INF5190 Concepts and Principles in Knowledge...

INF5190 Concepts and Principles in Knowledge Management

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UNIVERSITY OF OSLO Faculty of Mathematics and Natural Sciences INF5190 – Concepts and Principles in Knowledge Management Spring 2006 Applying Knowledge Management for Improving Software Lifecycle Processes in the Norwegian Tax Administration Written by: Petter Øgland Hani Murad Sturla Bakke Anne Berge Bjørnseth Delivered: 12.05.06


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Table of Contents 1 Introduction................................................................................................................. 3 2 Theory ......................................................................................................................... 4

2.1 Two types of knowledge..................................................................................... 4 2.2 Knowledge Management in an Actor-Network Theory perspective .................. 5 2.3 Knowledge Management in a Total Quality Management perspective.............. 6

2.3.1 Knowledge generation ................................................................................ 7 2.3.2 Knowledge codification .............................................................................. 8 2.3.3 Knowledge transfer..................................................................................... 8

2.4 Organizational theory........................................................................................ 10 2.5 Cultural aspects................................................................................................. 11

3 Method ...................................................................................................................... 12 3.1 Interviews and observations.............................................................................. 12 3.2 Document analysis ............................................................................................ 12

4 Case description and analysis ................................................................................... 13 4.1 Organizational analysis..................................................................................... 13 4.2 The NTAX software lifecycle model................................................................ 14

4.2.1 Knowledge generation .............................................................................. 14 4.2.2 Knowledge codification ............................................................................ 15 4.2.3 Mechanisms of knowledge transfer .......................................................... 16

4.3 Main ANT-concepts in a KM perspective applied within the organisation ..... 16 4.3.1 Heterogeneity and negotiations................................................................. 16 4.3.2 Inscriptions................................................................................................ 16 4.3.3 Translation ................................................................................................ 16

5 Discussion................................................................................................................. 18 5.1 Two ways of understanding .............................................................................. 18 5.2 Knowledge about the current system................................................................ 18 5.3 Knowledge beyond the current system............................................................. 19

6 Conclusion ................................................................................................................ 21 References......................................................................................................................... 22


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1 Introduction The report is written as part of the assessment in INF5190 – “Concepts and Principles in Knowledge Management”. The project group has chosen to look at the software lifecycle for one of the major processes at the Norwegian Tax Administration (NTAX), namely the self-declaration process for private citizens. The report’s primary focus is to investigate to which extent the concepts of Knowledge Management (KM) can give insights on the software lifecycle model, and how such insights may be used for process improvement. In our understanding of KM, based on the INF5190 lectures and the course literature, we tend to see KM as partly an information technology induced management philosophy and partly a management philosophy drawing upon insights from total quality management (TQM). While process improvement seems to be one of the major drivers for installing Knowledge Management, we have, however, found little indication of there being a clear bridge between the specifics of quality management and knowledge management. Using an organization, such as NTAX, as a case for investigating how the practical aspects of KM and TQM relate thus seems to give context to important research questions from the perspective of information management, quality management and knowledge management. In the next chapter we will try to provide a perspective on KM within in the context of quality management and information infrastructure theory. The purpose of this exercise is to differentiate between two distinct views on knowledge that seems to be one of the core ideas of KM, namely tacit knowledge and explicit knowledge, although will argue for Kuhn’s way of differentiating between the two rather than the way of Nonaka. This sets a framework for empirical research, and in the third chapter we give a short description of the methods we have applied when researching NTAX. Results from the case analysis are then presented in chapter four. The results include an analysis of how the knowledge processes of knowledge generation, knowledge codification and knowledge transfer are implemented in the software lifecycle. We try to differentiate between two perspectives on knowledge by applying TQM and ANT separately. The fifth chapter contains a discussion of the case analysis, where our emphasis has been to use aspects of KM as a way of synthesizing parts of the case analysis that came either from a control perspective or a design perspective. The type of problems one tries to solve puts an constraint on what will be a natural and efficient epistemology. However, as KM aims at handling all aspects of knowledge, both social knowledge and technical knowledge, we try to use this framework for giving a more holistic view on process improvement within the software lifecycles at NTAX. We chose to conclude the report by commenting on whether we felt the approach gave an added perspective on process improvement, and also give some recommendations for further process improvement at NTAX.


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2 Theory Our intent with this chapter is to describe knowledge management within a wider philosophical context that includes a perspective on technical and social knowledge representing two distinct types of knowledge, suited for solving two different types of problems. We continue by elaborating on what we see to be the characteristics of knowledge management within each of these two domains, and then conclude the theory chapter with one section on organizational aspects and one section on cultural aspects.

2.1 Two types of knowledge Kuhn (1962) argues that scientific knowledge evolves in two directions. The normal way of accumulating knowledge is by solving puzzles according to rules defined by the current paradigm of doing science within a given discipline. Every now and then, however, this paradigm may be challenged, and new ways of understanding the world may evolve. The way Kuhn describes the process of doing scientific research is strikingly similar to how Argyris and Schön (1978) suggests how to create organizational learning.

Figure 1 – Double loop learning (Argyris & Schön, 1978)

An organization may learn through the methods of quality management, i.e. identifying errors and opportunities for improvement, and work out ways to improve the system based on such insights, as would correspond to “single loop learning”. However, from time to time it may strike the organization that the whole system should have been designed in a completely different manner, so by challenging the current assumptions and beliefs, the variables governing the single loop learning may be adjusted. This external perspective on the system is referred to as “double loop learning”. Jashapara (2004: 135) suggests total quality management (TQM) and business process engineering (BPR) as a possible way for understanding or implementing double loop


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learning. In the appendix B of ISO 9004:2000, it is suggested that double loop learning should be a natural way of operating any ISO 9001:2000 certifiable quality management system, where the inner loop learning is handled by methods for creating continuous improvements (“kaizen”; Imai, 1986) while the outer loop is handled by “breakthrough management” (Juran, 1964). What seems to us to be not all that clearly stated in the quality management literature, and knowledge management literature, is the way the inner loop and outer loop of double loop learning seem to correspond to two different ways of understanding the world. In our understanding, the difference seems to correspond to the “two cultures” of natural science and social science (Snow, 1964), meaning that the two cultures deal with two different concepts of knowledge, corresponding to whether the purpose of the research is to predict and control nature or whether it is to “understand” a culture from an anthropological point of view, i.e. to understand the language of the tribe in terms of observing what they tend to do. Kuhn explains his gradual understanding of scientific discovery to start with the understanding of hermeneutics (Lee, 1991). A similar approach may be used for explaining Deming’s image of the organization as a learning system. In fact, Scherkenbach (1986: 35) uses a model similar to figure one to illustrate the Deming philosophy of organizational learning by illustrating process improvement within the current system as the inner loop feedback mechanism between supplier and producer, following the usual methods of statistical process control, while the outer loop feedback mechanism corresponds to consumer research. In this presentation we consequently try to distinguish between knowledge processes related to the social science of the outer loop, using Actor-Network Theory (Monteiro, 2000; Latour, 1987) as a possible framework, while applying the traditional methods of statistical quality control (Deming, 1992) for analyzing the knowledge processes within the inner loop.

2.2 Knowledge Management in an Actor-Network Theory perspective

Within the science and technology field it is of importance to be able to formulate and understand information, innovation and knowledge management processes, and hence ANT was created; in order to better understand not only what kind of knowledge that exists and gets distributed in an organization, but also how, and by that exploring how a knowledge network is created (Monteiro, 2000). ANT is, although it is called a theory, more of a material/knowledge-semiotic method that gives us a powerful linguistic tool to describe KM processes and relations. Rather than looking at knowledge as something that is contained by someone or something, it is possible or even feasible to recognize knowledge as a network, or network of contextualized data and information, and that this network may consist of both knowledgeable and may be not so knowledgeable humans, non-humans like i.e. information processing and storing kinds of software, a web of experience, an urge to tell


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and a yearning to know. In all, a suitable network for the creation and transformation of knowledge from tacit to explicit and back, in addition to tacit to tacit and explicit to explicit. In an environment of learning in multiple directions and contexts, we form networks of knowledge, where we teach and learn, show and tell, exchanging a mix of tacit and explicit knowledge in a both structured and unstructured manner, with all the influencing factors that are comprised of earlier experience, education, familiarity with the tools needed to understand and manage a task, relations to others and so on. We might say that the tools for facilitating KM to a certain extent resembles Information Infrastructures as it is described by Hanseth and Braa (2000) and Monteiro (2000) as open networks, linked to others networks indefinitely, and as such, not necessarily easy to control. It may help, though, to look at infrastructure as Dahlbom does, as a “regulating skeleton, providing framework and guidelines for the activity”, and even if the immaterial nature of knowledge makes it seemingly incompatible in relation to a physical infrastructure, the more important aspects of an infrastructure is in fact immaterial; agreements, standards and metrics. An important element in Information Infrastructures is the idea of gateways, which is a method for combining two, or more, initially incompatible actors (standards). In an ANT perspective this could be regarded as translation, and in KM as a tool for knowledge distribution. According to Dahlbom, the stable infrastructures of the information society would be its educational institutions, research organisations, legal systems, habits and so on, as a shared resource. (Dahlbom, 2000:217-220), and by sharing, knowledge is created and distributed.

2.3 Knowledge Management in a Total Quality Management perspective

Although the best definition of Total Quality Management (TQM), in a European context, may be the evaluation criteria for the annual quality awards (EFQM, 2006), when discussion the knowledge management principles underlying the ideas of quality management, we chose to focus on the ideas put forward by Shewhart and Deming. A good starting point for discussing KM within the context of TQM is perhaps by looking at the ISO 9000 model for designing quality management systems (figure 2). Although the figure appears to consists of a single loop, the system model can be thought of to consist of two loops or two types of logic as illustrated by the box indicating “measurements, analysis and improvement” having input from processes and products on one hand (single loop feedback) and input from customers on the other hand (double loop feedback). In fact, if we identify the customer box on the left hand side of the diagram with the customer box on the right hand side of the diagram, the structure would topologically be possible to be described as a torus, i.e. a topology of double loop learning that is identical to the Argyris model in figure one or the Kuhn model of how science evolves.


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Kunder Kunder

Tilfredshet

Krav

Ledelsens ansvar

Realisering avprodukt

Måling, analyseog forbedring

Ressursstyring

Produkt

Kontinuerlig forbedring av systemet for kvalitetsstyring

Verdiøkende aktiviteterInformasjonsstrøm

Figure 2 – The NS-ISO 9000:2000 quality management framework

As we have already presented Statistical Process Control (SPC) as a tool for knowledge management as a previous INF5190 presentation (Øgland, Bakke, Murad & Bjørnseth, 2006), in this presentation we will just summarize some of the main insights from the presentation.

2.3.1 Knowledge generation According to Davenport and Prusak (1998: 52), knowledge generation refers to: “…, the specific activities and initiatives firms undertake to increase their stock of corporate knowledge”. They characterize the importance of knowledge generation in this way: “…since it is axiomatic that a firm’s greatest asset is its knowledge, then the firm that fails to generate new knowledge will probably cease to exist.”(ibid.: 67). Acquisition of knowledge, as used by Davenport and Prusak (ibid), refers to the dimension of knowledge generation where the knowledge is acquired by the organizations as well as that developed within it. In chapter six of ISO 9001:2000 there are requirements related to people having sufficient competence for performing tasks, and that the competence shall be documented. The main process for generating knowledge with the ISO 9001:2000 model is by recording problems and areas for improvement. Although there are requirements all over the model aiding to define a consistent model that will make learning and improvement possible, the main issues are related to chapter eight in the ISO model where there focus is on applying (knowledge) metrics.


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2.3.2 Knowledge codification Knowledge codification involves codified material such as texts and computer systems that organize and contain knowledge of an organization. The purpose of knowledge codification is: “…to put organizational knowledge into a form that makes it accessible to those who need it” (Davenport and Prusak 1998: 68). Making a quality system in compliance with the ISO 9000 requirements and recommendations would be a typical example of a system for codifying, storing and managing knowledge for the purpose of improving organizational performance. As the focus of the system is on quality (conformance to standards), the process of codifications runs mostly through the processes of quality control. In order to perform quality control of processes and products, the standard way of doing this would be by identifying metrics for all critical aspects of the organization and use statistical process control (SPC) for monitoring whether the processes are stable and under control (Deming, 1992). In other words, codification starts by identifying what may go wrong or what we would like to improve, and then select metrics that are useful from this perspective. In chapter four of ISO 9001:2000 there are also requirements dealing with how to create a map to illustrate how the processes connect. This may be useful for understanding how processes are related when we want to understand the root causes for something going wrong or how to predict the effects of improving related processes. What seems to correspond the most directly with the concept of knowledge maps (or topic maps) in knowledge management, however, is the quality management idea of using Ishikawa fishbone diagrams for mapping out the ontology of how things can go wrong. The idea behind the Ishikawa fishbone diagram is that of indicating the five different “topics” that have proved useful for analyzing problems in industry; man, machine, materials, methods and metrics, catalogue problems as they occur (“occurrence”) and draw lines in order to make ontological “association”. In other words, the Ishikawa diagram, developed in the 1960s, should probably be seen as a prototype for what is now described as “topic maps”. The main difference between the Ishikawa diagrams and the more general topic maps, on the other hand, is that the Ishikawa diagrams relates to the ontology of problems and errors while general topic maps can be used for organizing explicit knowledge in general.

2.3.3 Knowledge transfer Davenport and Prusak (1998:101) state that knowledge transfer involves two actions; transmission and absorption. The goal of knowledge transfer is to improve an organization’s ability to work, so these two actions only provide value if they lead to change in behavior. However, as TQM in the context of ISO 9000 relates to the


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systematic aspects of knowledge transmission and absorption, we have added sections later in this theoretical section on organization theory and cultural theory. Nonaka (1995:19) provides a model with four different modes of knowledge conversion with the basis in the terms tacit and explicit knowledge as the two main types of human knowledge.

Table 3 – Nonaka’s model of knowledge conversion

As one of the fundamental ideas in “The Knowledge-Creating Company” (Nonaka & Tackeuchi, 1995) is to explain innovation and develop processes in Japanese companies as compared to those of the West, focusing on the “tacit” culture of the East, his framework seem suitable for explaining why Quality Circles has been and still is an important aspect in Japan while it only lasted as a short-term fad in the 1980s in the West. From the point of view of ISO 9001:2000, the idea is to have all management knowledge explicit in terms of probability distributions for making decisions, and by the process of doing so, knowledge can be codified as information to be transferred according to the traditional way of mathematical communication theory (Weaver & Shannon, 1949).


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Table 4 –Mathematical theory of communication (Weaver & Shannon, 1949)

The significance of going from knowledge management theory to information management theory when dealing with knowledge transfer of quality related issues is that quality management can be dealt with in objectivist ontology. By this approach, many of the problems of knowledge management are simplified to be problems of information management. Nevertheless, in order to deal with issues that can’t be explained by numbers, tables and graphs, we need additional theory, such as the organizational theory and the theory of cultures.

2.4 Organizational theory Mintzberg (1983) defines nine organizational design parameters, categorized in four main groups. We have found three of these useful for the purpose of understanding the aspects of knowledge management needs in the type of organization we are looking at. The groups are:

• Design of individual positions – the design parameters in this group covers job specializing, formalizing or work and training and indoctrination.

• Design of “super-structure” – this covers the grouping of and the size of each unit. • Design of communication between units covers fields like system for planning

and controlling, and also coordinating communication. • The group called “system of decisions” covers two parameters called horizontal

and vertical decentralization. This has to do with where, or at what level decisions are made. It is about power structures.

These four groups are then used for analyzing the what Mintzberg see as the five different configurations:

• Simple structure – suitable for a “one-man firm” and such. • Machine bureaucracy – typically for the industrial workplace (e.g. a factory). • Professional bureaucracy – organizations based on professional skills.


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• Organizations in divisions – an incompletely configuration but with clear terms on single fields, suitable for large and complex companies.

• Adhocracies – the innovative organization. In order to determine a configuration, many factors have to be considered, such as situational factors. Mintzberg split these factors into categories such as; age and size, technical system, environment and power. In our KM analysis, however, we only plan to use some of the most basic aspects of Mintzberg ideas.

2.5 Cultural aspects By identifying the structural configuration of a given company, one would perhaps expect that much of organization culture is also explained as one would expect culture to evolve and adapt to fit the structure. However, in a constantly globalizing society additional cultural factors may be taken into account for understanding knowledge flow and development. In particular, we would like to see how the organization culture manifests itself or evolves in order to meet the hetrogenity among “customer” (tax payers). Although globalization and hetrogenity may play a vital role in international business, for the processes we investigate within the tax administration, we do not expect it to play a vital part for understanding and improving the software lifecycle processes, but we would nevertheless like to add a perspective on the cultural issues as managing culture appears to be one of the most striking features of KM vis a vis TQM, e.g. through the emphasis on the interplay between tacit and explicit knowledge.


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3 Method Our approach for collecting knowledge and understanding NTAX has consisted of interviews, observations and document analysis.

3.1 Interviews and observations As one of the project members had been working as a quality manager within the IT function of NTAX and was still a part of the organization, we considered his knowledge from previous interviews and observations to be sufficient for the level of understanding that was needed for performing the analysis that was needed within the scope of the project. His previous interviews, observations and document controls had been following the framework of Action Research (Coghlan & Brannick, 2001), meaning that many of the interviews, observations and actions were done from the perspective of a change agent and thus biased in order to motivate organizational learning and improvement. During the course of the project, however, he interviewed the current IT quality manager and made some questions to the head of the IT department and the some of the people working in software development and IT security issues.

3.2 Document analysis Although there are some differences between how work is carried out within the IT function of NTAX and how the documents explain how work is supposed to be carried out, especially if we look at various plans, procedures and strategy documents, there are also documents identifying some of these differences in order to aid the organization in reducing the gaps. In our analysis, we have partly chosen to look at the organization from the ideal perspective of what it says it is doing and partly from our understanding of what is actually going on, i.e. by looking at quality management documents. We believe this dual perspective should correspond with our perspective on dual knowledge in section 2.1, i.e. how one type of knowledge deals with direction and narrative while another type of knowledge deals with decisions and control.


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4 Case description and analysis We start by giving a short description of NTAX from the organizational perspective, in order to identify two major substructures we call the professional bureaucracy and the machine bureaucracy, and thus motivating a more narrow inspection of the software lifecycle models that are within the machine bureaucracy although bordering on the professional bureaucracy.

4.1 Organizational analysis The diagram below gives a simplified description of how the Directorate of Taxes is organized (Skatteetaten, 2006; Wikipedia, 2006).

Figure 5 – Simplified organization chart for NTAX

Consistent with the Mintzberg models in chapter two, we chose to describe the tax administration to be a mixed configuration consisting of two different parts. The left hand side of the organizational chart represents the professional bureaucracy, mainly consisting of lawyers and other experts. The employers in this part of the organization don’t work here very long, so there is a challenge in transferring knowledge from one specialist to the next. On the other half of the organizational chart we have what we will characterize as the machine bureaucracy, with clear lines between the leaders and the workers, and no questions about there the powers of decision are. Here the matter of knowledge management is taken care of by interaction of various computer based systems. In the professional bureaucracy, expert knowledge is mostly tacit, and difficult or impossible to write down and put into procedures. Judgments and decisions made by specialists vary from case to case, and often the experts discuss among themselves how to interpret and handle difficult cases.

Directorate of Taxes Bjarne Hope

CEO

Declaration Department Collection Department Administration Department IT Department

Internal Audit

Machine bureaucracy Professional bureaucracy


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In the machine bureaucracy, on the other hand, knowledge about administrative and technological tasks may be tacit, but could or should (Weber, 1979) be put into procedures and managed in a rational manner, like a machine. On the organizational chart we have also identified the internal audit. The purpose of the internal audit is to make independent investigations to sure that the quality management system is performing correctly, and that the organization is constantly improving. From the viewpoint of Knowledge Management, one could perhaps say that the internal audit at NTAX fulfills the role of the Knowledge Manager of the organization.

4.2 The NTAX software lifecycle model Although there are different lifecycle models for the various systems being created and maintained at NTAX, the generic picture as shown below.

Krav-spesifisering

I Startutvikling (V10.1)

ErfaringDrift/Vedlikehold

Implement-asjon

Spek.designLøsning

II. Godkjennkrav.spek (V10.2)

III. Godkjenndesign spek (V10.3)

IV. Godkjennsystem (V10.4-6; N7)

V. Godkjennendringer (V10.1)

Kravspek Kildekode

Testrapport

System-beskrivelse

Testplan

Løsnings-beskrivelse

Bruker-veiledning

Erfarings-rapport

Drifts-veiledning

Vedtatteendringer

Figure 6 – Generic NTAX software lifecycle model (Skattedirektoratet, 1998)

Using quality control and process monitoring the lifecycle for the self-declaration system as an example (Skattedirektoratet, 2005), we will now indicate how the main knowledge processes mentioned in chapter two integrate with the software improvement process.

4.2.1 Knowledge generation In the case of hiring or renting software people to work within the IT function, there are NTAX requirements related to education and experience. There are also procedures on how to introduce new people into the organization and a series of meetings newcomers have to attend. Much of the practical learning, however, is based on “learn by doing” as novice programmers are given simple tasks to perform and then gradually more and more advanced tasks. The whole top line of the lifecycle model in figure five can be seen as a knowledge production process. Development starts by producing or updating the requirement


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documents. Quality control and approval (stage II in figure five) is a way of collecting knowledge about the quality of the specifications. The requirements may come from the professional bureaucracy (system users), external requirements or technical requirements from the machine bureaucracy, and thus requires acceptance from a wide group of people. If accepted, the process moves on to stage III were the requirements are interpreted and used as input for system design. This is mostly a technical process, although it may require user input if parts of the design relates to the user interface. Quality control and acceptance is done by people within the machine bureaucracy. Going from stage III to stage IV means that design documents are handed over to programmers, who will interpret the designs, evolve software and perform tests. There are different levels of testing, and on the final levels, the system designers will also perform tests in order to verify that the software is consistent with the designs. By the end of stage IV, the system is completed and ready for production. All known problems are written down in test reports. The results from quality audit of the whole process up to this point will be summarized as an audit report, and management will be given all available knowledge related to how one expects the system to perform before the decision is made whether to go into production or not. By the end of production, we enter a stage V where all insights, problems, ideas and opportunities for improvement from the process is written down and made as input for a new cycle. This model illustrates, thus, that along with the update and production for a given system, there is also a knowledge management process related to information and management flow. This knowledge is reported back to the first stage of next year’s cycle, and thus we have a process of continuous improvement based on knowledge management.

4.2.2 Knowledge codification As illustrated in figure five, and also commented upon in the section above, the software development process is codified on the abstract level as a flowchart, and as we go deeper into the subprocesses associated with each stage of the development process, there are documents being produced and knowledge being codified into reports, numbers, tables and diagrams. As we interpret how the life cycle process functions, or is supposed to function, there is flow of practical knowledge following the flow of the life cycle model, but knowledge collected from the learning process is more easily understood to be codified through the quality control processes where deviations from the existing framework is written down in quality audits.


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As the cyclical project evaluation report also may contain an evaluation of the quality audits and general comments on how the life cycle model is working, there is also an element of double loop knowledge being codified into documents. Most of the codified knowledge about how the processes are supposed to work are available through the intranet. The documents being produced by the life cycle are stored electronically in an internal digital archive system called ELARK.

4.2.3 Mechanisms of knowledge transfer If we look at the feedback loop at the bottom of figure five, then this is the basic mechanism for knowledge transfer from the end of one cycle into the beginning of the next. Insights and experiences from the end of one cycle is used as specifications and starting point for the next cycle. A particularly important aspect of this transfer of knowledge is how management knowledge is iterated from one cycle to the other by use of statistical process control and other statistical techniques for predicting quality levels and quality improvements.

4.3 Main ANT-concepts in a KM perspective applied within the organisation

4.3.1 Heterogeneity and negotiations A central aspect of Actor-Network Theory is the concept of the heterogenous network, meaning that such a network consists of actors (and actants) that are physically different, working together, creating a solid network capable of facing eventual resistance that might rise against it, and doing so through successful negotiations leading to a state where knowledge is the product of heterogeneity in action, where all the the heterogenous elements, both physical artefacts and immaterial entities such as organisation, work and is fitted together (Law, 1992). Just as the bigger Actor-Networks such as the Internet [the mother of all Actor-Networks], or the state of societal order, is the result of negotiations among a heterogenous web of actors unifying in creating the network, so is the actor-network that operates at a workplace, in this case, NTAX.

4.3.2 Inscriptions Results might be regarded as a sort reciprocal inscription, in that members of the organization make efforts to accomplish certain goals. In that sense, a potential achievement will have an impact on how they perform their work. In order to be able to measure their efforts during the work process, standards, metrics and routines have to be established. Another inscription is that knowledge itself is built into these metrics, standards and routines

4.3.3 Translation In a process of going from tacit to explicit knowledge, unstructured explicit knowledge, or from coincidental to scientific thinking, the members of the organisation will have to re-interpret distributed knowledge in alignment with one's needs, which in turn translates into a more general need eventually leading to a unified solution (Hanseth and Monteiro,


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1998), all through the process of translation, which, in turn is based on a medium or standard into which it is inscribed (Callon, 1991), building the actual network unifying the actors, and which is done through the process of negotiation. At NTAX this could, as an example, typically be done through the language of statistics.


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5 Discussion We would now like to discuss the results from the case analysis through the perspectives and theoretical framework presented in chapter two. We chose to structure the discussion by first returning to the perspective of the two cultures and types of knowledge, then discuss the case with respect to the first type of knowledge (knowledge about the system) and finally discuss the case from the perspective of the second type of knowledge (knowledge that challenges the current system).

5.1 Two ways of understanding In this chapter we want to return to the idea about two epistemologies corresponding to the two cultural traditions of literary critique and natural science. As mentioned in chapter two, we see the idea behind literary critique and storytelling in general to be an aid for discussing meaning and direction, while the idea behind natural science being that of finding out what is true or not when the direction of research (“paradigm”) is given. While the distinction between the type of knowledge to be found within the traditions of literary critique and natural science may to a certain extent correspond to Nonaka’s distinction between tacit and explicit knowledge, as also pointed out by Kuhn (1962: 44), but we feel that the distinction between science and meta-science is missed in Nonaka’s argument. On the contrary, what seems to us to be a natural way of reading Nonaka is to think of tacit and explicit knowledge as two ways of representing same level knowledge, like the practice on riding a bike and a manual on how to ride a bike. The way the concepts are used by Kuhn would, it seems to us, be more like the science of riding a bike on one hand and the sociology (or history) of scientists studying how to ride a bike on the other hand. From out point of view, this distinction between science and the sociology of scientists seems to have an interesting parallel in production improvement and customer research. In public organizations, such as the Norwegian tax administration, the word “customer” may perhaps not be the most natural way of describing the tax payer, but in the terminology of ISO 9000:2000, the receiver of products (or services) from any process is named the “customer of the process”. However, before we comment on the analysis of NTAX by applying ANT to the “customers of the processes” for challenging the way things are presently being done, we start by commenting on the “normal science” of the system as it is.

5.2 Knowledge about the current system As we noticed from the section on knowledge management and total quality management, viewing knowledge management as a “normal science” (Kuhn, 1962) seem to give clear operational definitions for distinguishing between data, information and knowledge. To make the argument more explicit: Data, in the software lifecycle model, would correspond to any sort of fact or information being recorded by the ISO 9000 quality management system. Information would be data


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that can be attributed to some specific statistical distribution, describing the process. Knowledge would be the statistical distribution in itself (Øgland et al, 2006). In other words, as long as we work within the area of explicit knowledge, and apply the standard epistemology of quality management (Deming, 1992; Lewis, 1929), then the concepts of data, information and knowledge are all possible to define in an operational manner, using the SPC chart as a way of illustrating the principles. As all knowledge can be codified as statistical distributions, all the knowledge management processes can be handled as information management processes (Weaver & Shannon, 1949), and all other KM concepts seem to fit into the framework of viewing the organization as a machine. The language of systems thinking and artificial intelligence seems to be a natural way for describing, analysing and improving the organization. We will also argue that this could perhaps be the best way of approaching knowledge management in the public sector, as public sector organizations are supposed to be a part of the national and international infrastructure, and thus to function predictably as a machine. Even though Nonaka and Tageuchi (1995) point out that Cartesian dualism is less apparent in oriental philosophical traditions, Cartesian dualism being the basis for modernity and scientific thinking, this does not seem to indicate that the way of the machine bureaucracy would be a less natural way for the Japanese. On the contrary, as has been pointed out by Tsutsui (1998), some of the keys for understanding Japanese management seems to be work in better harmony with the ideas of Taylor and Ford than what has been the case in Europe and the US. What seems to make a difference, though, is the issue of consumer research. Understanding consumers from the perspective of designing, producing and marketing requires sociological, anthropolical and psychological knowledge, depending on the type of product and the type of consumer. Although mass production for mass audiences does not necessarily require as much sociological or anthrological insight as more specialized products or specialized consumer groups would require, the type of knowledge is different. In the case of process improvement of the software lifecycles at NTAX, we have looked at the people responsible for the software lifecycles from the perspective of ANT, in order to see whether this will create knowledge on how to improve the process improvement strategies.

5.3 Knowledge beyond the current system When Kuhn talks about scientific revolutions, he talks about collecting knowledge that indicate problems with the current way of thinking or knowledge saying that there may be a better way of thinking and solving problems, i.e. knowledge about different paradigms of doing science. In out NTAX analysis, we tried using ANT as a lens for understanding for this purpose, focusing on the ideas from ANT about inscriptions and translations. Among the various methods applied by NTAX management in order to control the behavior of the people working within the software life cycle system, we identified the metrics and statistics as


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important elements of the socio-technical infrastructure. Furthermore, through the ANT concept of translation we suggested a need for changing the culture into a culture more based on scientific thinking and less based on “rules of the thumb”. If we regard this in the context of the two cultures discussed in section 2.1, we notice that this corresponds to attempting to change the current paradigm of the organization, or, in other words, to stimulate double loop learning by challenging the mindless way of working by applying a more scientific way of working. In the context of section 2.5, were we mentioned the importance of considering the culture at large, by reducing communication barriers based on differences in cultural perceptions, we believe that an organization can enhance knowledge transfer and improve its own knowledge management system. By focusing more on metrics and statistical methods, we believe that NTAX can facilitate the transfer of tacit knowledge to explicit knowledge in its infrastructure, thus getting on step closer to achieving its objectives.


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6 Conclusion In this report we have been trying to answer the question as to whether knowledge management (KM) may give additional insights to process improvement, beyond the standard ways of process improvement (SPI) known through total quality management (TQM) and information systems (IS). We have then argued that there are indeed such insights, and that the main key for discovering these insights is through the perspective of discriminating between the epistemology of natural science and the epistemology of literature critique (“humanities”), what Kuhn would perhaps describe as the difference between positivism and hermeneutics. In order to argue the practical consequences of this epistemological dichotomy of these two perspectives, we have used knowledge management for the software lifecycles of the Norwegian Tax Administration (NTAX) as a case. The natural approach, from our point of view, has then been to use TQM as a typical positivist way of understanding the organization, and then Actor-Network Theory (ANT) as a way for gaining additional insights through a critical perspective on the current TQM system. In order to support the knowledge generation in the software lifecycle, we believe the cultivation and nurturing a knowledge-sharing culture and motivation of employees may be more efficiently achieved by applying internal metrics and deriving knowledge from these metrics through the use of methods of statistical quality control. Aligning the knowledge management strategy with the quality management strategy should form the the foundation for establishing and maintaining knowledge generation. When looking at the existing working environment related to the software lifecycles, it is obvious that socialization is the most used method for transferring knowledge within the organization, although most aspects of the methods are made explicit through documents in one way or another. The need for making everything explicit is consistent with the traditional needs of the bureaucracy, while the fact that most of the important knowledge is kept inside the heads of a few IT experts seems to be consistent with the psychology and sociology of information technology intensive environments. Because of this, the project group concludes that it is important to focus on integrating the current software lifecycle quality management system with the technical infrastructure, and thus making the knowledge processes more fully integrated into the logic of the bureaucracy. The technical infrastructure forms basis for the codification of knowledge, which is a central topic in the report. The project group discusses implementation and use of knowledge maps, in the style of Ishikawa fishbone diagrams and Pareto charts, for understanding how problems relate to each other and how to address the problems in a more systematic manner. The charts and diagrams should be available to all parts of the organization by making better use of the Intranet.


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Latour, B. (1987): “Science in Action”, Harvard University Press: Cambridge, Massachusettes. Law, J. (1992): “Notes on the Theory of the Actor-Network: Ordering, Strategy, and Heterogeneity”. Systems practice, 5/4, 379-393. Lee, A. (1991). “A Guide to Selected References on Hermeneutics”. Available: http://www.people.vcu.edu/~aslee/herm.htm [Accessed 11th of May 2006]. Lewis, C. I. (1929): “Mind and the World Order: Outline of a Theory of Knowledge”, Dover Publications: New York. Mintzberg, H. (1983): “Structures in Fives: Designing Effective Organizations” Prentice-Hall: Englewood Cliffs. Monteiro, E. (2000): “Actor-Network Theory and Information Infrastructure” in Ciborra, C. U. & Hanseth, O. (Eds.) From Control to Drift, Oxford University Press: Oxford. Nonaka, Ikujiro (1995): “Dynamic theory of Organizational Knowledge Creation” Organization Science , Vol.5, No. 1, pp 14-37 Nonaka, I. & Takeuchi, H. (1995): “The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation”, Oxford University Press: Oxford. Scherkenbach, W. W. (1986): “The Deming Route to Quality and Productivity: Road maps and roadblocks”, Quality Management Press: New York. Skattedirektoratet (1998): “Strategisk plan for bruk av IT i skatteetaten”, SKD nr 62/96, Oslo. Skattedirektoratet (2005): ”Stokastisk modell for forvaltningsløp PSA-2004 til støtte for håndtering av klarsignal”, SKD 2005-012, Oslo. Skatteetaten (2006) online at http://www.skatteetaten.no, download 09052006 Snow, C. P. (1964): ”The Two Cultures: A Second Look”, Cambridge University Press: Cambridge. Statskonsult (2002): “Organisering av IT-funksjonen i Skatteetaten”, 2002:13, Oslo. Tsutsui, W. M. (1998): “Manufacturing Ideology: Scientific Management in Twentieth-Century Japan”, Princeton University Press: Princeton. Wikipedia (2006) online at http://no.wikipedia.org/wiki/Skatteetaten, Downloaded 09052006


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