resources at this stage?
31. How did you manage the corrective actions as well as corrections? 32. How did your PMO contribute to provide above mentioned resources and
information? 33. What should have been done or developed to improve the quality of this phase? At Closing Phase
34. What kinds of documents/information were required and how they were provided (practices or Technology)?
35. How did you provide the required resource, especially knowledge resources at this stage?
36. How did you dismiss /terminate the cooperation of team members? 37. How did your PMO contribute to provide above mentioned resources and
information? 38. What should have been done or developed to improve the quality of this phase? 39. Do you believe that your project environment/PMO contributed to create
knowledge?
• If yes, please explain what kinds of processes, practices, technology and/or software were used to create the knowledge. Please provide an example.
• If no, please explain what was missed? And how it could have been done better. 40. Do you believe that knowledge was properly captured for that project?
• If yes, please explain what kinds of processes, practices, technology and/or software were used to capture the knowledge. Please provide an example.
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• If no, please explain what was missed? And how it could have been done better. 41. Do you believe that the project’s knowledge was properly transferred?
• If yes, please explain what kinds of processes, practices, technology and/or software were used to transfer the knowledge. Please provide an example.
• If no, please explain what was missed? And how it could have been done better. 42. Do you believe that there were some facilities to help you for reusing existing
knowledge?
• If yes, please explain what kinds of processes, practices, technology and/or software were used. Please provide an example.
• If no, please explain what was missed? And how it could have been done better. 43. Please recall one of the projects which was less successful or failed, Do you believe
that proper knowledge management would contribute to success of project?
• If yes, please explain what kinds of techniques/technology should have been used.
SECTION 4: RATING THE IMPORTANCE OF PHENOMENA
44. Please rate the importance of following knowledge types at each phase of project (1 is the lowest and 9 is the highest level of importance).
Type of knowledge/ Project Phase Initiation Phase
Planning Phase
Execution Phase
Monitoring phase
Closing phase
Project Management Knowledge Knowledge about Procedures
Technical Knowledge Knowledge about Clients
Costing Knowledge Legal and statutory Knowledge
Knowledge about suppliers Knowledge of who knows what
45. Please fill out the following table in order to describe how the required knowledge is
provided at your project environment.
Type of knowledge/ Provision
Exists in Organization
or PMO
Is accessible through existing
procedures
Should be Captured by staff
Should be Created by
staff
Should be Shared/transferred
by owners
Yes No Yes No Yes No Yes No Yes No Project Management
Knowledge
Knowledge about Procedures
Technical Knowledge Knowledge about Clients
Costing Knowledge Legal and statutory
Knowledge
Knowledge about suppliers
Knowledge of who knows what
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46. Please rate the importance of following Knowledge Management processes at each phase of project (1 is the lowest and 4 is the highest level of importance).
KM Process / Project Phase Initiation Phase
Planning Phase
Execution Phase
Monitoring phase
Closing phase
Capturing Creating
Transferring Reusing
47. From knowledge management Point of view, please rate the importance of following sub-processes. (1 is the lowest and 5 is the highest level of importance at each phase).
Knowledge Capturing sub-process
Level of importance
(1 to 5) knowledge Identification
knowledge Filtering Knowledge Selection Knowledge Storing
Knowledge Classification
Knowledge Transferring sub-process
Level of importance
(1 to 3) Knowledge Distribution
Knowledge Sharing Knowledge forwarding
Knowledge Creating sub-process
Level of importance
(1 to 4) Knowledge formalization Knowledge Codification
Knowledge Representation Knowledge Mapping
Knowledge Reusing sub-process
Level of importance
(1 to 4) Knowledge learning
Knowledge Applying Knowledge Integrating
Knowledge adapting
48. Is there anything that I have missed? 49. Do you mind to be approached for complementary information if required? If yes
please leave your contact detail.
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Appendix C - Ethics Approval
Appendices 303
304 Appendices
Appendix D - Samples of interview transcription in SCIENCO
In.Sc.1 Interview
Demographic A.
Interviewee’s background
Senior Manager
General Investigation B.
Types of project being undertaken
R . So in terms of the sort of project it’s a research and development project but it has a commercial outcome in the sense that it’s being prepared for a, or it was being done directly for a commercial client
Project management methodology
R: in general there’s not a formal methodology that’s been outlined. We’re beginning to develop tools within the organisation that stage a project in various ways. So that you’re required to fill out a range of different forms associated with various stages of the project but not, but there really isn’t a specific methodology no.
PMO’s status
R: There are people who are called project support officers but their role is probably more along the lines of… I wouldn’t say book keeping but it’s effectively keeping track of and giving …reports about hours booked to the job, you know budgets that kind of thing. So there’s, there are people who can help us to get those reports out of the, out of SAP which is the accounting/management software that we use across the organisation. Now we can do that ourselves and typically I’ll do that myself but they will also produce reports for us from time to time so…
How PMO contribute to Project management
R: Well currently and this is something that I think has been missing for a while. There isn’t a kind of easy way of maintaining what we used to call production control back in my previous order which was maintaining control over the various aspects of the system that we’re actually running. Yeah. So for example labor keeping track of labor in a more real time manner. I mean we do, we can batch report things from month to month but it’s still a bit of a clunky process. Better management of things like materials procurement, things like that. There’s probably a bit of a disconnected as well between the dynamics of a research and development organisation and the structure of this program. So this program would, SAP was originally designed in a manufacturing context where you know everything was fairly predictable. You know the system may change but there are fairly basic rules that everything develops by. In a research and development environment typically most of our projects begin with us not knowing the research outcome when we start. So we will make an offer to a client or a customer to
Appendices 305
help solve a problem of theirs using some kind of technology but we will be very clear and upfront that in a research cycle we may find out that some of the methods that would work won’t work or that things are not going to proceed as easily as what we thought. And this happens all the time, it’s very common to say oh well we believed that this particular sensor or this technology would resolve the problem.
How your PMO help to manage project knowledge
R: I suppose in terms of knowledge management there’s umm I mean there’s the research knowledge, the technical knowledge associated with particular problems and outcomes in a project and that’s probably reasonably well managed because of course in the context of the research work we do we have a kind of a split priority. We have the priority to achieve the project outcome but at the same time we also have a research priority to do things like get publications or possibly file the patent for a technology or something like that. So there’s those two outcomes and typically the organisation is quite good about emphasizing the importance of publications and things like that. So the research knowledge is usually better managed from that point of view however, the practical knowledge of the use of the technology or the implementation of the technology in a project, that sometimes varies. There is again the potential for a disconnect there. How will I explain it? Umm….the implementation of a…of a technology or some new research based knowledge in an area in a particular sort of area, a mining area…is often half the battle. Maybe three quarters of the battle because the environment is usually very difficult and sometimes dangerous and therefore given the opportunities to actually implement the technology at the coal face which can be very difficult. So, the process whereby that’s done need to be better captured and better propagated to other people because it seems very often that whenever we come to do a new project we’re starting again from square one to try and do ….relearn the lessons that we’ve already learnt on other projects. So that’s an area of issues.
R: no I think it’s largely the project officer or the project leader’s responsibility to attempt to manage that. Certainly for the practical knowledge of project processes umm unless the project officer or the project leader themselves decided to capture that knowledge in some way or develop some kind of personal system, there’s not really a strong system there to do it. No well certainly not in my experience anyway within the division and the flag ship that I typically work. Also , there is no system strategy or process for managing knowledge, it means that , we are at the beginnings of a…you know they are taking steps in this direction so we probably umm you are probably asking these questions at a time where I think there is a growing awareness of this issue. So some very simple things for example that have been passed on and just not being done that we recommend. Are things like post project reviews, for example, going back and actually performing a formal post project review. There is now umm a form to do that which they’ve developed. However, I think oh well I think that’s been developed for a little while, it isn’t typically enforced. Usually what happens is that there’s a limited time available as there always is and there comes a point where a project is completed and people race off to do the next project. And there’s usually very little option or time for or time made available to actually do a kind of a formal post project review. You get ad hoc ones there’s a….
306 Appendices
Level of PMO Maturity
R: Probably I’d have to say fairly mature. It’s not…..the management system SAP is relatively recently introduced, it’s only been with us for three or four years and it’s been quite a struggle to convert people over to that. And I think the role of the project support officers has generally been just to help people who can’t use the software to get the information out of it. But there certainly is not a, typically it’s not a very proactive role. They will you know send you an email when an invoice is due to be paid on a project for example and you’ll have to explain why it’s not going to happen or why it is happening. However, apart from that there’s not really a structured approach to providing support for the ongoing project management. So typically it’s left up to the individual in charge of the project.
Expectations from PMO
R: So typically the expectation there is that we need to be able to dynamically adjust the parameters of the project outcomes and deliverables in order to cope with the realities that we discover as we do the research process. So this is a difficult concept to put into the context of a very rigid umm kind of a management trading system where you know the expectation as you said, you were going to invoice at this stage of the project on such and such a day. And then you know you need to go through and try to manipulate the system to accept these changes. So it’s a…in one sense it sounds like a trivial thing I suppose. It’s not a you know it’s a matter of managing a piece of software but it’s more the context of the … a fairly rigid structure associated with the expectations about project outcomes compared with the more dynamic reality of what actually happens. And usually what happens is that we, to bridge that gap, we, the project manager has to fill in the detail with a lot of explanation and running back and forth and often times trying to convince the client that look you know if you can see your way clear to allow us to invoice you for this stage, we’re hopeful that we’ll be able to resolve this issue at the next point or something like that.
Investigating the KM at project stages C.
Initiation Phase
What sort of document /knowledge are given
R: Okay well I guess there’s the usual basics for an approach of our sort of, we need to know….the scope of the project. The customer, the key deliverables, the time frames, the budget and during the project initiation stage I guess just to clarify are we talking about when we’re at the project proposal stage or are we at the point where the project has been approved? Would you be, do you mean so for example….
How the information are/were provided
R: Alright well typically the process that happens just to give you the understanding and there might be a little bit of blurring here between the different phases because of this. We will either approach or be approached by potentially somebody in the industry and they have a particular problem in their area. So the mining area. And we would propose a technology solution to them. Now to do that we usually will prepare a short
Appendices 307
document, two or three pages describing the sorts of technologies that we think could be used to do that. So in that document there is already …there is already the beginnings of the thinking about planning but it’s not a formal proposal as yet. If the customer or client is interested then they may ask for a formal proposal at which point we will prepare a more extensive document that will probably include a basic project plan like a Gant chart with some time frames and deliverables and we’ll give them a budget for the project.
How PMO/Current system contributes
R: usually at this stage the proposal is simply logged within our publication system. Our electronic publication system, usually….what we do do is we prepare what’s known as a CCF a common costing framework. It’s an elaborate spread sheet that allows the…allows the budget to be worked out accurately so that you can list the people that you want involved in the project and their pay scales. The amount of time that you believe that you want from each of them, the materials’ budgets and things like that. And then you can go through and determine the sort of project that you’re talking about. So if it’s a new technology and development and collaboration then there’s one kind of pricing structure, if it’s direct consulting work there’s another so there’s a range of them and you’ve got to sort it out through that. That project that system allows us to set a formal budget that’s acceptable within SCIENCO in the first step to approval. And then depending on the size of the project that’s been proposed it will then have to be approved at various levels. So up to I think about sixty thousand dollars I think can be approved at the project manager level or one level up. What we call the stream level. Above that say up to about 250 thousand or something it goes to the next one, there are various levels you know for approvals. So all that process kind of defines the context and the parameters of the project. But then in terms of the knowledge beyond that, so I guess I would call that project initiation and if the client has accepted that, has accepted that process, has accepted that….
Expectations to make it better
R: It’s the notion of the project pipeline which is something they’ve been trying to gradually work on but it’s still I think largely not well understood by most of the project leaders and doesn’t as yet provide an easy one stop shop. But the idea that they’re trying to do which I think is good is that all projects should be registered within a common system and the basic area and domain for that project works across should be easily flagged. So there needs to be you know whether it’s a key word type scenario or something like that so that you can search and filter on a range of, you know across all the projects that have been done in the organisation to find out who is working with say scanning lasers for example. You know if I had a project that’s using a scanning laser system and then find out well who is doing the work with you know profile measurement using that kind of instrument or something like that. However, the system isn’t at that stage yet. The idea is there but that’s the kind of thing that I think would need to happen because all too often we find ourselves looking at or working on things and then finding out you know these guys have done something similar. So usually because of the knowledge that’s around in the general population things don’t go too far before somebody puts their hand up and says oh hold on I do that. and researchers
308 Appendices
and scientists tend to be very who are very protective of their knowledge domain. So because of that people pretty quickly let you know if you might be transgressing into their area. But it would be a lot better obviously if it was a system whereby you didn’t have to stumble upon it through that way. And so ….so at the moment the PMO doesn’t do what I think it needs to do is to provide a system whereby those sort of fundamentals can be flagged and people can identify okay well this is something….and as you say not only to avoid you know issues with people who…. You know from other divisions or outside your own group but even within your own organisation. We have a pretty good feel say the group that I work in my team is about five people or so but I’m in a group of about 25-30 people and we know pretty well what we all can do and people have a pretty good idea of what people have worked on. But it’s still umm there is still a specific need I think to be able to search through a PMO to identify or individuals or identify the particular individuals that have worked with a particular type of technology. And again there’s no formal way to do that. So as a project manager or project leader I might know vaguely that this person over here has experience in writing visualisation software. But it would be a lot easier if I knew that there are three people who have had specific experience with this type of technology and I can discuss with them or with their team leaders to find out about their availability for a project.
Ordering the KM process at PMO
R: Well we umm the creating and capturing is still not happening well enough for us to be able to, I mean it is creative to an extent and it is captured in various forms. Well I suppose if you really want to say you’d probably focus on organising because the umm it is created in various forms. But no doubt the information is out there and it’s captured for various reasons. But umm it’s like they’ve poorly written relational data base where you’re storing the same information in lots of different places and sometimes it’s contradictory when in fact it ought to be stored in a common location and then able to be queried for specific reasons. And that’s what we really would like to have. So yeah organisation is probably key there
Planning Phase
What sort of document /knowledge are given
R: Okay the formal requirement internally once we get to the planning phase are not very, there’s essentially once the project has been awarded and commenced so we’re into that phase of planning how it will actually be executed. We do have to provide, the key thing really that’s required for the PMO is the project timeframe. The deliverables but even still, even within that context they are really mostly just interested in the milestones and the invoices associated with them. So we might from a project point of view be saying I need to deliver this technology by the 10th June or something and then the client will be invoiced to that milestone. From RMT side of the things the only thing that the 3 dimensional system requires is milestone on the 10th June, invoice payment of forty thousand dollars or whatever, that’s it. There’s not a great requirement from that point of view to do much more in terms of the project management. Oh except of course they do require the knowledge of how the people’s time will be spent. So labour has to be planned in terms of you know people’s time will
Appendices 309
be allocated, so many hours for that month. So say I have a project with a dozen people working on it, I am required to plan out where their time will be allocated throughout that project. However, typically what happens is the system automatically will just allocate it across the board on average. So if I’ve said that I need a particular person for twenty per cent of his time for the next six months then the system will just boom, boom, boom, boom for the next six months, it will put him in at twenty per cent each month and that will be that. You know I can if I choose to, I can go back and request that, well in fact I believe that I’m only in for eighty per cent for the first month and then only ten per cent for the rest. I can make that kind of request but ….
How the information are/were provided
R: In that context one of the things that has to be reviewed and it’s not probably managed as formally as what it could be, it still needs improvement I think, whenever you are proposing a new project you are potentially developing or discussing or proposing technology solutions. And there is the issue of umm the potential to, that intellectual property is created that SCIENCO needs to manage carefully because that’s our key product if you like is intellectual property associated with the project. And so one of the things that is supposed to happen in the initiation phase is that the project proposal is reviewed by various people within the management chain in order to say are we offering something to the client that we want to protect from an intellectual property point of view? And if so how do we define that? So umm there is a procedure there to do that in a sense that the various levels of management are supposed to review and identify those kinds of areas and it’s up to the project leader to kind of at least give them an idea. But umm again as I say, it’s probably not a good, there’s no good formal mechanism whereby that can happen. So it’s still you know largely based on reading the proposal, having conversations about it and then making a decision. You know which works up to a point but umm in terms of a formal knowledge management system it’s not really there.
How PMO/Current system contributes
R: there’s no formal mechanisms for that at all. In fact that’s probably one of the greatest challenges within the organisation is the fact that there isn’t a straight forward way of even finding out you know is this a domain which somebody else might already be doing something in another division for example in SCIENCO. And as you can imagine a very large organisation spread out across Australia and often it’s only by word of mouth that you might find out oh actually somebody down in Sydney was doing something similar to that you know five years ago or eight years ago or something. But there’s no, the PMO doesn’t provide help in that way. I mean it’s up to again the project leader to search on the intranet and find out if anybody within SCIENCO has … There is a system but there’s no incentive or reason to do that because how will I put it? Well in the end all they ultimately care about is that the books balance at the end. So that as long as the time is covered and you know the invoices are paid on time the system doesn’t really care too much and the project support officers are really only there to ensure that the books balance or that the times add up. So, it’s you know they do want to know about large capital items. So for example if I’m working on a
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project, I had a very large project over in Western Australia a few years ago and there were some very large capital items that had to be purchased. And so I did need to let them know well okay in April we’re going to need to spend thirty thousand dollars on some equipment, boom. And then you know a couple of months later you know a bit more. So that kind of thing they like to know but again it’s the motivation is primarily from the point of view of managing cash flow and budgets. So it’s not, it isn’t really done for the sake of the project it’s done for the sake of the organisation. I: How does the intranet work or you know for instance find for instance so people know? R: Not real good it could be a lot better. It could be a lot better because they are attempting and they are attempting to try to standardise a little bit more the structure of the different groups and things so that you can search for key words about what various people have worked on. But it’s still a long way from being really well developed and there’s still a lot of knowledge which is retained in people’s heads basically. People who have been around for a long time and they know that that fellow down there was working on a project like this ten years ago. So no the PMO doesn’t really capture that knowledge or make it easily available that way.
I : Does your PMO ask any kind of information knowledge at this stage? R: Let me think just to make sure. I would initiate…at first glance I would say no, you just think if there’s any way that it does. Again probably not in a formal way. There is the, during the planning process there is the opportunity for management to identify or to request that we essentially protect certain parts of the intellectual property that we might be creating. And certainly capturing some kind of record of that might be requested but it isn’t a part of the, it’s not really a part of the PMO. It’s not part of what the, a formal part of the process. So once you get to this point it really does become more about the project leader managing that, you know in a more personal way, sort of an ad hoc way. I: What sorts of practice or process or procedure are being undertaken by your PMO? R: Let me think. I’m just thinking of their performance at the project and I …at the planning stage I don’t believe so, no, no. I don’t believe there’s any formal process. the knowledge that is come through at the planning stage is purely the structural knowledge associated with that particular project and its particular financial parameters. It isn’t really associated with the knowledge generated in the project or even the plan of knowledge of umm so typically that kind of thing will be bigger. Will actually be happening on an informal basis, not only by the project leader but also I suppose by graduate staff as they start to develop their plans for what they’re going to do. But it’s not a, it’s not, there’s nothing in the PMO that really captures that I don’t believe.
Expectations to make it better
R: I think probably at the planning stage, because again the planning stage things are still….not aware and it may not be known. But ideally would be the first thing that allows you to begin a register of potential knowledge base. Not knowledge of you
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know new knowledge that’s going to be developed in the project. So for example a system whereby fairly quickly and easily you could say well this project umm is going to be associated with the following work. And just you know and at the planning stage has identified we’re going to be developing you know knowledge associated with this aspect of this industry. Using this technology perhaps umm something that collating or at least classify in broad categories or domains the kinds of areas that we’re going to be working in so that when you go back to it later on you’re able to say well…or when somebody outside the project looks at this information they can say okay looks like you’re going to be working in the areas of X, Y and Z and they can provide some input or help to assist you. Or they can say well that looks very much like a project that we have here that is doing something similar. So you can just kind of classify in broad terms the knowledge that is likely to be generated. That would be sufficient I think at the planning stage. Just to… I: So what about knowledge capturing? R: Well because as I say at the planning stage typically there’s not, the knowledge that’s generated at the planning stage is typically, well in my experience, it’s not very significant. Or it’s not a very complete knowledge. You know ideas are being generated but they’re largely uncertain. Speaking from a research and development point of view if you are working with something that you know all about already you can probably have a very clear idea. But if you’re working with new technologies or technologies that haven’t been applied to that problem it’s likely that umm you won’t have specific knowledge. What you’ll have is hypothesis. So you will hypothesise that I will be working with this sort of equipment, I will be doing something in this area and I think at the planning stage it would be sufficient to be able to categorise the kinds of domains that you’re working in and then as you then move on from the planning stage you can begin to fill those, fill in the details. So you’re basically at least laying the ground work for the kind of knowledge map if you like that’s going to be developed later on. So you …it just gets you out in the big areas but you may not have a really clear idea of what’s going on at that stage. If that makes sense?
Execution Phase
What sort of document /knowledge are given
R: Same question and I’m ….I guess I’m trying to think of it in execution context specifically now. Again the PMO is not umm really set up to deliver that kind of information or knowledge in any formal way, at least that I’m familiar with.
How the information are/were provided
R I suppose the process is umm…the processes are there to a certain extent but again they’re largely informal. What will happen or semi-formal I should say. Typically within your group we will organise projects or group meetings where we will review projects and discuss the status of the project during the execution phase. So what that will involve is sometimes everybody in the group but more typically the sort of the leadership team. So the team leaders [?] leaders came in together and discussing what’s going on with their projects and where they’re at. And through that process there will be opportunity for people from outside the project to provide input to the
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project to say look if you’re working on such and such have you considered doing this or that. so from that point of view we’ve developed mechanisms whereby we seek to provide knowledge to the project leader about the situation that they’re in. But it’s not done through a structured project management system. It’s done through a…it’s largely done I would say on the capability side. So it’s done from the group and team structure looking at, oh you’ve got a project working in this area and we have people with capabilities in this area, let’s talk about how those things can work together or let’s get some ideas going about that and what can be done. I: Do you have this kind of meeting for instance for planning or… R: The meetings will be usually fairly regular and they’re not specific to one project. So they will be across…. I suppose from that point of view you could say that those meetings could apply across the various stages of the project because they’re not typically, they’re typically organised as I said on the group level. So if you think of this matrix management model, in a group we have a range of people who are project leaders. Or working on projects. And those projects may be at any of the different phases when it comes time to discuss, in our regular meetings, what’s currently going on, what are people working on? So at any time within the project management cycle I suppose it’s possible that you could be discussing with others this is the situation that I’m working on, these are the sorts of challenges that I’m facing or I think I will face. And then it’s an opportunity to discuss those things and to have other people provide input. So I suppose that’s probably, and I guess I neglected to mention it in those earlier phases because usually the focus in those meetings is on the projects that are currently happening. So it’s on what …so it’s much… So people might say oh I’ve got a project that I’m trying to get up in this area and people might give some advice about that but it’s usually the focus will tend to be on what’s going on now. What are we doing and what can we, you know, how is everything tracking? You know do we need extra resources allocated to this project at the time and certainly from a knowledge management point of view there’s two questions I suppose that come up fairly regularly. One is how can we help you kind of thing, other people thinking about oh you’ve got a problem here could we do that? And the second one is probably what sort of intellectual property is being generated in the project and should we be thinking about publishing or possibly signing a patent or doing something like that. so there’d be an intention to try and capture knowledge to a certain extent through that mechanism. So as I said the organisation is pretty strong on you know the fact that our product if you like is….intellectual product is knowledge. That’s the product that we have. And so capturing that at the various stages whether it’s through publication or through umm patents or similar things or.. you know modifying the commercial terms of a project for example. Or making sure that the commercial terms allow us to have freedom to operate with our technology that we [?]. Those are the kinds of things that often will be discussed.
Ordering the KM process at PMO
R: we’re probably pretty good on the creation and capture side of it because it’s a key part of what we do and …again talking about the matrix model if you like, the capability side, the input side if you like of the matrix…is the domain which we are
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concerned mostly with the creation and capture of knowledge. And that’s because the whole point of that’s the capability development is to say we want to maintain and develop our knowledge base, our capability but the organisation of that knowledge so that it is efficiently applied to the output side if you like. To the present and future projects that’s where I think there’s a bit of a disconnected. Also I’d have to say it’s probably the transferring more than anything. Because the information has this certainly created, certainly captured….it seems quite well organised in the sense of being in its own domain. If the knowledge is well organised, well-structured you could go there but it isn’t being transferred into a kind of a useful format from a project management point of view. Yeah it’s probably still in the organisational side again I think yeah you have to have those basic organisational things done before you can then do that kind of transfer. So I mean every…you know there would be issues on the transfer side as well but that is first things first yeah.
Expectations to make it better
The PMO is primarily focused on budgets and invoices and the formal financial aspects of the project. R: There is definitely I mean that’s yeah I wouldn’t want to minimise it completely. They do do a good job of capturing the I guess the basic stuff, the bare bones of the project what the you know what the project is, how it is structured and what’s going on. So there’s no doubt about that, it does all that kind of thing very well. But the meat of the project and how that is…is…. Everybody is very clear about it and everyone is conscious of it but they’re not really as concerned about how that is made available to existing or new projects. I: so what do you think that would be good to your PMO? R: In terms of knowledge management umm I’m trying to think of the best sort of way that that could happen. I mean I think what needs to happen is that the umm the information that’s been captured already through the structures [?] called e-publish for example where papers and reports of all sorts, internal, external you know publications, papers, everything is logged or is supposed to be logged into this e-publish repository. So we have a very well structured mechanism for capturing that kind of knowledge creation and….there’s no real connection between that and an appropriate management structure. What would be ideal would be, as you say, an effective knowledge management system that allows that kind of information to be umm searched, interrogated, examined, from the point of view of the project so from the point of view of matching a project’s deliverables or outcomes with the capabilities and the knowledge that’s already been generated. At the moment that isn’t typically done.
Monitoring
What sort of document /knowledge are given
R: …project progress and a similar kind of dynamic. So in terms of information and knowledge provided for the project the basic framework of the project as we’ve already discussed is provided you know. We are kept informed of is the budget on track you know. We are notified you have a milestone coming up, you need to invoice.
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If you can’t can you explain why? So those basic I suppose you know baseline, bottom line things that are managed but in terms of providing information, knowledge or guidance through that process there’s probably not a lot. It’s not very strong at all and certainly in terms of providing some means of using that information from prior learning from projects it’s probably pretty weak I’d say. Again it’s more the informal knowledge of the project leader who has done projects before and has had experience. So. I mean that is one of the things that they put into the structure in the initiation phase I didn’t mention. But it is you know the project leader is if you like ranged in certain categories in terms of have you done projects in this sort of domain before? Do you have you know how much experience do you have? What’s the biggest project you’ve managed to date? All that kind of thing. So there is a process of trying to establish the credentials if you like of the project leader and that is associated with the project risk. So there is you know there is the notion of the amount of risk being engaged in the project. But that kind of thing is really in the initiation phase. Once the project has begun it’s not formally pursued. I suppose it’s not …it’s not usual to find an enforcement of this kind of thing as well but if I dare say some of these forms and things are available but they’re not being utilised in the sense that from time to time we’ve had you know…the information put across you know all of these things have to be filled out and ready to go for any new project. But they tend to get filed and forgotten so nobody really uses them or looks at them and therefore there’s nobody that’s really asking for a lot of that information during the time. So if a project leader is managing you know two or three different projects and they have their own research work as well it’s typically likely that they’re not going to spend a lot of time filling out forms that just get put into a directory somewhere and forgotten. So that’s just the way of things so….so again it’s a…that’s a part of the process thing. So not a lot this, again it’s the same basic the bare bones information is provided. What type of information generally asked by project managers? During the monitoring phase…well typically I suppose it’s…our expectations are matched to the, what the system currently provides. So most project managers just want to know from the system how much money has been spent. Whose you know whose booking time to my job? You know how much budget I’ve got left and more or less can I have however enough money left to finish the project. So it’s you know the bare bones financial information which is I’m not trying to minimise that. I mean that’s a key aspect to managing a project. But it does ignore the knowledge dimension a lot. You know the…it’s up to the project leader in an internal or an informal way to deal with the question of are there you know are there technical challenges that haven’t been resolved yet that I need to resolve? Or are there issues that I’m going to face in this process that could stop me from completing the project? That’s traditionally left to the project leader to use his experience or his or her experience. How change are managed R: Yeah so well typically so if there’s a change of …for whatever reason….some kind of approach or variation will have to be carried out. So if it’s a change that’s going to impact on the time or the budget then we have to submit a project variation. So at this point there is a, there’s a…the system requires that we develop a… we put together a small mini project plan if you like, again using the (6CF?) form we work out the cost of
Appendices 315
this variation work and how long we think it will take. That has to be submitted internally. And then a legal modification to the contract has to be drawn up. I should say almost all of this is on the assumption that you’re dealing with an external client. If it’s an internal strategic project that will be a very different story but those are much more fluid anyway. So I’m you know again dealing with an external client where there is a contract in place. In that sort of a context the umm the variation has to be submitted, approved by the client and then you can go on. So again it’s really, what they’re mostly concerned about is the time and the dollars. And you can invoice on time or if you can’t then there’s some… I: is here any system for change management? R: Okay again you’re spot on, there isn’t a system or a systematic way of doing that. It is umm typically again I suppose those project meetings might be an opportunity or even informal meetings between project leaders or senior people there’ll be the opportunity for conversations. People will say look you know umm well let’s say you’ve tried one type of sensor for a particular occasion and it hasn’t worked very well. You might start looking around and saying well what might work better in this scenario? But that key bit of information which is this sensor doesn’t work very well in this environment that’s not formally captured which it should be. It should be captured because it’s an important piece of knowledge that we should be building on. It’s informally captured I mean it becomes known, it becomes common knowledge if you like within the group and certainly from a capability point of view again it’s likely that you know there might even be a publication or something that comes out of it. Because you might then implement a different technology that works and it might be something new and therefore you say okay we’re going to publish some results that we’ve got showing what we’re going to achieve. But that isn’t captured by a knowledge management system at all. I: Is your KM satisfactory? R: Well that would be not certainly Expectations to make it better R: okay if you could be….a little more specific in terms of you know you can get some actual hard data usually about performance and things like instruments and stuff like that. It would be very nice if they system was able to identify and categorise the kinds of umm you know first of all the knowledge domains that you’re working in. So it might be, because it might be something about a…something to do with a piece of hardware a technology or an instrument but it might also be something to do with you know a software implementation or learning about you know finding that a particular method of processing breaks down under these circumstances. It would probably be good if they system had some way of capturing internally that kind of thing. Now I see an issue here though with the fact that again amongst research and scientific, people of research/scientific mindset there will be a tendency to kind of protect their knowledge to a certain extent. So sometimes the lessons learned may not be captured or be forthcoming because people were keen to say well oh you’ve got that information to get publication, I don’t want to just put it out into this you know…so there would be a need to reassure people that a knowledge management system is a secure system. That it’s used internally. That kind of thing just off the top of my head thinking about it
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that would be an issue in this kind of environment because people are very happy to view the knowledge generated to get as I said to put it into this knowledge repository to be published. To be publications or to get patents or to do anything. That’s the kind of thing that will reflect well on them, it’s useful from a career development point of view so they’ll do that. But the incentive to put it into a knowledge management system from a project point of view I think it would be, it would be important to make the system you know fairly streamlined so that people could put the information in without having to umm…well without having to sort of rewrite their publications or do you know do things along those lines. But that’s where I can see there could be some issues. You know most people are relatively open about things but I think you do have those people who will be kind of closed about their knowledge. Closing What sort of document /knowledge are given R: one of the key things at a project close out there’s two kinds of knowledge I suppose that need to be captured. There’s the …there’s knowledge related to the project processes itself. And they can be things like well we’ve learnt that this particular client is very slow at paying invoices. And they are very and we need to develop better mechanisms to deal with them or in the future we need to ensure that our contract is tighter with these guys. Because that sort of that kind of knowledge and I mean that’s just an example. How the information are/were provided R: There’s a whole host of project related processes that we might have discovered. There was a problem here or we ended up travelling to site a dozen times. If we planned it better we could have gone three times, you know something like that. Capturing that is the purpose of the post project review and as I said we traditionally although there is a form and structure for doing some kind of post project review, that hasn’t typically been used a lot. In my experience it has been used very little. So the project is done, people will write the final project report and even that they’re usually rushing to get that done for the client while they’re trying to pick up new work or do other things. And you know once that’s done the thing is put to bed. From a system’s point of view the project management system once the last invoice has been paid or it’s been invoiced, it really is, it’s no longer, there’s no longer much interest expressed Ordering Km processes R: From the point of view of the knowledge created in the project, the technical knowledge the research and development knowledge usually the staff involved are usually pretty strong about again capturing that knowledge and you know giving things like publications and whatever. That’s often if you like the reward at the end of a project for the researcher is to say when we did this project, blah, blah, blah yes but I got two publications because I got you know I did this and I did that. And that’s kind of the umm the knowledge use that’s there. So the …it’s pretty strong on capturing the knowledge. And I suppose from an organisation point of view you could say it’s even, the knowledge is in a sense organised in terms of that kind of a thing, in terms of getting you know publications done and it’s put into the knowledge register but umm
Appendices 317
the key area of relating that information to the project management system there’s a big gap there. And once again in terms of what to do about that I’d suggest yeah it probably you know is vital I think to have….some mechanism that relates the domain of operation of a project which might be a particular part of a say mining industry or particular parts, or particular clients or whatever, relates that kind of domain knowledge with the research and development knowledge that’s been produced. So that we’re able to say okay we learnt the following about the use of this type of technology in this domain and in future you know we can say do this and this and this but don’t do that. You know for a … I’m trying to think from a point of view of a future project leader trying to use the information what they would like to know is what worked, what didn’t and what don’t you know. What were still open questions? So that often happens and as I say we do tend to do that with project management. Well not project review meetings because not so much that but these group meetings we will often talk informally about how a project went and during that time again you know the senior leadership might be encouraged to discuss alternative ways of doing things or saying well we could try this and this and this. But it’s not you know it’s not been captured in any way apart from the knowledge is now shared amongst the sort of the senior leadership group. And you know maybe other staff as well but it …although that’s good you know and that does grow the knowledge of the group it’s not a…it’s not been all logged, recorded or organised in any sort of formal way. Expectations to make it better R: Yeah for sure so I think the umm the key thing that a formal system should do, it should be able to easily classify knowledge according to the kind of the capability areas. The sorts of areas in which you know the knowledge is created or the kinds of people that have the capabilities to do it. The domain of operation of the knowledge, so where is it being deployed and the limitations, the known limitations of various technologies or I mean I keep saying technologies because that’s a common one but it could be even processes or approaches to doing things. So you know what may have worked very well in one particular domain may not work very well at all in another and that might just be a process or it could be you know the way that a project has been rolled out or chosen to be rolled out might work very well for one type of but not for another. Kind of like oh as an analogy I suppose if you’re studying for physics or chemistry it works very well to memorise a lot of facts. But if you’re studying for a Maths exam memorising a lot of facts isn’t going to do it. What you have to do is do lots of …solve lots of problems because it’s the process that….so you know depending on the domain the way that you assimilate the knowledge is actually, can be very important as well. And it’s the same thing with projects. I think that sometimes for some projects where you’re dealing with umm particular types of environment it probably you probably are going to have to go through a much more formal trial process where you actually trial different technologies or things in order to see what will work. And then you should capture that information for the future whereas in other areas we may be able to say well no we’ve got a pretty good idea of what’s going to work here or even you know it’s a waste of time to trial something here because we’ve already done it in a similar area. So capturing that kind of knowledge as well, so knowledge of the domain, the sorts of technologies and the process that are working
318 Appendices
in that domain and that environment that’s the kind of thing a system should do. And again you know it’s a challenge because there’s such a thing as domain expertise within a research and development organisation and there’s probably a certain resistance, I know this is something that people struggle with when they develop sort of expert systems, there’s often a resistance to umm on the part of the experts to believe that the system is going to be able to do what they do. So they like to be the person who is approached and can you tell me what, how do you think this would work in this environment? Or something like that. So you know, I think one of the challenges facing the development of a knowledge system is that open sharing of knowledge.
General explanation D.
In terms of the sort of project it’s a research and development project but it has a commercial outcome in the sense that it’s being prepared for a, or it was being done directly for a commercial client. So it’s not a government funded project it’s a direct industry project as we call them. And it’s the genesis of the project is the background of a prior more research oriented project using the laser scanning technology to detect and volumetrically analyse coal in coal wagons and things like that. So in terms of the knowledge coming into the project there was specific knowledge that we had gained and technology that we had developed in the earlier research project but it was how will I best put it? It was a surveying tool almost. So it would acquire data and it would …it would allow statistical analysis of the target you know later on. So post processing. And that allowed us to develop the statistical information. What the new project needed to do was to use that information in real time to provide information to the client about what was going through their plant at any time. So it was an interesting because we had to transfer that knowledge in that sense from I guess very much a research oriented mode to a real time 24/7 type robust software package. In terms of the transfer of the knowledge there was also a secondary challenge. And that was in the first project I was responsible for developing a lot of the software. So although I was the project lead I really did the bulk of the work because it’s a very small research effort in some ways. Not small but it was relatively contained. But in the new project I had software engineers who had to implement the new version. So I had to transfer to them an understanding of how the technology you know worked. So in terms of tools to do that the, there are several things. One, the most basic and fundamental thing I suppose was the actual source code itself that I’d used previously. Sitting down and working with the software engineers to say okay these are the modules that are available within the source code. So that involved providing a design specification based on the source code that was available. In terms of capturing that knowledge and ensuring the software engineer in question, there was one particular engineer who had to do most of the development work, to be sure that that person had that information there was a point that I required a design document back from this person to see that they’d actually understood the processes. And I think maybe there was an opportunity for something to be done a little bit better because the …there are kind of two conceptual levels at which the thing works. There was the bare bones of the software and understanding how to make the thing work and work in real time and
Appendices 319
communicate and all those sorts of software related low level things. But there was the high level conceptual concept of how the detection process worked. And that kind of knowledge you know which is more a theoretical or research oriented type of thing was more difficult to transfer because it had to be re-implemented in a new code base. It really required that this person understood that knowledge very, very well and I think there was a… I know there was a good period of time where there was a struggle to confirm that this person understood and I was under the impression oh yes they understand what’s going on and they’ve understood it. And then it wasn’t until you know several weeks down the track that I realised that some of the fundamental ideas haven’t yet been captured here. So in terms of you know knowledge management I guess I can see there looking back on it, although I wouldn’t have used those terms, I could see that there was an opportunity there for something to be done a bit better in terms of transferring that knowledge and you know capturing what the core ideas were. In terms of tools to do that one of the things I’ve done in other projects before this and I started to do almost you know instinctively and this was to break the thing down into you know structure diagrams. Either flow charts or things like that, but also even kind of pictorial not …I’d shy away from the term you know mind map or anything like that but you know more conceptual diagrams that just sort of allowed the picture to build up in that person’s mind of what it was that I’d been doing. Because ideas you know are intangible and so difficult to manage that process obviously of ensuring that the other person really understands what it is that you’re after and why it matters. So there are certain aspects of the detection system that there were subtleties in the way that it was designed that made a big difference in how well it worked. But if you didn’t understand it you could, you might think it didn’t matter, I’ll do it my way or I’ll do it this way. So umm so that’s one thing. Then there’s the second stage of it as we’ve come to the end of that project. Well the project is still ongoing we’re still working with this client but we’re also now looking to commercialise this product. So we’re now in a position where we’ve developed documentation and put it out to various commercial entities to see if they’re interested in taking the technology on and further developing it and supporting it as a commercial product. That has involved transferring that knowledge and understanding to them. And here I think one of the key methods that we’ve often used here at SCIENCO for capturing that information comes about, and that is that we typically will look to publish. You know scientific publications of our work where it’s appropriate and inevitably in the process of developing a paper, whether it’s a journal paper or a conference paper you have to go through and explain how the thing works and break down those ideas in a much more formal structured manner because you’re producing a document for public consumption. So one of the things that happened was that I presented a paper on this project to a rail engineering conference and using that just slightly modified and a bit more detail, that formed a core technical information that we put out to tender or put out for reviews of commercial parties. So I think and I may have mentioned this last time, but I think that that’s one of the key ways that we capture knowledge and transmit at SCIENCO. Is that we have the project going on here, and there’s almost three lines. There’s the project itself and the client, there’s the kind of the knowledge capturing process of publications and papers and then there’s also this commercialisation line which is best
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to transfer it on. Do you believe that your project environment/PMO contributed to create
knowledge? R : No I’d say the knowledge creation is typically a fairly free process within the organisation in terms of the fact that people can use the tools that they prefer. So some people don’t use (Mal??) for example they’ll do other things. They have their own preferred methods you know people tend to be fairly umm open or free in terms of the tools they use or the processes they go through. Probably because it’s most… I: What sort of practices have you used? R: Yeah these sorts of things. Well we certainly for a lot of the things that we do and I think there’s a slightly different approach at the moment but it’s one, it was a successful large project that I managed about four or five years ago. But brainstorming sessions was one of the things that we did do, we sat down and I had an idea of how I thought something should work. And I took it to the group though and we talked through it and we spent you know several hours in several meetings going through and fleshing out the bones of how the project was going to work and how the different parts of the system would work together. So we definitely did that. In terms of sorry in terms of knowledge creation that’s definitely a tool that does get used. Being in a research organisation there’s also as I said I would say there’s probably just as often or maybe even more often will typically be one researcher who will spend a lot of time developing the concept themselves and fleshing it out and then they will communicate that idea. So there’s a kind of scientific prerogative almost of people from a science background in particular tend to enjoy that process of discovery. And we’re encouraged within the organisation to spend some time you know just working with ideas and thinking of ideas. So there’s a certain amount of time that’s made available. So that’s certainly another tool if you like is that we’re encouraged to have, we’re in a capability development time…and that might be going to a conference and getting some other ideas or doing some training. But it might even just be you know spending a couple of days reading some journal papers and doing some work in an area to try and get some ideas. With the intention that you know there’s a problem here in industry or something that we’re looking to solve and I’ve got an idea, I want to try that out. So we’ll play around and do some things. And maybe one or two people will work together and they’ll do a little trial of something and then produce you know a…what we often will do is what we do is like a demonstrator concept and this is something which for this project as well we did do. We have a weekly group mining technology discussion group we call it. The group gets together it’s only half an hour and somebody will present something on what they’re currently doing. So they’ll and you know the group is about 25 people. Not everybody always shows up, it’s usually an audience of say you know 15 people or so and you’ll present something on what you’re working on. Probably you know no more than half a dozen PowerPoint slides, some ideas and that’s a good process in terms of not only I guess it’s a combination of knowledge generation and knowledge capture and transfer because you’re proposing,
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you’re raising what it is that you’re proposing. During the process of delivering it people talk about it, it spreads the idea to the group…so that everybody gets a…and by the end of it you’ve had to formally connect the dots on your own thinking. Because you’ve transmitted it to others. So that’s a powerful tool within the group that we’ve, our current group leader initiated that a couple of years ago now and I think it’s been quite successful in terms of doing that kind of knowledge transfer. So that might sound a bit unrelated to the project stuff but typically things that you’ve presented are associated with particular projects that people are working on. So it becomes a method whereby it also informs the wider group of what’s going on in a particular project because we might have up to 25 people you might only have 2 or 3 working on a project over here and it’s good for others to get an idea of what’s going on. Yeah well probably there is more of this kind of thing beginning to happen from the point of view of the there’s been more attempts to do things like workshops. Develop people’s abilities to I mean even just to do basic things with project management like using Gant charts and certain things like that. There’s been…so there are, probably in the last couple of years there’s been an attempt to start doing more of this kind of thing. So some of the people who are newer to the organisation have gone on some of these courses and I think the impression I get, the feedback I get is that you know it’s a good start in some areas but umm …. In terms of the knowledge creation I think it’s probably still a ways to go. So we are encouraged to you know do this kind of thing in informal ways as is aid you know within our group structure we are very much encouraged to those sorts of meetings and we have them and you know we do, we will discuss not just the specifics of individual projects but the processes around it at times. So that kind of thing will happen as well. But in terms of umm well let’s see… I: What about the project briefing for instance or best practice, do you have something like that? R: Yeah. Project briefing yes we will have, SCIENCO you know we’ll do some briefing about yeah things like you know giving you know giving overviews of projects doing you know project presentations doing that kind of thing. That happens quite a lot and internally umm in fact this is an area where the strategic projects which by strategic I mean typically internally funded projects that are more focused on developing you know… R: Yeah for or doing things with in terms of more pure research and development which may not be directly funded by, so it’s not solving a particular problem for a customer but it’s a…so that kind of project which is, has a different kind of a structure to it, although usually it’s not as, it’s not tracked in anything like the formal ways of an external project because there’s no, you don’t have the external pressure of invoices and deadlines and milestones and deliverables. One of the things you do usually have is a more formal process of presentation of project briefing. So what are we doing, where are we going, what have we found out, what have we discovered? So that kind of thing does happen in that context. So again I think what we see here and I suppose it’s becoming clearer to me talking about it is that those internal projects tend to be more capability oriented. You know developing, they’re more of an input side almost if you like of growing our capability and that side of things requires (?) and capturing that knowledge and doing things. So there is the requirement to be very clear about what it
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is that you’re doing and part of that briefing will always be well yes there’s some technology here that we might be looking something in terms of a patent. Certainly you know what publications have you done, what publications are you planning to do? So that kind of thing would be relatively strong in that kind of domain. On the sort of outlook side if you like the external side it’s probably less, it’s probably less strong. Because the real, there’s an awareness of it, but the real emphasis tends to be on those more fundamental aspects of a project. The deliverables, milestones, and budget you know. Do you believe that knowledge was properly captured for that project? R: Okay at the risk of sitting on the bench, I would say yes and I think ultimately yes we do capture the knowledge. And we have successfully transferring it onwards and I think probably the umm one of the key processes that actually helped to do that was the process of publication because it forces the researcher to formalise his or her ideas. So in this case things which were in my mind, but maybe not umm maybe not formally enunciated as principles or theories…or concepts….had to be structured in that way in order to demonstrate what I’d done and to talk about it in a formal publication for review. So that’s a key method that was one thing. And even more so then moving from that point to the point of umm then providing that as documentation for a potential commercial partner. Because they really want to know you know there’s one level of scrutiny that comes from someone reviewing a paper but a much greater level of scrutiny in some ways comes from a commercial client or it can come from a commercialise-side where they’ll be saying what am I really getting myself into? Do I want to sink time and effort and potentially money into something, is it going to work? So those steps are very good. The reason why I say yes, so I say yes ultimately, the reasons why I say no or with a process is that internally and in terms of the knowledge transfer internally to other staff, I think there was some deficiencies in the way that that happened. And it occurred to me and maybe it’s only been on reflection afterwards that using that kind of process of formalising the knowledge into a publishable document would have been well served to have had that information available internally earlier so that these people, so that the software engineer I was working with could read through that and get a coherent understanding of the overview of the project. Having said that one of the potential failures of that is very often when we publish we can’t, we don’t reveal the underlying techniques and technologies that we’ve used or even the methods perhaps. Because there might be some commercially confident information or know how that we want to use for other projects. Or potentially information that could be patented so we can’t you know we won’t publish that. in those cases and even you know even when those sort of things don’t apply you never go into the level of detail in a publication that you might need to go into when you transfer the knowledge technically to an associate. I: So my question is that in that specific let’s say section do you have, do you think that your organisation has some sort of things…for instance your intranet or something like that to help you to capture that knowledge? R: Yes. And that’s a good question and a good point and we have used, we do use a confluence website which is a part of the SCIENCO intranet but you can set up specific
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pages or project based pages where you can put information. Typically what happens and this is a valuable enough thing in itself. Typically what gets recorded is the nuts and bolts of the project. So IP addresses, the different machines, pass words, log in details and things like that. And it’s all knowledge and it’s all invaluable stuff that you have to have in order to do the job, and particularly if you’re working on multiple projects and you come back to a project after two or three weeks. You know you think oh now how do I log into that machine? So at a superficial level that kind of knowledge, the working day knowledge is captured. For some projects in the past and I’m thinking about other ones at this time you know we’ve been probably much more exhausted about keeping source code and things like that available through the intranet. We do use SBN which is a sort of a source code repository system. So for all the projects that we do, we do ensure that we keep the code checked in and any changes are updated so that we can always be on the same, we’re always on the same code. So that’s you know source control is important. But I think there’s scope there for better use of that resource in terms of …the core ideas, the core technical ideas of a concept, ensuring that those are transmitted or the information is there for a person to go and find out more and I think that’s probably, I’d see that as the primary challenge of the way that these sorts of things typically work. Is usually one person who’s done the research, the initial research, has that idea in their head and the capacity for that to be transmitted to others, sometimes it can be a tricky process for them to actually really understand what did he actually do to make this work? How did that happen? So ….yeah I …I think one of the things that I did do and very often what will happen is that the research will happen in a stage process. So we might acquire some data and then prior to writing formal source code for our application we would look at, well I know I would use a (???) for example and actually I’d begin to do some scripts and writing some simulations and trials, some algorithms with the data to see what would work. In the process of doing that you usually develop a handful of different scripts and other little routines that you can use to test the data. And you produce a lot of plots and information stuff like that. Just the PMO itself I’d say really it doesn’t really do it at all in terms of the identifying, even re-identifying sort of stage of the knowledge as I said there’s no formal connection between that captured knowledge base that we have and the actual PMO proper. Very much there’s a reliance of getting the right people on the project to start with and then the assumption is that those people have the knowledge and that they will do the right thing Do you believe that the project’s knowledge was properly transferred? R: Yeah sure okay. I would say the primary knowledge transfer formal knowledge transfer system that we use would be things like publications, papers and that sort of thing with the intention to publish those ideas or to put them into a form where they can be captured within the organisation. So there will be, in terms of the things that are here, and I guess that would come down to communities of practice and also looking here, information or knowledge repositories we have an e-publish system an online system where all…and that’s not just scientific publications but project reports, proposals you know even you know within reason even sort of project interim reports or memos, things like that are all captured within the published system now. So that’s
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been oh that’s been 2 or 3 years now that that’s been across the whole organisation and that’s probably raised the level of rigor in terms of knowledge management. Simply because now in order to get something submitted to e-publisher it has to go through a formal review process. So somebody will, you have to nominate people to review it. They will read it, they have to say they understood what you’ve done and then it can be accepted for publication or release. So that umm that process is probably a powerful way of doing that. In terms of the internet and things like that there certainly are as I said project, internal internet facilities or intranet facilities that we’ll use. Not on this project but on another one this other larger project that I was mentioning before we did establish and external or it was a wiki site if you like. Or a confluence site again which is a form of wiki but it was open to the external partners in the project as well so it became a repository for storing information. So on that we all, we were working on a large project with Rio Tinto and they …we opened up this website to their people as well so that we could store information, they could read it, and we could share documentation and discuss ideas. That became a tool for transferring the day to day knowledge of the project as well as the more formal reports and things like that. In terms of the core research knowledge and technical stuff that’s …it’s quite strictly mandated that that kind of stuff stays within the organisation and it’s only via the formal procedures of publication or reports or things like that that we’re meant to be releasing that kind of information. Ultimately that knowledge is the product that we have so we… you know so the …they really…they’ve then as an organisation SCIENCO has become much more aware of that in recent times. So these sorts of procedures have been in place because of that. Also well we did have a group wiki for example a confluence site that we will use and we will put up, the intention is that you put up a little blurb about your project there. So I probably should have mentioned that previously but it’s kind of slipped my mind. Again probably because it’s more of a voluntary than a necessary mentoring, it’s not, a lot of these things probably suffer from the point of view that they’re not mandatory. Or if they’re mandatory they’re mandatory but there’s no penalty if you don’t…,laughter….so umm the difficulty is that people aren’t actually held to that and I guess not from the point of view of being forced to do it but I think people need to be motivated to see the value in it. And I think often times there isn’t sufficient recognition of the value. Except again when it’s a question of transferring knowledge from that more basic research and development work you know the fundamental research, transferring that knowledge into a more formal project domain. People usually are pretty good about doing that like they’ll develop a case for that. They’ll… because again that, at that fundamental research level there’s always the intention of showing you what’s this about? What’s it for? So I the organisation I do think is actually very good, probably in some ways excellent in trying to identify from that fundamental point of view the knowledge that can be taken from a fundamental technology and applied into a domain. The …so like that information flows into the project domain from that area but within the project domain keeping that going as it were you know keeping, feeding that information back as projects have performed and more lessons are learned I think there is a bit of a, that’s where I think the main gap is. Is in you know organising that information in such a way that it continues to allow further
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improvement. So…
Do you believe that there were some facilities to help you for reusing existing knowledge?
R: Okay so certainly for the project I’ve been discussing here yes absolutely. As I said the its genesis was in a previous project which was a research, a more research oriented project I suppose with less of a commercial outcome. It was still working with the external client because we needed someone to work with to get the data but its goal was a much more research oriented goal. So the primary, well I guess the knowledge was transferred in two ways. One that project and its results which were published as results and knowledge that became the motivation for the client to request a further project. So that was used in order to actually generate the following project. But more obviously the technical knowledge that was gained in that project and the algorithms used for the detection and all that kind of thing that was used and transferred to the new project. Now as I say in some ways it was a, there was an element of it being a fairly informal process initially because I was the person who had done the original work and I commenced the process of re-implementing those concepts. However when it came time to transfer that knowledge within the project to other engineers and software engineers that’s where, as I said, the some of the typical approaches that we have used which is to provide resource code, talk through it and let the person start to work on their own version, as I said I think there’s a bit of a deficiency in that method because reading somebody else’s source code doesn’t give you the umm it doesn’t provide an adequate explanation of the ideas. You know the intangible aspect of the research knowledge. And so as I said the process of using a more formal transfer mechanism so that knowledge can be reused properly I think is important. And probably there’s scope for an internal publication if you like which has much more technical detail which could be a summary of the project mechanisms, algorithms and things which could be passed onto the person and allow them to do that. Now in the end I did produce documentation of that sort but it wasn’t produced at the outset as part of the transfer. It came about because of the need to use the knowledge. I sat down and worked together with this person and we gradually developed the information that they needed to do the job. So… I: do you think your existing PSO had a kind of contribution for the knowledge you’re using? R: Yeah I ….probably in that area, I think that’s, that I guess what I’d call the core technical research knowledge it’s probably, there’s a bit of a deficiency in the project support culture or mechanism at the moment. There’s certainly I think as I said, I think there’s an awareness of it that we you know we haven’t done as good a job as we could transferring that kind of knowledge from one project to another. And as I say I think this comes about because we do typically think of the knowledge as being something that we use to generate publications. And as I said I think that’s a very good mechanism but it’s probably the fact that when you produce a publication for external consumption you hold back some of the core knowledge. You don’t want to show everybody in the world exactly how you did it. You want to just tell them we did this and then we got these results. But what you’re holding back is the very knowledge that
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other people within your organisation will need if they’re going to work on that and continue to develop that process, the product. So there needs to be, between the level of the publication and just the raw source code which is difficult to work through if it’s not your own, in between that there needs to be this kind of intermediate level where the ideas are transferred in a more formal manner. And as I said, typically in my experience anyway that has tended to be more informally done. We do produce things like software specifications for example but in my experience you know the very, very formal software specifications that are often produced are such, there’s such an amount of work and effort that goes into them that they’re very well suited to big, big projects. You know where you have maybe at least a dozen programmers or more and several years of time and obviously your first step is to develop the specification so everybody knows what they’re doing. But this particular project I’m talking about had a short time span, really only one or two people working on it and you simply couldn’t afford the investment of time required to produce a really formal, exhaustive specification. You’d spend your whole budget before you even started to do the job. So yeah so I think there’s a deficiency in there in terms of transferring some of those ideas. You know in the end we did manage to do that but I think it was done in a somewhat informal fashion as compared to that. And yeah so it could have been better. Okay. Umm….yeah. Well it’s umm …the I suppose within an organisational sense there is the intention at the level above the project leader, the stream leader level as it’s called and higher again, the intention should be that these umm leaders should be able to identify knowledge outcomes from particular projects and provide that or utilise that, their kind of Meta knowledge if you like of that knowledge they should use that information to assist project leaders in other projects and say well I’m aware that we have had projects in this domain or that domain and you should talk to so and so about that project. But that’s a…so the intention there was in our organisational structure to do that but you can see that even in our (?) views that it’s not a formal linkage. It’s something the leadership structure will do and then the intention is go and find out from this person how that worked or whatever. So there’s no systemic method for doing that. I mean I’m probably, I don’t want to paint it too black because I think that can work quite well and sometimes knowledge, the sorts of knowledge that we deal with can be sufficiently complex that it’s difficult to summarise and that you might need to you know have a direct interview with the expert in this area and find out and ask questions and flesh things out. So I think that’s important. But there’s not a mechanism whereby you can kind of check that you haven’t missed something. And that’s the key thing you could, if something is overlooked well it’s overlooked and nobody will…if somebody forgets to talk to the guy down the hallway who knows about this or that well that’s just too bad. So if it’s remembered then great you know everything will be fine, so that’s probably where it breaks down. I: Right so what, do you think at this stage you have some sort of system for the knowledge management in terms of IT, forms, process, instruction, IT system or so forth? R: Yeah further….so there are some forms that have been developed. So I mentioned the post project review form which the intention, part of the intention of that form is
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to identify aspects of you know knowledge creation from the project and to identify how that can be sort of captured and organised. Well captured anyway I don’t know if it’s been formally organised. So there are forms and I suppose the post project review would be a process but as I say it’s not one that’s actually usually carried out. You know it you know it usually is a look so that’s an issue. In terms of other processes I mean we do have you know umm certainly at the outset of you know the financial year for example, if there are strategic projects being developed there’s certainly an effort made to examine you know the knowledge domain and to try and look at what projects have been done. So there would, in terms of processes I think it’s probably fairly heavily reliant on meetings, reports or workshops from time to time. You know we might have a workshop where we discuss applications of technologies in certain areas. But there’s no sort of online register or system you can go to in order to access that information. It’s umm you know it’s sort of word of mouth type thing yeah.
Please recall one of the projects which was less successful or failed, Do you
believe that proper knowledge management would contribute to success of project?
R: Okay so let me think of a project that would be considered unsuccessful…umm….let me think. Well I guess there are levels and levels. Like in terms of projects that haven't gone on, like they may have achieved some sort of a goal but they haven’t developed into further work. I can think of a couple of projects where they kind of came to a standstill at, you know at the end of their time. And so I guess from that point of view you wouldn’t call them highly successful. So in a particular case that I’m thinking of, we developed a technology system implemented for a particular at a mine site, a particular customer. And in the end it didn’t really go any further than that. They used the system on site but the…but it didn’t…actually would knowledge management or better knowledge management have helped? Well let me think. Yes in some ways yes because umm part of the problem was the use of the system was that would be knowledge management across the entire project chain, was that within the internal structures of the client company the person that they had designated to do the job didn’t have very much authority within the company. So that he was given the task of arranging to work with SCIENCO to develop this technology but he didn’t have the kind of authority to communicate the project as an important aspect of what was going on in the company. So as far as the client was concerned it was a kind of some little project running on the side and the majority of people within the client company probably didn’t really care about it or know much about it. And so there was one failure there immediately of the knowledge management which would be the goals of the system and what it was doing for them were not well communicated to the customer. Or at least they were well communicated to our immediate contact but not well communicated within the wider organisation. That probably came about partly because it was a two-step process. There was an independent consultant who had contacted SCIENCO and said oh well this might have this particular problem. And then he, through him we arranged a contact within the company but the knowledge part if you like went between, went through this sort of two stage process and even then when it got to the company the person that was the recipient of the knowledge
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probably didn’t have the capacity or the authority to really promote the knowledge within the company. So from a knowledge management point of view I’d say yes there was certainly some deficiencies there and from SCIENCO’s point of view it’s probably, this was a few years ago, and we probably wouldn’t work that way now anyway. But from SCIENCO’s point of view it would have been important for us to establish a better formal and direct relationship with the customer so that we had clear lines of authority within the organisation that we would report to. And as it was we didn’t have that and therefore the project was hampered from day one by that kind of thing. Secondly the information that we then produced for the client or that we produced you know specifications and some detailed information about the system, the client didn’t give us any clear concept of how they wanted the knowledge presented. So the fellow who was in charge of the project there you know very informally said oh you know look we just want to know how it works. Just maybe something here and could you give us a bit of a report on what happens. But it was very, very vague and you know we more or less had to go through the process of saying is this what you would like? Do you want this? Do you want that? Now that meant that I wasn’t confident at the end of the project that they really had a clear grasp of what it was that they were using and for that reason I think that you know it was not at all unlikely that they were going to…well I’m not surprised that it didn’t go any further because I think that the fellow who was in charge of that project there, he got moved to another section, somebody else came in to that area and because there was no clear transfer of the knowledge this other person didn’t have any particular interest in the technology. It all kind of just fell in a heap you know. I mean…the project was not financially unsuccessful I mean we….we made you know we made a profit out of it if you like or whatever but it’s not the sort of thing that we want to do. Like we’re not really interested in just doing little engineering projects that go nowhere. We really are interested in sort of you know actual research and development that creates improvements in the mining process so it was, whilst it wasn’t a disaster or anything like that it was a wasted effort I think in some ways because… So you know from that point of view and I think there it was that you know if you want to point to a deficiency in knowledge it was the transfer of understanding of the idea and why it mattered. Which is ironic because in this case it was a case where they, the company had approached the consultant and said that we’ve got this problem. The consultant approached us and said they’ve got a problem can we solve it? But then you know internally they didn’t seem to value the solution or didn’t seem to, you know they just passed it on to this fellow. So even though they were the ones looking for the solution they didn’t really umm you know they didn’t really kind of structure or manage very well the way that they dealt with it. So that’s yeah that’s a good example I suppose. Anything missed R: I’d say just to reiterate that one key area, the nature of the knowledge creation process in a research and development organisation is non-linear. You know it’s a umm you know ideas will come to people, there’ll be…so the process is a little bit mysterious almost how that happens, how that knowledge is being created. And it’s not something that you can pre-plan exactly how that will happen certainly in the
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context of the project work that we do. We often find out a lot the first time we are doing it and by contrast with my previous career which was in more industrial engineering sort of environment where you’ve got a known problem and you knew that you could apply knowledge to that problem and it would solve the problem and that meant you could pretty well guarantee you’re going to need these tools and this amount of time and we will make that work. In contrast to that in this sort of environment the knowledge development process is not always quite so clear. So you can be a knowledge management system for example could inform the project leader about options or possibilities or prior knowledge but there’s probably no way of completely capturing that kind of intangible element of the research. So umm I guess from that point of view I can see how …well it’s just something a knowledge management system would have to be flexible enough to handle. Is that kind of reality. And as I said it’s one where in terms of the project management system in which I wish there was greater flexibility because very often the sorts of projects that we do, even though we specify in the contract or whatever that research is an inherently uncertain process and therefore things may change. Nevertheless we still tend to tie ourselves into the typical contracts that are familiar to other industries. Which typically have very fixed timeframes, budgets, deadlines and milestones and there’s a lot of effort that has to be gone through in order to vary those parameters once the thing is laid down. And so that’s probably a frustration for a project leader well for me it’s personally a frustration as a project leader in a research and development environment that on one hand there’s a recognition of that aspect of research in terms of the organisation but there’s not a recognition in terms of the systems. The systems don’t allow for the flexibility as a… sometimes you just aren’t going to get the answer you want straight away. You might have to do something again several times and that might take longer than what you’d originally planned to do. So how that, how the integration of that kind of knowledge management can happen in that context of you know the project management system, that’s a tricky question. That’s not immediately you know it’s not immediately obvious to me how you could capture all the data and certainly there has to be, the system has to have a certain amount of flexibility built into it to do.