1 Drs. David and Alex Bennet are co-founders of the Mountain Quest Institute, a research and retreat center situated in the Allegheny Mountains of West Virginia.
Exploring Concepts, Interpretations and Meaning: Knowledge and Knowledge Management by Alex and David Bennet1 Explore. Experience. Expand. ABSTRACT: The authors use the results of a 2005 study where thought leaders across four continents were interviewed regarding their thoughts and feelings about knowledge and the field known as Knowledge Management to take a closer look at these concepts and what they may mean for the future. Specifically, diverse definitions of knowledge and knowledge management are presented, then the breadth of the field of Knowledge Management explored through the 14 learning objectives developed by the Knowledge Management Working Group of the U.S. Federal sector. Along the way, a grounded definition of information based on universal phenomena of ordered patterns is proposed, an operational definition of knowledge directly relating it to effective action is explicated, and the idea of the field of KM as a complex adaptive system is explored. This paper is based on original research, personal experience with the U.S. Federal sector, and a literature review.
Introduction In the field of Knowledge Management (KM), new thought leaders are continuously emerging both inside and outside of organizations. Each of these thought leaders offers new ideas—new frames of reference, new strategies, new approaches, new processes, new technologies—under the rubric of KM or a related label, and many of them have the passion and experience to successfully apply these new ideas in specific situations. This is one reason why the life cycle of KM (no matter what you call it) is continuously shifting, rising and falling with the tides of new thought and new situations. When the KM life cycle was explored in 2005 during interviews with 34 KM thought leaders covering four continents2, hereinafter referred to as the KMTL study, there was a wide variety of opinion on where KM was in its life cycle. Specifically, 33 percent placed KM at a very early point of evolution, 17 percent placed it somewhere in the middle in terms of the Gartner and Forrester models, 20 percent saw it as maturing and being integrated into the fabric of organizations, 20 percent saw a rebirth, a rediscovery around the world, and 10 percent thought it would always be around, it is just not going to go away. (See Figure.) Three years later it is clear that all of these ideas are right. Considering the breadth of ideas that are part of KM, some of them fit into each of those life cycle areas. This paper explores the concepts represented by the terms “knowledge” and “knowledge management” through the eyes of these 34 thought leaders, then adds the additional texturing of what recent findings in Neuroscience tell us about the workings of the brain to take another look
1
Drs. David and Alex Bennet are co-founders of the Mountain Quest Institute, a research and retreat center situated in the Allegheny Mountains of West Virginia. They co-authored Organizational Survival in the New World: The Intelligent Complex Adaptive System, a new theory of the firm that combines theory and practice to empower leaders, managers and professionals who must excel in the age of complexity. This material appeared in Effective Executive: The Icfai University Press, July 2008. 2
See the 2005 study, Exploring Aspects of Knowledge Management that Contribute to the Passion Expressed by KM Thought Leaders, for the names of participants. The full study is downloadable at www.mountainquestinstitute.com
Exploring Kn and KM
1
www.mountainquestinstitute.com
at how we might define knowledge in the future. Then we focus on the movement called KM3, exploring its meaning, interpretation and breadth. Defining Knowledge Throughout the centuries there have been multiple definitions and interpretations of knowledge, ranging from the Platonian concept of knowledge as justified true belief to considering information as knowledge. For example, Turban (1992) and Beckman (1997) define knowledge in relationship to, or close to, information. Conversely, another group considers the classical definition of knowledge—justified true belief—to be the best one (Nonaka & Takeuchi, 1995; van der Spek & Spijkervet, 1997). Still others consider knowledge to derive from experience and thinking, and say it originates in the mind/brain (Davenport & Prusak, 1998; Probst, Raub & Romhardt, 2000; Bennet & Bennet, 2004). A somewhat surprising observation is that many authors of KM books do not define knowledge, nor do they address the meaning or interpretation of the concept. When asked to define knowledge, 32 of the 34 participants in the KMTL study offered an immediate response. Of these responses, 84 percent tied knowledge directly to action or use (see Table). For example, John Seely Brown says, “Knowing has much more to do with knowledge in action, and we know infinitely more than we have knowledge. That is kind of a key differentiator I think. For example, why stories are so important . . . because they bring knowledge into play. It also has to do with why when I approach something and interact with it, it’s almost like something is going to pull the relevant stuff out of my head and I can now do something. I can do things I don’t even know that I can do.” Similarly, Juanita Brown tends to think about knowing collectively, “which means knowing together . . . and so to me knowledge has to do with the discovery of an inner knowing that is an embodied thing that enables the capacity to act.” Three other responders connected knowledge and knowing. One responder saw knowledge as, “The very simple, know-how, know-what, know-where, know-when, know-why about stuff in the organization, and if it in any way infuses the individual with some knowing experience other than the mundane side of the informative aspect of data, then it has knowledge qualities.” Another classified knowledge as a social phenomenon. “The experience of knowing is very much ours, but our ability to know is related to our engagement with community . . . then knowing is the experience of participating as an individual in this process of knowledge defined at the social level.” Yet another responder reflected that knowledge is related to the knowing dimensions in terms of, “you have a sense that it’s probably right. Knowledge is more an iconized package of the knowing, so it’s easier to share.” This sense of “rightness”, or truth, was the focus of another responder who saw knowledge as truth—validated rules derived analytically by first principles or validated through experimentation. Closely related to “rightness” was the reflection added by one responder that, “What is missing from knowledge is any issues of ethics and what it should be used for, where it’s coming from, what the purpose is, and the overall context within which knowledge should be embedded.” It is forwarded here that with knowledge comes the responsibility for how that knowledge is used. 3
In the study referenced above, these thought leaders labeled the field (approach, area, era, culture, discipline, focus, mentality, movement, revolution, space or strategy) as: (knowledge) awareness, connecting, ecology, emergence, environment, evolution, innovation, navigation, networking, shring, strategy and transfer. Also, as breakthrough thinking, collective intelligence, collective wisdom, competence learning, learning architecture and organizational learning.
Exploring Kn and KM
2
www.mountainquestinstitute.com
Offering a different perspective, Clyde Holsapple found the definition forwarded by Alan Newell in 1982 useful, looking at knowledge as “that which is conveyed in usable representations.” By representations Newell means patterns that may exist: symbolic, digital, mental, audiovisual, or behavior patterns. The other key part of Newell’s definition is usability. A representation that is usable suggests there is a processor that uses it, which then depends on the time, situation and context in which that processor is operating (Newell, 1982). In other words, some knowledge that may be very valuable in one situation is entirely irrelevant or not so important in another situation. The idea that knowledge is context sensitive and situation dependent has been recognized in the KM field (Bennet & Bennet, 2007a; Bennet & Bennet, 2007b). One definition that is descriptive in nature is: knowledge is considered as the intellectual property of the individual (what we have learned through books, experience, and conversations with others). A second definition descriptive in nature leans toward Karl Popper’s identification of knowledge objects as the basis for understanding knowledge. For example, Michael Sutton said, “I’m actually using a framework or taxonomy to describe knowledge, knowledge existing everywhere from the most molecular level in terms of DNA and the coding that goes into that (and that’s naturally created) versus the personal, psychological, philosophical beliefs held by an individual that cannot easily be shared (and their dispositions that they may not even be conscious of) to the abstractions that are codified for sharing purposes.” After a pause, Sutton thoughtfully adds, “Yet, in apparent contradiction, I believe very strongly in the social construction of knowledge within our different realities . . . There seem to be knowledge objects within and without.” This insightful reflection leads us to a discussion of knowledge from another frame of reference based on the universal and physical reality of information. In his three-volume study of the role of information in the structure of the Universe, the theoretical biologist Tom Stonier proposes that “organization is the physical expression of a system containing information” (Stonier, 1997, p. 14). By organization he means the existence of a non-random pattern of particles and energy fields, or more generally, the sub-units comprising any system. Thus, organization can be observed in space and time as a physical phenomenon. Stonier considers information (any organized or non-random pattern) to be a basic property of the Universe—as fundamental as matter and energy (Stonier, 1997). Along with Stonier, we take information to be any non-random pattern or set of patterns. Data (a subset of information) would then be simple patterns, and data and information would both be patterns but they would have no meaning until some organism recognized and interpreted the patterns. In other words, meaning comes from the combination of non-random patterns and an observer who can interpret these patterns to create recognition or understanding (Bennet & Bennet, 2008a). It is only when the incoming patterns from the environment are integrated with the internal neural patterns within the brain that they take on meaning to the individual. These units of understanding are referred to as semantic complexes. As Stonier explains, ... a semantic complex may be further information-processed as if it were a new message in its own right. By repeating this process, the original message becomes more and more meaningful as, at each recursive step, new semantic complexes are created. As these impinge on even larger areas provided by the internal information environment, whole new and elaborate knowledge structures may be built up—a process which leads to understanding (Stonier, 1997, p. 157).
Exploring Kn and KM
3
www.mountainquestinstitute.com
Thus knowledge exists in the human brain in the form of stored or expressed neural patterns that may be activated and reflected upon through conscious thought. This is a high-level description of the creation of knowledge that is consistent with the neural operation of the brain and is applicable in varying degrees to all living organisms. It took 50 years of research before this process of neuroplasticity (the capability of the external environment and learning to change the internal patterns and structure of the brain) was understood and accepted by the scientific community. (For an interesting review of how this happens, see Begley, 2007, pages 26-48.) Consistent with the above discussions, we have suggested a broad, operational definition of knowledge as follows: knowledge is the capacity (potential or actual) to take effective action in varied and uncertain situations (Bennet & Bennet, 2004). Note that knowledge is now a creation of the human mind. Recognizing that knowledge is created through associative patterning in the brain, it can be separated into two parts: Knowledge (Informing) and Knowledge (Proceeding) (Bennet & Bennet, 2008). This builds on the distinction made by Ryle (1949) between “knowing that” and “knowing how”. Knowledge (Informing), or KnI, is the information part of Knowledge; it could be implicit, explicit, tacit or any combination of these. KnI represents insights, meaning, understanding, expectations, theories and principles that support or lead to effective action. When viewed separately this is information that may lead to effective action. However, it is considered knowledge only when it is used as part of the knowledge process. Note that when the information part of knowledge is described and stored in a database or book, it is often referred to as knowledge artifacts4). Knowledge (Proceeding), KnP, represents the process and action part of knowledge. KnP is the process of selecting information relevant to a situation at hand and mixing it with internal information from memory to develop new information (KnI) that KnP process toward effective action. There is considerable precedence for considering knowledge as a process versus an outcome. As Kolb (1984) forwards in his theory of experiential learning, knowledge retrieval, creation and application requires engaging knowledge as a process, not a product. This is consistent with the relationship of knowledge and action previously discussed and forwarded by thought leaders across different disciplines (Argyis, 1993; Sveiby, 1997; Wiig, 2004; Huseman and Goodman, 1999; Devlin, 1999). Since a part of KnP, will always include tacit knowledge, the process used to find, create and semantically mix the information needed to take effective action is often difficult—if at all possible—to communicate to someone else. The more complex a situation, the larger the role of tacit knowledge (Bennet & Bennet, 2008a). This is why you cannot “teach” knowledge to anyone. What can be done is to put information together in a way that makes it easier for the learner to create the desired knowledge. Defining the Field Knowledge Management is an embryonic field that gives visibility and focus to an awareness and appreciation of knowledge. As explored above, knowledge, the foundational concept of KM, has been forwarded as the capacity to take effective action in varied and uncertain situations. 4
Information that relates to individual or group knowledge (such as that stored in libraries and various information systems) can be referred to as knowledge artifacts, a term forwarded by George Washington University (GWU), one of the first universities in the world to develop a dedicated knowledge management doctoral program (Stankosky, 2005). Exploring Kn and KM
4
www.mountainquestinstitute.com
Such capacity (both potential and actual) requires information, sense-making, understanding, context, theories, rules, insights, intuition and judgment, as well as anticipating the future. KM works primarily with meta-knowledge or knowledge about knowledge. Therefore, it is also concerned with learning, people, organizations, technology, networks and knowledge about knowledge processes. Finally, it is concerned with knowledge about designing, developing, leading, managing and changing organizations to improve their performance in a knowledge economy. As individuals and organizations began to refocus on knowledge as a core element of personal and professional success, they recognized the potential value in KM. Along with this recognition came nearly as many definitions of KM as there were individuals involved in the field. For example, nearly every KM book in the literature forwards its own definition of knowledge management. This, of course, makes meaning-making challenging as we move across the myriad of literature—and wide variety of authors—connected to the field. The concept of KM can also be biased in a number of directions. In the preface of Daryl Morey’s book of classic and contemporary works on knowledge management he notes, “All books, even collected works, are influenced by the frame of reference of the editors. In particular, there is a strong leaning toward the learning-centric view of knowledge management in this collection as opposed to an information-centric view. The learning-centric view emphasizes that knowledge is the ‘capability to act effectively’ and is derived from learning. Knowledge management in this view is a management function that accelerates learning.” (Morey et al., 2000, pxii) Note the similarity of Morey’s preferred definition to the relationship of knowledge and action emerging in the KMTL study and to our operational definition of knowledge. The information-centric view is exemplified by the Gartner Group’s definition of knowledge management: “Knowledge management is a discipline that promotes an integrated approach to identifying, managing and sharing all of an enterprise’s information assets, including database, documents, policies and procedures as well as unarticulated expertise and experience resident in individual workers” (Morey, Marbury & Thuraisingham 2000, pxii). On the other hand, the definition used during implementation of KM in the U.S. Department of the Navy was: “KM can be viewed as a process for optimizing the effective application of intellectual capital to achieve organizational objectives” (Porter, et al, 2002). Consistent with the literature, while 84 percent of responders in the KMTL study tied knowledge to action, the definitions of the field provided by these thought leaders—at least in terms of focus—were almost as diverse as the participants themselves in terms of focus. These responses are loosely grouped below. Responses defining KM that are of a descriptive nature included:
processes that are a part of knowledge strategies: the principles, tools and approaches that allow people to build knowledge assets and leverage them as part of how they do their work; the processes which include systems to collect, organize, validate, “verificate”, distribute, and archive information within context, within time, within certainty for humans to use; those systems and processes by which entities create, cultivate, and transfer that subset of information that is knowledge, usable and actionable;
Exploring Kn and KM
5
www.mountainquestinstitute.com
a collection of processes, policies and activities that help organizations better know what they know and use what they know; the processes whereby an enterprise uses its collective sources of intelligence to accomplish its objectives; and the creation and transfer of knowledge; and how we can identify, develop and use the relevant knowledge in our organizations more effectively.
A third set of KM definitions focuses more on effectiveness, improvement and value added. These are: creating, renewing, sharing, and so forth, knowledge for better performance; organizational performance and effectiveness; a concerted attempt to improve how you create or distribute or use knowledge in organizations; and, systematic approaches to enable information and knowledge to grow, to flow and to create value both for the individual and the organization. Similarly, four other definitions are worded in terms of value: the value and growth of intangible assets: the art of creating value by leveraging intangible assets; taking systematic approaches to the growth of intangible assets; and, the growth or renewal of our intangible assets. Creating a similar pattern to the earlier responses regarding the definition of knowledge, five KM definitions in the KMTL study focused on the concept of knowledge. Specifically: it’s about what you know that you know; structuring what you know so it can be reused and shared; the capacity collectively to move forward and deeper in our knowing together around key issues that make a difference to our lives; and, harnessing the collective know-how, experience and intellect of a group of people or an organization. As one responder explains, “The things that you know that would be helpful to other people, or things that you don’t even know that you know that would be helpful to other people, comprise that which we are trying to share ... with the outcome of improving the way the organization runs.” One thought leader moved the conversation to his concept of “deep knowledge.” He stated that the field of KM allows you to perhaps build the materials to participate in good conceptual blending, that is, the human capability of taking a concept with some relevance into a new concept or mental model that has the potential to provide a better approach, a better solution, an improvement. In this concept deep knowledge is not something that exists, it is a capability that people have to perform conceptual blendings that fit the new context, the new challenges. “Therefore, you will never have deep understanding of things yet to come, you will get that deep understanding when the situation emerges, but a priori you would not have it . . . see, I think we’re on a raft going down a white river and the actions respond when you get around the next corner and see the big rock in the middle. So, in essence, the field provides an approach to developing the deep knowledge capability needed to respond to and embrace an unknown future.” The largest grouping (eight) of KM definitions are focused on creating/managing an environment (or context). Specifically:
creating the environment—an ecology if you will—so that good things will happen; managing the environment in which knowledge can be created, evolved, exchanged and applied into products and services that benefit a constituency; developing a program or an effort through which you can create an environment within which the organization can make the optimum or maximum use of knowledge in the performance of its day-to-day activities;
Exploring Kn and KM
6
www.mountainquestinstitute.com
creating a context where ideas are likely to flourish and transfer well in organizations; creating a sufficiently shared context that information is meaningful and the output of it is knowledge; creating a context to bring the reflective capability to the fore; and the care and feeding of activities that make people and organizations better capable of building and utilizing this thing that we call knowledge.
Assuming creating/managing an environment (or context) is the responsibility of leadership, one response specifically described KM as leading to increase the capability to act in context by transferring this capability, and, of course, having the information level, competence and ability to process this information. Another thought leader defines KM as the efforts within an organization to manage knowledge resources; to organize, coordinate and implement and execute the activities that manipulate those resources; and to manage what is it that influences the knowledge resources that we have within an organization and what is it that influences how the patterns of knowledge processing unfold within an organization. A clear pattern emerging from these definitions –and many others appearing in the literature—is the recognition of knowledge as a human resource essential for the success of the organization or enterprise. Thus the need to “manage” that resource, with the recognition that “manage” means making the best use of the resource, not controlling or directing the resource, which clearly cannot be done. When the industrial age concept of management as control is applied, knowledge management is often proclaimed as an oxymoron. However, in the context of a knowledge era, how to develop, manage and apply the valuable resource of knowledge becomes the focus of KM strategies, processes and approaches. As we have discovered along the way—and recognizing the power of information and information systems in a global economy—successful knowledge management focuses on people and their interactions. Individuals must create and manage their own knowledge. According to one responder, the first wave of KM was focused on technology and the second on communities of practice and interest. The idea of KM as strategy was forwarded as the third wave focus. Further, one responder in the KMTL study says that realizing KM is a strategy leads to the understanding that communities are a way to engage the organization in strategic conversations about knowledge. For example, Etienne Wenger said, “It is often thought that strategy belongs to the CEOs, the leadership team. In fact, when you’re talking about knowledge, and if knowledge is the key to the capability of an organization, then managing this knowledge is managing the strategy of the organization, the knowledge-based, knowledge-driven strategy of the organization. So we have to be able to create that loop.” Another responder sees KM as an overarching, strategic, enterprise-wide initiative—a multiple, simultaneous and very complex thing—which includes strategic, enterprise-wide multiple simultaneous initiatives. We agree. Further, in the summary of the KMTL study, we forwarded that the field of KM is a complex adaptive system with many possibilities and opportunities. There are a number of reasons for this assertion. KM does not have a single leader or guru as was evident in earlier management initiatives such as TQM (Total Quality Management) and BPR (Business Process Reengineering)5. Because of this it does not have a narrow objective, a specified process, or a restricted domain of interest. This creates a flexibility and robustness, allowing the field (in terms of its continuously 5
A comparison of KM, TQM and BPR taken from the KMTL study is in Chapter 6 at www.mountainquestinstitute.com/Characterizing.htm
Exploring Kn and KM
7
www.mountainquestinstitute.com
emerging thought leaders and KM implementers) to adapt to—and address—issues and opportunities without being constrained by rigid practices or unquestioned edicts. Aided by the breadth and scope of the field and the variety of potential applications, KM leaders are free from the constraints of the need for imitation and relatively independent in their focus while simultaneously interdependent in terms of learning and creating new knowledge. As a group and individually, they can pursue different areas that can be brought together to focus on metaknowledge and its application to individual and organizational performance. Leadership is distributed, self-organizing, collaborative, and natural—just as are many KM activities such as knowledge sharing, communities of practice, and networking. It is this diversity that permits continuous learning and adapting to local needs and contexts as various methods and approaches are tested and evaluated. As Battram said, “complex behavior need not have a complex explanation, and order will emerge from ‘self-organization’ ” (Battram, 1996, p. 125). Considering the “self-organization” in the field of knowledge management, we begin to see that the subject matter (knowledge) and its corollary (learning), coupled with the objectives of improving organizational performance, provide a direction and focus for the field without constraining it. For a further discussion of this phenomenon see Bennet (2005). Exploring the Breadth of KM When we introduced the idea above that the field of KM is a complex adaptive system (hopefully intelligent ... but that’s up to all of us), we referred to the breadth and scope of the field in regards to the wide variety of potential applications. This is exemplified in the early work of Karl Wiig, who could arguably be called the father of knowledge management. His groundbreaking work lays a KM foundation built on three pillars: Exploring Knowledge (including surveying, categorizing, analyzing, codifying and organizing knowledge), Finding the Value of Knowledge (including appraising and evaluating knowledge), and Actively Managing Knowledge (including synthesizing knowledge-related activities, handling, using and controlling, leveraging, distributing and automating, and implementing and monitoring knowledge-related activities) . In his three books (Wiig, 1993; Wiig, 1994; Wiig, 1995), support materials range from taxonomies to practical suggestions for understanding and applying knowledge accompanied by hundreds of visuals. From another perspective, a 1999 survey article by Thomas Beckman titled “The Current State of Knowledge Management” stated that “Knowledge management is an emerging discipline with many ideas yet to be tested, many issues yet to be resolved, and much learning yet to be discovered” (Beckman, 1999, p. 1). Consistent with this stage of KM and its diversity of views, Beckman presented a brief outline of major ideas and practices in the field. When introducing KM he provided eight definitions of knowledge, and described five different typologies. He then considered the field from the additional perspectives of processes, technologies, organizations, management and implementation, with each of these perspectives yielding a differing set of viewpoints by knowledgeable authors in the field. In his conclusions Beckman noted, “Until the past few years, most of the knowledge, experience, and learning about KM has been accessible to only a few practitioners. However, during the past three years an explosion of interest, writing, research, and applications in KM has occurred. . . . Future work must focus on building practical experience through extensive experimenting, prototyping, and testing—especially in the process, technology, organizational, and implementation perspectives.
Exploring Kn and KM
8
www.mountainquestinstitute.com
In addition, the conceptual frameworks and integration across KM perspectives need more investigation and development.” (Beckman, 1999, pp. 1-1 through 1-22) Simultaneously, a growing interest in KM was occurring in the U.S. Federal Sector. Sponsored by the cross-government Knowledge Management Working Group6, working sessions were held in 2000-2001 to build an understanding of the concepts, roles, and importance of KM in the U.S. government. As a result of these sessions, the working group developed “learning objectives” for KM courses taught in the public sector7. Still used as a baseline, these objectives span the field of KM, setting the scope of the field for the United States Federal sector as well as the tens of thousands of businesses and tens of millions of professionals that support the U.S. government. These learning objectives make clear connections to earlier management movements such as total quality management, and provide a business focus for KM while emphasizing the importance of learning and knowledge; in other words, focusing on both the values of intangibles to the Federal sector and linking those intangibles directly to people and learning. The ideas presented through these learning objectives—built on the foundational work of research institutions such as the American Productivity and Quality Control (APQC, 2000) organization and The Knowledge Institute (an early research organization sponsored by IBM) as well as a myriad of ideas provided by practitioners and academia—provide an objective overview of the content of the field. Each of the learning objectives and a short explication of them is included below. Note that these are not prescriptive but rather provided as a guide to developing a deeper understanding of the field of KM. Learning Objective 1: Have knowledge of the value added by Knowledge Management to the business proposition, including the return on investment, performance measures, and the ability to develop a business case.
Though knowledge management is capitalized in this objective, knowledge management is best considered as having a small “k” and a small “m.” The intent is that knowledge management is not an initiative in and of itself, but supports the mission and business objectives of the organization, thus positioning KM as a strategic enabler for the organization. KM is an extremely broad field. Using metrics such as those related to the return on investment (ROI) bring solid management practices to the forefront of decision-makers, thereby enabling choices. Learning Objective 2: Have knowledge of the strategies and processes to transfer explicit and tacit knowledge across time, space, and organizational boundaries, including retrieval of critical archived information enabling ideas to build upon ideas.
Since Nonaka and Takeuchi (1995) first explored the interaction between tacit and explicit knowledge, there has been a steady growth of interest in the capture of tacit knowledge. Aging workforce issues in the public sector have served as a catalyst for the development of processes and systems that facilitate understanding the role and importance of context in decision-making. But this objective goes beyond understanding the nature of tacit and explicit knowledge to focus 6
The Federal Knowledge Management Working Group still serves as an integral part of the U.S. government KM community. 7 A detailed treatment of these learning objectives is included as Chapter 15 in Organizational Survival in the New World: The Intelligent Complex Adaptive System (Bennet & Bennet, 2004) and as Chapter 27 in the Handbook on Knowledge Management 1: Knowledge Matters (Bennet & Bennet, 2003).
Exploring Kn and KM
9
www.mountainquestinstitute.com
on the transfer of understanding. Increasing the dynamics of transfer moves knowledge through the organization at an increasing rate; the more knowledge that is being transferred, the more it is available to others—and the organization—as a resource. The use of teams, communities, mentors, and dialogues coupled with widespread organizational trust greatly assists the organization in sharing tacit knowledge. (See Bennet and Bennet, 2008, for a detailed treatment of explicit, implicit and tacit knowledge.) Learning Objective 3: Have knowledge of state-of-the-art and evolving technology solutions that promote KM, including portals and collaborative and distributed learning technologies.
We live in a world of technology. The exponential increase in data and information is both driven and enabled by information technology. We have the ability to reach further and further across domains and within domains for ideas and solutions. Knowledge repositories, automated libraries, computer services, databases, etc. offer the capability for not only storing large amounts of data and information, but also for the intelligent retrieval and assemblage of information. Powerful search algorithms, intelligent agents, and semantic interpreters allow employees to rapidly retrieve information needed for problem-solving and decision-making. Knowledge managers and leaders need to be aware of these capabilities, how they are used, and how to integrate their operation with people to ensure knowledge availability and application. Learning Objective 4: Have knowledge of and the ability to facilitate knowledge creation, sharing, and reuse including developing partnerships and alliances, designing creative knowledge spaces, and using incentive structures.
Knowledge creation, sharing, and reuse are the heart of KM programs and the knowledge-centric organization. As people share knowledge, and other knowledge workers use that knowledge and find new ways to improve on it and innovate, its value increases for all of the organization. This process also provides the opportunity to identify integrators (knowledge leaders who connect people and ideas together) and subject matter experts (who provide depth of thinking in specific areas). In turn, those involved in exchanges benefit from the exchange through a more complete understanding of the area addressed, thereby becoming a more valuable resource to the organization. Learning Objective 5: Have knowledge of learning styles and behaviors, strive for continuous improvement, and actively engage in exploring new ideas and concepts.
People learn differently. Some learn through reading, others through lectures or visual or graphic representations, while still others learn by doing. Effective transfer of information requires understanding different learning styles and how individuals learn and what their frame of reference is. Since adults often learn best from direct experience with real-world problems, how can this be extrapolated across a virtual environment? (Knowles, 1998) As learning becomes the mutual responsibility of leaders and workers, knowledge professionals must be constant learners, seeking new information and exhibiting behavior for others to model by continuously striving to improve the organization’s use of information and knowledge. This objective also sets the stage for capitalizing on new learning approaches including broadband Web-based multimedia. As new concepts unfold, models and theories for learning will evolve. A foundation in this area will prepare the organization and its knowledge workers for the future. Much has been learned about
Exploring Kn and KM
10
www.mountainquestinstitute.com
how adults learn from recent findings in Neuroscience that may significantly enhance our understanding of how we learn—and our ability to learn—in the near future! Learning Objective 6: Have working knowledge of state-of-the-art research and implementation strategies for knowledge management, information management, document and records management, and data management. This includes project management of knowledge initiatives and retrieval of critical archived information.
Knowledge leaders and workers need to understand the conceptual linkages between knowledge management, information management, and data and records management. KM is part of a larger movement supported by information technology, a movement that has brought us into the information age and is rapidly propelling us toward an age of increasing complexity where knowledge appears to be the only way to deal with complexity. There are continuing advances in data management, document and records management, and information management that will make information technology infrastructures more effective in supporting knowledge workers as they make their organization more effective through intelligent management of the knowledge environment. The knowledge centric organization will make maximum use of technology and the latest research findings related to information and knowledge management. Learning Objective 7: Have understanding of the global and economic importance of developing knowledge-based organizations to meet the challenges of the knowledge era .
We live in an omni-linked world. Anyone in the world can talk to almost anyone else in the world in real time. Technology has provided totally new ways of moving and transferring data, and information among individuals, organizations, and governments. The results of these interactions are increased communication, and a corresponding increase in the flow of ideas. Organizations are forced to scan, select, and quickly respond to the increased flow of Web-based exchanges and actions. Moreover, as the number of nodes in networks increase, the number of links increase, and as the links and their consequent relationships increase, so does the complexity. Critical thinking, the possession of deep knowledge, and the ability to work collaboratively with others who think differently may help address issues of increasing complexity. Knowledge-based organizations need to provide time and space for critical thinking. Learning Objective 8: Have the ability to use systems thinking in implementing solutions.
KM addresses powerful activities throughout environments, organizations, cultures, and economies. As one considers the relevant issues and opportunities, systems thinking provides a means for looking at the “big” picture while examining the component parts. Systems thinking assumes that almost everything is a system, made up of connecting elements and their relationships. Systems thinking is one of the integrative competencies that knowledge workers need to work effectively in a complex environment. Systems have boundaries and behaviors that are different from their individual elements. Systems thinking emphasizes the importance of relationships and structure within the organization and makes individuals aware of the effects of their efforts on others in the organization, permitting them to understand and perform their roles more effectively. Learning Objective 9: Have the ability to design, develop, and sustain communities of interest and practice.
Exploring Kn and KM
11
www.mountainquestinstitute.com
Communities are social constructs. In a primarily virtual world, communities provide a fundamental capability for developing and sharing expertise throughout the workforce. Communities of practice share a domain of practice, crossing operational, functional, and organizational boundaries and defining themselves by knowledge areas, not tasks. In like manner, communities of interest share a domain of interest. Communities are managed by establishing and developing connections between individuals and organizations, and focusing on value added, mutual exchange, and continuous learning. They have an evolving agenda as participant knowledge builds and related areas of exchange emerge. Collaboration, innovation, learning, and knowledge mobilization are at the core of communities of practice and interest. Communities increase information flows in order to maximize knowledge, and exploit existing competencies to achieve maximum return. They also facilitate the transfer of best practices and lessons learned between organizational content centers, thus creating efficiencies while improving effectiveness. And communities fill in the gaps where organizational knowledge falls short and where enterprise information is underexploited. In short, sometimes we do not know what we do not know. Communities encourage personnel to access key resources and build new knowledge to complete tasks faster, better, and easier. Learning Objective 10: Have the ability to create, develop, and sustain the flow of knowledge. This includes understanding the skills needed to leverage virtual teamwork and social networks.
The flow of data, information, and knowledge moves around in the networks of systems and people. It is shared through team interaction, communities, and events, and is facilitated through knowledge repositories and portals. This flow is both horizontal and vertical, including the continuous, rapid two-way communication between key components of the organization and toplevel decision-makers. With increased connectivity, we reach further and further across organizations, communities, industries, and the globe to tap resources. Virtual teamwork requires new skills of leadership, management, and facilitation to create and maintain the trust, open communication, and interdependencies needed for physically separated individuals to collaborate effectively. Learning Objective 11: Have the ability to perform cultural and ethnographic analyses, develop knowledge taxonomies, facilitate knowledge audits, and perform knowledge mapping and needs assessments.
As the amount of information and knowledge increases, tools such as taxonomies, audits, and maps help organize information for decision-making. While search engines and agents keep improving, the bottom line is that the human brain is the final arbiter of effective relationships and patterns. Analytic techniques such as cultural and ethnographic analyses and social network analysis help leaders understand organizational cultures and their characteristics. Culture is often cited as one of the main barriers to successful implementation of KM. Learning Objective 12: Have the ability to capture, evaluate, and use best-known practices, including the use of storytelling to transfer these best practices.
Exploring Kn and KM
12
www.mountainquestinstitute.com
The use of best practices across industry and government can provide efficiencies and increase effectiveness, if they are indeed best practices for each specific organization and if the organizational needs in that area are stable. How is the applicability of a best practice determined? How do you understand the context of the best practice, the simple rules that made it successful in some organizations? Further, as we move into an uncertain and complex future, overarching patterns of best practices may serve as the basis upon which transfer of best practices among organizations. These overarching patterns are most likely to carry over to other organizations even if specific process needs vary because of changes in the internal and external environments. Storytelling, the construction of examples to illustrate and understand a point, can be used to effectively transfer knowledge and best practices. A variety of story forms exist that will arise naturally throughout organizations, including scenarios and anecdotes. Scenarios are the articulation of possible future states, constructed within the imaginative limits of the author. An organizational story is a detailed narrative of management actions, employee interactions, or other intra-organizational events that are communicated informally within the organization. Storytelling connects people, develops creativity, and increases confidence. The appeal of stories in organizations helps build descriptive capabilities, increase organizational learning, convey complex meaning, and communicate common values and rule sets. There is a natural sharing of stories through the use of teams and communities. Learning objective 13: Have the ability to manage change and complex knowledge projects.
Management concepts, whether old or new, are about change management. Considering Ross Ashby’s law of requisite variety, which says there must be as many or more ways to change a system as those things in a system that need to be changed, today’s world of increasing complexity presents increasing challenges (Ashby, 1964). It is also recognized that cultural change of any kind is a long, slow process. Add to that the fact that KM initiatives are particularly challenging because of the uncertainty of outcomes. Most managers like to change only one or two things at a time to mitigate against unintended consequences. This is not possible with KM. Accomplishing change requires daily support of sharing knowledge openly throughout the entire organization. Learning Objective 14: Have the ability to identify customers and stakeholders and tie organizational goals to the needs and requirements of those customers and stakeholders.
Total quality management brought to the forefront the tried and true values successful organizations have used for years, a focus on customers and stakeholders. No matter what new approach or initiative is popular, organizations must keep a focused eye on the needs of their constituents, and ensure all efforts underway contribute to fulfilling those needs. This makes good business sense for public and private organizations alike. Final Thoughts This paper has addressed a number of issues and perspectives related to knowledge and knowledge management that offer insights into the diversity and potentiality of these concepts. The variety of interpretations and usage of the terms information, knowledge and knowledge management are indicative of their flexibility and robustness. On the other hand, such variety makes communication difficult and slows down the development of knowledge management as a
Exploring Kn and KM
13
www.mountainquestinstitute.com
potential discipline. This may well be for the overall good. While they increase rigor and depth of knowledge and create boundaries, disciplines also restrict thinking, create standards of acceptability and limit ways of approaching problems. Perhaps knowledge and KM are too foundational and powerful concepts to be contained within the constraints of a discipline. As we relook at the field of KM three years after the initial study, we still believe in the strong potential it offers for the future. In the course of life, the history of KM is short, but vibrant and pregnant with possibilities and potentialities for all who take knowledge, understanding, and the greater good seriously. KM offers the potential to fulfill—and may be able to fulfill as it churns and changes in response to a turbulent world—a fundamental need of individuals and organizations. This need is to make better use of the creation and application of knowledge to strengthen institutions, increase individual competence and improve the value produced by both. As the world shrinks in space and time and marches toward intangible values, global collaboration, and the multiplication and entanglement of living networks and artifacts, the need to appreciate and advance knowledge will be the seminal force for growth and survival so long as civilizations remain coherent. Since the Greek philosophers, we have nurtured and sometimes abused the concept of knowledge, while always seeming to make longer-term progress. This upstart called knowledge management may be at the leading edge of a renaissance of thinking, creating, sharing and applying our greatest human asset—the ability to observe, understand, learn, make sense out of our environment, and act upon our situation, what, in short, is knowledge.
References Argyis, C. (1993). Knowledge for Action. A guide to Overcoming Barriers to Organizational Change. San Francisco: Jossey Bass. APQC (2000). Report On Knowledge Management. Houston, TX: APQC. Ashby, W.R. (1964). An Introduction to Cybernetics. London: Methuen. Battram, A. (1996). Navigating Complexity: The Essential Guide to Complexity Theory in Business and Management. London: The Industrial Society. Beckman, T.J. (1999). “The current state of knowledge management” in Liebowitz (Ed.). Knowledge Management Handbook. Boca Raton, FL: CRC Press. Begley, S. (2007).Train Your Mind, Change Your Brain: How the New Science Reveals Our Extraordinary Potential to Transform Ourselves, Ballantine Books, New York, NY. Bennet, A. (2005). Exploring Aspects of Knowledge Management that Contribute to the Passion Expressed by Its Thought Leaders. Available at www.mountainquestinstitute.com Bennet, A. & Bennet, D. (2008). “The decision-making process for complex situations” in Burstein, F. and Holsapple, C.W. (Eds.) (2008), Handbook on Decision Support Systems 1: Basic Themes, Berlin: Springer-Verlag Bennet, A. & Bennet, D. (2007a). “CONTEXT: The shared knowledge enigma,” in VINE: The Journal of Information and Knowledge Management Systems, Volume 37, Number 1. Bennet, A. & Bennet, D. (2007b). Knowledge Mobilization in the Social Sciences and Humanities: Moving from Research to Action. Frost, WV: MQI Press. Bennet, A. & Bennet, D. (2004). Organizational Survival in the New World: The Intelligent Complex Adaptive System. New York: Elsevier.
Exploring Kn and KM
14
www.mountainquestinstitute.com
Bennet, A. & Neilson, R. (2003). “The leaders of knowledge initiatives: Qualifications, roles, and responsibilities” in Holsapple, C.W. (Ed.), Handbook on Knowledge Management 1: Knowledge Matters. New York: Springer-Verlag. Bennet, D. & Bennet, A. (2008a). “Engaging tacit knowledge in support of organizational learning”, in VINE: The Journal of Information and Knowledge Management Systems, Volume 38, No. 1. Bennet, D. and Bennet, A. (2008b), “Associative patterning: The unconscious life of an organization”, in Girard, J.P. (Ed.), Organizational Memory, ICI Global, Hershey, PA. Davenport, T.H. & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Boston, MA: Harvard Business School Press. Devlin, K. (1999), INFOSENSE: Turning Information into Knowledge, W.H. Freeman and Company, New York, NY. Huseman, R.C. & Goodman, J.P. (1999), Leading with Knowledge: The Nature of Competition in the 21st Century, SAGE Publications, London, UK. Knowles, M. (1998). The Adult Learner. Houston, TX: Gulf Publishing Company. Kolb, D.A. (1984). Experiential Learning: Experience as the Source of Learning and Development, Prentice Hall, Englewood Cliffs, NJ. Morey, D., Marbury, M. & Thuraisingham, B. (2000). Knowledge Management: Classic and Contemporary Works. Cambridge, MA: the MIT Press. Newell, A. (1982). “The knowledge level” in Artificial Intelligence 28(2), 1982. Nonaka, L. & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press. Porter, D., Bennet, A., Turner, R. and Wennergren, D. (2002). The Power of Team: The Making of a CIO. Washington, D.C.: Department of Navy Chief Information Officer. Probst, F., Raub, S. & Romhardt, K. (2000). Managing Knowledge: Building Blocks for Success. West Sussex, England: John Wiley & Sons Ltd. Ryle, G. (1949). The Concept of Mind. London: Hutchinson. Stankosky, M. (2005). Stonier, T. (1997). Information and Meaning: An Evolutionary Perspective. New York, NY: Springer. Sveiby, K. (1997). The New Organizational Wealth: Managing & Measuring Knowledge-Based Assets. San Francisco, CA: Berrett-Koehler Publishers. Turban, E. (1992). Expert Systems and Applied Artificial Intelligence. New York: Macmillan. Van der Spek, R. & Spiskervet, A. (1997). “Knowledge management: Dealing intelligently with knowledge” in Liebowitz, J. and Wilcox, L., Knowledge Management and Its Integrative Elements. New York: CRC Press. Wiig, K. (2004). People-Focused Knowledge Management: How Effective Decision Making Leads to Corporate Success. New York, NY: Elsevier. Wiig, K. (1995). Knowledge Management Methods—Practical Approaches to Managing Knowledge. Arlington, TX: Schema Press. Wiig, K. (1994). Knowledge Management: The Central Management Focus for IntelligentActing Organizations. Arlington, TX: Schema Press. Wiig, K. (1993). Knowledge Management Foundations—Thinking About Thinking—How People and Organizations Create, Represent, and Use Knowledge. Arlington, TX: Schema Press.
Exploring Kn and KM
15
www.mountainquestinstitute.com
