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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.


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
19Ibid.

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