Unearthing and Enhancing Intelligence

and Wisdom Within the COBIT 5

Governance of Information Model By Ahmet Efe, Ph.D., CISA, COBIT 5 Foundation

COBIT Focus | 18 April 2016

Data, information, knowledge and wisdom (DIKW) are the best known, sequential, theoretical and conceptual

stations of understanding of things for taking proper action to save more in assets while losing less in resources in

the course of life, both for individuals and legal entities. They are also the most difficult issues that can be

differentiated within a certain context by practitioners without studying and referring to pertinent academic

researches. Even in the COBIT®

5 framework, it is not easy to distinguish these items.

Despite the fact that the Data Management Body of Knowledge (DMBOK) focuses on data, COBIT 5 seems to focus

more on the information layer, rather than data and knowledge, by emphasizing the transition of data into

information on the road linking to knowledge. Though information is emphasized as one of the 7 enablers of COBIT

5, knowledge management is considered under the Build, Acquire and Implement (BAI) domain as BAI08 Manage

knowledge, a management process. It is possible to argue that the challenges of big data that raise the importance

of converting an overwhelmingly huge, sophisticated, doubtful, changeable and intertwined volume of numbers,

signs and semiotic reflections into meaningful context. This seems to be very reasonable for the purpose of filling

gaps at the diverging paths between data management and knowledge management.

Furthermore, COBIT 5 has added a new paradigm of governance of information on the transition of data through

the knowledge creation path. However, it seems to be missing or undervaluing the intelligence and wisdom path,

which should follow consecutively after knowledge. This article puts those concepts under conceptual, theoretical

and logical scrutiny in order to add value to the common body of knowledge for prospective COBIT releases in the

future.

This study is a pioneering one that handles the COBIT 5 Information enabler with a critical approach using arduous

epistemological thinking of information theory, and considers the possibility that there may be some points left

ambiguous, superfluous or incomplete. In this study, along with discussions on intelligence and wisdom under the

context boundaries of COBIT 5 enabling information, there are also some issues such as data and data governance;

information governance and management; information goals/quality criteria; information attributes; DIKW; and

divine wisdom, wisdom of the crowd, and knowledge manufacturing concepts that are briefly discussed in order to

obtain a better understanding of the problem to contribute to the evolving common body of knowledge of COBIT 5.

DISCUSS THIS ARTICLE

Definition of DIKW DIKW has its place within the management information system (MIS) discipline and the common body of knowledge

management domain. In order to better understand DIKW in the context of COBIT 5, it seems wise to look at the

concept of risk and its conformity related to risk optimization—one of the COBIT 5 governance goals. There are

numerous definitions of governance and management of the risk concept included in COBIT 5 as a governance goal

and also as processes to be optimized. COBIT 5 has integrated the once-separate Risk IT framework with the latest

developments including ISO/IEC 31000 into governance goals, governance process optimization and management

processes. If the risk concept is to reflect the available DIKW, i.e., the various elements of the well-known DIKW

hierarchy, then it will be possible to trace relative attributes and criteria that can be various in theory.

In one study,1 a structure (conceptual framework) is presented for linking some common risk perspectives and the

DIKW elements. The structure is based on the following main ideas:

Data—The input for the risk assessment

Information—The risk description and definition.

Knowledge (for the decision maker)—Understanding the risk description and its impact on organizational goals

and objectives.

Knowledge (for analysts)—Understanding how to do the risk assessment and understanding the risk

description in order to set the best control activities to manage risk.

Wisdom (for the decision maker)—The ability to use the results of the analysis in the right way.

Wisdom (for analysts)—The ability to present the results of the analysis in the right way.2

Better understanding of the link between the risk concept and the DIKW elements is vital for COBIT 5 to strengthen

the foundations of the meaning and characterization of risk and, in this way, provide a basis for improved risk

management and governance of risk optimization.

Data and Data Governance Data can be defined as things that are, or represent, facts. Every thing or action continuously produces new data in

time. This data can be in many forms (e.g., text, numbers, graphics, sound, signs, video). Information is data in

context. Especially due to the pervasive use of IT infrastructure, tools, software, hardware and gadgets, data have

become more complex, intermingled, huge, insecure, ever changing and reproductive. Data in context means

providing a meaning to the data, defining the format in which the data are presented and describing the relevance

of the data within a certain usage context. Therefore completeness, integrity, accuracy, accessibility, availability and

reliability become the central locus of data management. Moreover, converting data into information becomes one

of the most important issues over time.

DMBOK, which is a main reference of COBIT®

5: Enabling Information, defines data management as “the planning

and execution of policies, practices and projects that acquire, control, protect, deliver and enhance the value of data

and information assets.” Both definitions are aligned, although the COBIT 5 definition emphasizes that management

has to align with the direction set by the governance body.3

As depicted in figure 1, DMBOK data governance consists of strategy, organization and roles, policies and

standards, projects and services, issues, and valuation that require an integrated management life cycle of data

architecture, data quality, metadata, document and content, data warehousing, reference and master data, data

security, database operations, and data development.

Figure 1—Data Governance

Source: ISACA, COBIT®

5: Enabling Information, USA, 2013

Information Governance and Information Management The terms “data governance and management,” “information governance and management,” and “knowledge

governance and management” are very often used interchangeably or are used to describe very similar activities by

practitioners. However, there are huge differences in their meaning.

Based on the definitions from the COBIT 5 and DMBOK frameworks, information governance and management can

be described as follows.

Information governance ensures that:

Stakeholder needs, conditions and options are evaluated to determine balanced, agreed-upon enterprise

objectives, which are to be achieved through the acquisition and management of information resources

Direction is set for information management capabilities through prioritization and decision making

Performance and compliance of information resources are monitored against agreed-upon direction and

objectives

Information governance activities include:

Communicating information strategies, policies, standards, architecture and metrics

Tracking and enforcing regulatory compliance and conformance to information policies, standards, architecture

and procedures

Sponsoring, tracking and overseeing the delivery and operational execution of information management

programs

Providing an understanding, based on stakeholder needs, of the decisions and priorities associated with

information resources

Based on the previous descriptions and staying aligned with the overall COBIT 5 definition of management,

information management can be described as follows:

Information management plans, builds, runs and monitors the practices, projects and capabilities that acquire,

control, protect, deliver and enhance the value of data and information assets, in alignment with the direction

set by the data and information governance body.

Some information, such as management reports and business intelligence information are important enablers for

the governance and management of the enterprise.4 COBIT 5 says that information management is encountered as

one or more specific areas of practice in many organizations, with various names, such as data architecture, data

management, data administration, database administration, data warehousing, data/information governance,

business intelligence (BI) and analytics, information architecture, information resource management, enterprise

architecture, enterprise content management, and/or records management.5

Information Goals/Quality Criteria One of the biggest contributions of COBIT 5 to the domain of information governance and management is forward

information goals, which are quality criteria based on development and revisions of former versions of COBIT

information criteria. This innovative development is neither philosophical nor theoretical, but rather a technical

aspect of intrinsic, contextual and security/accessibility information goals/criteria that can be applied to all enablers

by practitioners who need reasonable and applicable paradigm and contextual definitions.

Figure 2—Definitions of Sub-branches of Information Quality Criteria

Source: ISACA, COBIT

® 5: Enabling Information, USA, 2013

Information Attributes Another vital contribution of COBIT 5 to the domain of information governance and management is that it sets 7

information attributes, differentiated from information criteria. Information attributes cascade into the theoretical

and philosophical domains of information rather than the technical domain of information criteria, which can be

applied to any information that can stem from any of the physical, empirical, syntactical, semantic, pragmatic and

social world layers of information attributes.

However, it is possible to argue that there can be another layer for the source of information such as an ontological

layer, from which information is yielded. As part of this layer, intuition, conscience culture, scruples and beliefs can

be counted. Without understanding the source of information, the requirements of intelligence and wisdom cannot

be achieved.

Figure 3—Definitions of Information Attributes and Layers

Source: ISACA, COBIT

® 5: Enabling Information, USA, 2013

Knowledge Management Though information is emphasized as one of the 7 enablers of COBIT 5, knowledge management is considered

under the BAI domain as a management process, BAI08 Manage knowledge. ITIL V3 2011 Service Transition, 4.7

Knowledge Management is the main reference of this process. This process is described as:

Maintaining the availability of relevant, current, validated and reliable knowledge to support all process activities

and to facilitate decision making

Planning for the identification, gathering, organizing, maintaining, use and retirement of knowledge

The purpose statement of this process is “to provide the knowledge required to support all staff in their work

activities and for informed decision making and enhanced productivity.”6

There are 5 process practices of manage knowledge as shown in figure 4.

Figure 4—Knowledge Management Process of COBIT 5

Source: A. Efe. Reprinted with permission.

Intelligence Between Knowledge and Wisdom The DIKW hierarchy is the model used for the discussion of data, information, knowledge, wisdom and their

interrelationships. However, one study argued that the definition of data, information and knowledge are trapped

in a logical fallacy known as the circular definition.7 It is said that there is some agreement in the definition without

the fallacy. The missing intelligence in DIKW plays a major role between knowledge and wisdom. This gives rise to a

revised DIKW model called data-information-knowledge-intelligence-wisdom (DIKIW) (figure 5).8

Figure 5—DIKIW

Source: A. Lau. Reprinted with permission.

Intelligence requires ability to sense the environment, to make decisions and to control action. Higher levels of

intelligence may include the ability to recognize objects and events, to present knowledge in a world model, and to

reason about the plan for the future. In essence, intelligence is thought or mental processing capacities including:

Learning—Pattern recognition, memorizing, recalling, correcting mistakes, sense making

Conceptualizing—Modelling, prioritizing, categorizing

Analytical thinking—Analysing, interpreting, understanding, scenario playing, evaluating

Critical thinking—Logic, reasoning

Creative thinking—Imaging, imagining, supposing, hypothesizing, simulating

Quick thinking—Processing time

Performing—Reading, speaking, music, physical activities

Problem solving, decision making, judging

Affective thinking—Emotion handling9

Therefore, if applied to the COBIT 5 structure, intelligence becomes the fusion of business and IT goals,

effectiveness in achieving goals, agility, and competency in execution of the governance and management

processes.

There are 6 different wisdom dimensions that should be considered:

1. Reasoning ability—The unique ability to look at a problem or situation and solve it, good problem solving

abilities, a logical mind

2. Sagacity—Considers advices, understands people through dealing with a variety of people, feels he/she can

always learn from other people, is fair

3. Learning from ideas and environments—Attaches importance to ideas, looks at different perspectives, learns

from other people’s mistakes

4. Judgment—Acts within own physical and intellectual limitations, sensible, has good judgment at all times,

thinks before acting or making decisions

5. Expeditious use of information—Is experienced; seeks out information, especially details; learns and

remembers and gains information from past mistakes or successes

6. Perspicacity—Offers solutions that are on the side of right and truth, able to see through things reading

between the lines, the ability to understand and interpret his or her environment10

Wisdom is described as:

Understanding of universal truth

Sound judgment

Appropriate execution11

In this sense, wisdom can find its place in COBIT 5 from the following:

Goals cascade—Understanding ontological environment and ecosystem that effect stakeholder needs;

competency to convert stakeholder needs into corporate objectives, IT-related goals and enabler goals

respectively and skilfully.

Proper direction—Proper steering and redirection for effectiveness in achieving governance goals.

Running processes—A holistic approach to 7 enablers and 5 governance and 32 management processes with

inputs/outputs equilibrium covering the enterprise end-to-end.

Wisdom and Its Manufacturing Wisdom, arguably, has been sought after by many (if not all) throughout time.

12 Nevertheless, practical wisdom with

its multifaceted elements provides a plausible goal for all individuals and organizations that seek a brighter future

and the greater good. An organization cannot survive in the future with solely mechanistic and materialistic

approaches and without a clear, environmentally friendly, humanistic vision and a practical wisdom that empowers

people by taking all their concerns into consideration. For achieving results of wisdom for both organizations and

internal and external stakeholders of organizations, there is a need for well-defined enterprise wisdom, defined

according to the environment they are operating in and realities they are bound to recognize. The more

organizations take universal wisdom into consideration of governance goals the better vision and mission

accomplished in the future.

In some studies, it is argued that a philosophical understanding of human nature and the human good—attained

and enjoyed through the cultivation and exercise of theoretical wisdom—is especially conducive to one's full

development and exercise of the practical virtues, i.e., practical wisdom and the ethical virtues.13

Practical wisdom aids the practical problem solving of business, human and social issues. Presuming that practical

wisdom can be cultivated in individuals systematically and developed in organizations collectively, practical wisdom

would offer nontrivial contributions to society as a whole. Therefore, wisdom may well be the greatest goal as well

as the journey of human development.14

A person cannot achieve happiness, tranquillity and confidence about upheavals of the future and wisdom cannot

be obtained without a link to the real needs of stakeholders. A person should be effectively and sustainably

motivated to work diligently for accomplishing governance goals. Therefore, the purpose of organizations and

governance goals of risk, resources and value optimization needs sustainability of wisdom of people sharing similar

interests. Governance goals can be achieved only when internal and external stakeholders have motivation in an

ever-changing innovative ecosystem.

As required by the COBIT 5 goals cascade model, every organization should seek requirements of its unique

ecosystem within which it is dealing and the environment from which it gets benefits and charge costs. Otherwise

institutional set up of an organizational system will not yield desired results that are expected to be in conformity

with the governance goals of risk optimization, resource optimization and value optimization.

In a study of the wisdom of the crowd, it is argued that the wisdom of the crowd advocates that decisions made

collectively by a diverse crowd could be better than those made by an elite group of experts. The wisdom of the

crowd puts preconditions on this to work correctly. These preconditions concern the diversity of the crowd, their

independence from each other, their decentralization, and the methods of aggregating their distributed knowledge

and forming collective decisions.15

Therefore, for providing effectiveness on reaching governance goals, the wisdom

of the crowd approach of wide participation from related stakeholders can be taken into consideration in the

decision-making processes. By making meeting stakeholder needs a basic principle of corporate governance and

developing stakeholder transparency both a governance goal and a separate governance process used in COBIT 5,

wisdom of the crowd then finds a central role within the framework.

Apart from wisdom of the crowd, another issue under wisdom creation is 3 virtues that can enhance decision-

making skills. The 3 core factors—human, environmental and knowledge—and their incorporation into an

understanding of wisdom are depicted in figure 6. Moral virtue, epistemic virtue and practical virtue are considered

the wisdom-related aspects.16

Figure 6—The Contribution of Wisdom and the 3 Virtues to Management Decision-making

Source: A. Efe. Reprinted with permission.

The role of the mutual interactions between humans, knowledge and the environment in encouraging or precluding

wise decisions can be examined from different perspectives and with different methodologies that may provide

other explanations of the contribution of wisdom in the managerial decision-making process. For practitioners, the

models point the way for both individuals and organizations to improve decision-making skills through the

systematic expansion of perspectives gained through consideration of moral virtues, epistemic virtues and practical

virtues.17

Both service and manufacturing enterprises are sociotechnical systems, which necessitate overall integration of the

technical aspects from IT devices in shop floor to enterprise resources planning vertically and from product order to

shipment horizontally, as well as the social aspects from human interactions and consumers’ intentions to internal

and external stakeholders’ needs, virtues and wishes.18

Moreover, there is growing stakeholder need in the use of

data, information, knowledge and wisdom in enterprise contexts in order to survive in competition, surpass rivals

and excel in the creation of innovative products that can be considered under the governance goal of the value

optimization concept of COBIT 5.

In one study, the most recently developed manufacturing models such as smart manufacturing (SM)/smart factory

(SF), cloud manufacturing (CM), and socialized enterprise (SE)/Enterprise 2.0 are analysed, and a wisdom

manufacturing (WM) vision is presented to aggregate SM, CM, SE and existing intelligent manufacturing (IM) that are

to complement one another.19

Conclusion Pathways toward the WM vision must be addressed in relationship to knowledge, intelligence, creativity/innovation,

learning, intelligence and wisdom, especially from DIKIW and semiotic perspectives, as well as from the web

evolution and IT pervasiveness in business processes. Things; computers and humans; ubiquitous, artificial and

collective intelligence, as well as explicit and tacit knowledge, are integrated as a whole in the WM. Therefore,

wisdom and realization toward the WM vision need to be investigated and integrated to the business model of

COBIT 5. By fleshing out the information criteria and information attribute model of COBIT 5, it is possible to make a

more constructive and significant contribution to the DIKIW domain.

COBIT 5 emphasizes the need for the use of knowledge through enablers and, principally, via running processes of

management properly with compliance of input/output settings. To meet such needs, WM is emerging with

advances in IT-based services and manufacturing, as well as intelligence that can begin with the goals cascade and

run with proper execution of processes. In the COBIT 5 context, intelligence can be defined as the organizational set

up of the goals cascade from stakeholder needs to enabler goals, and the capability of pertinent acting according to

how to reach the governance goals of value, risk and resource optimization in every unique business case of each

organization. Wisdom can be defined as:

Goals cascade—Understanding ontological environment and ecosystem that effect stakeholder needs;

competency to convert stakeholder needs into corporate objectives, IT related goals and enabler goals

respectively and skilfully.

Proper direction—Proper steering and redirection for effectiveness in achieving governance goals. Running processes—A holistic approach to 7 enablers and 5 governance and 32 management processes with

inputs/outputs equilibrium covering the enterprise end-to-end.

For the intelligence and wisdom approach to be embedded in COBIT 5, the principles also should be redefined. Into

the 5 main principles, another principle such as “Manufacturing United and Universal Wisdom of the Crowd” should

be added to the main principles. It is defined as:

All functions, departments, and internal and external stakeholders are united for the cause of enterprise

wisdom.

Wisdom of the universal order and environmental concerns provide the main elements of enterprise wisdom.

Governance goals are to be accomplished by inclusion of all persons by externalizing and socializing their tacit

knowledge.

Whoever has the desire and motivation to add value to enterprise governance goals is appreciated.

Lessons learned from past activities and errors made by the crowd are valuable assets for governance goals.

Ahmet Efe, Ph.D., CISA, COBIT 5 Foundation Is internal audit executive at Ankara Development Agency in Turkey. He has worked in various public bodies such as

the Turkish Ministry of Forestry and the Turkish National Agency as an inspector, auditor, chief procurement officer

and logistics coordinator. He has contributed to the Turkish translation of COBIT®

5 Implementation. He can be

reached at aefe@ankaraka.org.tr.

Endnotes 1 Aven, T; “A Conceptual Framework for Linking Risk and the Elements of the Data–Information–Knowledge–Wisdom (DIKW) Hierarchy,” Reliability

Engineering and System Safety, vol. 111, March 2013, p. 30-36 2 Ibid. 3 ISACA, COBIT® 5: Enabling Information, USA, 2013 4 ISACA, COBIT® 5, USA, 2012 5 Op cit, COBIT® 5: Enabling Information

6 ISACA, COBIT® 5: Enabling Processes, USA, 2012 7 Liew, A.; “DIKIW: Data, Information, Knowledge, Intelligence, Wisdom and their Interrelationships,” Business Management Dynamics, vol. 2, no. 10,

April 2013, p. 49-62 8 Ibid. 9 Ibid. 10 Ibid. 11 Ibid. 12 Ibid. 13 Walker, M. D; “Rehabilitating Theoretical Wisdom,” Journal of Moral Philosophy, vol. 10, iss. 6, 2013, 763-787 14 Op cit, Liew 15 Hosseini, M., J. Moore; M. Almaliki; A. Shahri; K. Phalp; R. Ali; “Wisdom of the Crowd Within Enterprises: Practices and Challenges,” Computer

Networks, vol. 90, October 2015, p. 121–132 16 Intezari, A.; “Management Wisdom in Perspective: Are You Virtuous Enough to Succeed in Volatile Times?,” Journal of Business Ethics, vol. 120,

issue 3, March 2014, p 393-404 17 Ibid. 18 Yaoa, X.; H. Jina; J. Zhanga; “Towards a Wisdom Manufacturing Vision,” International Journal of Computer Integrated Manufacturing, 2015, p. 1291-

1312 19 Ibid.