A process-centric approach to knowledge creation is the latest adjunct to the two methods previously described. Process-centric concept of knowledge creation is based on a widely used notion of domain destruction and creation proposed by Boyd (1976). Contrary to either people- or technology-centric models, the pro- cess-centric concept is based on destroying the pre-existing domains, selection of their relevant components, then recombining these components into an entirely new domain relevant to the activities within the changed environment. The funda- mental assumptions of the process-centric model are based on quantitative physics and mathematical analysis [ibid], but the model also incorporates both people- and technology-centric concepts.
Central to Boyd’s idea of destruction and creation is the thesis that in order to cope with our environment we develop mental patterns or concepts of meaning (domains) (i.e., knowledge). However, the world in which we act constitutes an ever-changing environment that demands flexibility of interaction with and response to its continuous and often unpredictable demands. Continual destruction of historically established domains, constructive extraction of their subcomponents, and their recombination into new patterns are fundamental aspects of the response patterns that allows us to be shaped and shape our environment, in a similar fashion to Gidden’s structuration theory (Giddens, 1979).
According to Boyd, there are two main ways to approach creating concepts; (1) deduction and analysis—moving from general to specific, or (2) induction and synthesis—moving from specific to general (Boyd, 1976). As time is traversed, be it at an individual level, organizational level or societal level, domains of knowl- edge are formed to represent observed reality. Destructive deduction is achieved by removing domain boundaries and the disassociation of the previously ordered domain constituent into a chaos. Faced with such disorder the natural propensity is to regain the state of equilibrium and reconstruct order and meaning. The pro- cess of reconstituting such order requires induction, synthesis and integration and ends in the construction of a new domain where new commonalities and orderly interrelationships govern the existence of previously disparate parts. The process reflects the fundamental essence of knowledge creation, and the forming of these commonalities and creation of a new domain constitute the principal force that drives increases in the extant knowledge base. However, since the original goal was to re-establish equilibrium, the new domain and the new state of order that it both imposes and represents through the re-establishment of the state of equilibrium of all subcomponents also represents germane knowledge.
Boyd’s approach to creation is rooted in mathematics and physics, a novel ap- proach that may, ultimately, provide quantitative foundations of the process. Using Gödel’s Theorem (Boyd, 1976) describing incompleteness and inconsistency of ordered systems Boyd demonstrates that “in order to determine the consistency of any new system we must construct or uncover another system beyond it” (von Lubitz et al., 2004). However, the degree of intrusion into the system necessary for the construction of a new one is governed by Heisenberg’s uncertainty principle.
Hence, the uncertainty values not only represent the degree of intrusion by the ob- server upon the observed but also the degree of confusion and disorder perceived by that observer.
All natural processes generate entropy, and any closed system is characterized by a progressive increase of its chaos and disorder. Combining Gödel’s theorem, Heisenberg’s uncertainty principle, and the third law of thermodynamics, Boyd argues that any inward-oriented and continued effort to improve the match-up of concept with observed reality will only increase the degree of mismatch. Hence, we can expect unexplained and disturbing ambiguities, uncertainties, anomalies, or apparent inconsistencies to emerge with the frequency that is proportionate to our efforts to re-establish the order within the system. As a result, rather than reverting to the stability of equilibrium, we will impose an ever-increasing degree of confu- sion and chaos. Seen from a practical perspective of an organization wishing to survive and thrive in the dynamically changing environment of modern business, any attempt at introspective analysis of its operation that is limited to historical knowledge is doomed to failure and may be the main contributor to the downfall of the organization itself. The only solution available, and the only solution that assures continuous progress is then that proposed by Boyd: a contiguous destruc- tion of old domains, extraction of pertinent subcomponents, and recombination into new domains (Boyd, 1976). The solution also defines the role of the construc- tor—the more direct involvement in the destruction/creation process, the greater potential for inducing chaos. The creator needs to assume a superior position of providing overall guidance rather than participate in the details of the execution.
Inadvertently, we have then arrived at the confirmation of one of the essential rules of operational conduct: micromanagement by superior entities of the organization is one of the most harmful forms of interaction that, rather than inducing order, produce chaos and loss of working potential. Consequently, the level and adequacy of the organization’s germane knowledge will suffer and its decline will lead the organization to the rapidly steepening path of self-destruction.
The biologically motivated instinct of survival is a characteristic as much of societies as their functional subcomponents—organizations. More importantly, the exponent of the quality of survival is the measure of how well it fits into the pattern of prede- termined survival characteristics (i.e., “survival on our terms”) (Boyd, 1976). Thus, for example, the notion of a sustainable competitive advantage for an organization translates into being an active participant in the activities of the selected industry on
terms predetermined by the organization. Such terms must allow the organization to continue the sole and complete occupation of its “ecological niche” in a manner that excludes incursion by a competitor. Using military analogy (von Lubitz et al., 2004), the organization’s goal is therefore to improve its capacity for independent action that, in turn, allows it the capacity for a flexible response to any emergent threat (ibid). Consequently, individuals and groups must form, dissolve, and reform their cooperative or competitive postures in order to overcome environmental obstacles which may impede or even prevent survival. Knowledge is the primary tool in the development of the appropriate survival strategy and, hence, the goal of knowledge management should be to focus on the knowledge creation effort. New knowledge, as long as it remains inaccessible to the competitor, then becomes one of the most essential weapons in gaining operational superiority, and continuous development of new knowledge—the prerogative for the sustainment of competitive advantage.
It is in this context that actions and decisions become of critical importance.
The process centric perspective of knowledge creation and the ability of Boyd’s loop to support analysis and consequent action of dynamic operations rapidly, makes it a most important aspect for all knowledge-based enterprises to incorporate into their decision-making activities. Knowledge-based enterprises must continuously operate at optimal efficiency in complex and unstable environments and Boyd’s
Figure 10. Process centric perspective of knowledge creation
Observation Data/information collection
Orientation Data transformation/
analysis/
Generation of germane information Determination
Action
Germane knowledge development Superior decisions Optimal solutions Winning strategies
Boyd’s Loop
Storage of non-germane data/information
Process-centric Perspective to Knowledge Creation
loop provides a most suitable tool to ensure that at all times rapid decision-making is superior.
Chapter Summary
Any knowledge creation process should start with a clear understanding of the organizational specifics, like the type and the structure of the organization, the dynamics of the people, process, and technology, the multi-dimensional nature of knowledge and the different possible approaches to knowledge creation. The KM Triad and the KM Diamond facilitate such an understanding. Specifically, the KM Triad emphasizes the socio-technical perspectives for knowledge management while the KM diamond emphasizes the impact of the socio-technical perspectives on the four steps of knowledge management and/or knowledge itself.
From the KM Diamond we can see the pivotal role played by knowledge creation, the first step in the KM cycle; since it impacts and simultaneously is impacted by the other steps. Currently two well-established approaches for addressing KM are the algorithmic/technology focused perspective (i.e., data mining and the KDD process) or the psycho-social/people focused perspective (i.e., Nonaka, Spender,
& Blacker’s respective frameworks). In our opinion, a key limitation is that, taken in isolation, these respective perspectives on knowledge creation present a partial picture of the multifaceted knowledge construct. Given the importance of knowledge creation in the knowledge economy, we believe a more complete picture can be obtained by amalgamating these two perspectives into a unified meta-framework.
This is best illustrated by taking a process centric perspective to knowledge cre- ation. Such a meta- framework is of particular value and relevance to enable and facilitate knowledge re-use as it attempts to address a current systemic limitation with respect to knowledge creation.
References
Adriaans, P., & Zantinge, D. (1996). Data mining. Addison-Wesley.
Alavi, M., & Leidner, D. (2001). Review: Knowledge management and knowl- edge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107-136.
Alberthal, L. (1995, October 23). Remarks to the financial executives institute.
Dallas, TX.
Barnett, T. P. M. (2004). The Pentagon’s new map. New York: G. P. Putnam &
Sons.
Becerra-Fernandez, I., & Sabherwal, R. (2001). Organizational knowledge man- agement: A contingency perspective. Journal of Management Information Systems, 18(1), 23-55.
Bendoly, E. (2003). Theory and support for process frameworks of knowledge discovery and data mining from ERP systems. Information & Management, 40, 639-647.
Berry, M., & Linoff, G. (1997). Data mining techniques: For marketing, sales, and customer support. John Wiley & Sons.
Boland, R., & Tenkasi, R. (1995). Perspective making perspective taking. Organi- zational Science, 6, 350-372.
Boyd JR COL USAF. (1976). Destruction and creation. In R. Coram (Ed.), Boyd.
New York: Little, Brown, & Co.
Burrell, G., & Morgan, G. (1979). In search of a framework: Part 1. Sociological Paradigms and Organizational Analysis, 1-37.
Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., & Zanasi, A. (1998). Discovering data mining from concept to implementation. Prentice Hall.
Choi, B., & Lee, H. (2003). An empirical investigation of KM styles and their effect on corporate performance. Information & Management, 40, 403-417.
Chung, M., & Gray, P. (1999). Special section: Data mining. Journal of Manage- ment Information Systems, 16(1), 11-16.
Davenport, T., & Grover, V. (2001). Knowledge management. Journal of Manage- ment Information Systems, 18(1), 3-4.
Davenport, T., & Prusak, L. (1998). Working knowledge. Boston: Harvard Business School Press.
Drucker, P. (1993). Post-capitalist society. New York: Harper Collins.
Fayyad, Piatetsky-Shapiro, Smyth. (1996). Advances in knowledge discovery and data mining. Menlo Park, CA: AAAI Press / The MIT Press.
Holsapple, C., & Joshi, K. (2002). Knowledge manipulation activities: Results of a Delphi study. Information & Management, 39, 477-419.
Kovalerchuk, B., & Vityaev, E. (2000). Data mining in finance: Advances in rela- tional and hybrid methods. Kluwer Academic Publishers.
Krzysztof, J. C. (2001). Medical data mining and knowledge discovery. Physica- Verlag.
Malhotra, Y. (2000). Knowledge management and virtual organizations. Hershey, PA: Idea Group Publishing.
Markus, L. (2001). Toward a theory of knowledge reuse: Types of knowledge reuse situations and factors in reuse success. Journal of Management Information Systems, 18(1), 57-93.
McGee, M. K. (1997, September 22). High-tech healing. Information Week.
Newell, S., Robertson, M., Scarbrough, H., & Swan, J. (2002). Managing knowledge work. New York: Palgrave.
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Orga- nizational Science, 5, 14-37.
Nonaka, I., & Nishiguchi, T. (2001). Knowledge emergence. Oxford: Oxford Uni- versity Press.
Orlikowski, W. (1992). The duality of technology: Rethinking the concept of tech- nology in organizations. Organization Science, 3(3), 398-427.
Parent, M. R., Gallupe, W., Salisbury, J., & Handelman. (2000). Knowledge creation in focus groups: Can group technology help? Information & Management, 38, 47-58.
Polyani, M. (1958). Personal knowledge: Towards a post-critical philosophy. Chi- cago: University Press.
Polyani, M. (1966). The tacit dimension. London: Routledge & Kegan Paul.
Schultze U. (1998, December). Investigating the contradictions in knowledge man- agement. Presentation at IFIP.
Schultze, U., & Leidner, D. (2002). Studying knowledge management in informa- tion systems research: Discourses and theoretical assumptions. MIS Quarterly, 26(3), 212-242.
Spiegler, I. (2003). Technology and knowledge: Bridging a “generating” gap. In- formation and Management, 40, 533-539.
Swan, J., Scarbrough, H., & Preston, J. (1999). Knowledge management: The next fad to forget people? Proceedings of the 7th European Conference in Informa- tion Systems.
von Lubitz, D., & Wickramasinghe, N. (2005). Creating germane knowledge in dynamic environments. International Journal of Innovation and Learning (in press).
Wespi, A., Deri, L., Kmiec, Z., & Vigna, G. (2002, October 16-18). Recent advances in intrusion detection. Proceedings of the 5th International Symposium, Zurich, Switzerland. Springer Verlag.
Wickramasinghe, N. (2003). Knowledge management and data mining: Strategic imperatives for healthcare. In A. Fadlalla, E. Geisler, & J. Schaffer (Eds.), Proceedings of the 3rd Hospital of the Future Conference.
Wickramasinghe, N. (2003). Do we practice what we preach: Are knowledge man- agement systems in practice truly reflective of knowledge management systems in theory? Business Process Management Journal, 9(3), 295-316.
Wickramasinghe, N. (2005a). The phenomenon of duality: A key to facilitate the transition from knowledge management to wisdom for inquiring organiza- tions. In Courtney et al. (Eds.), Inquiring organizations. Hershey, PA: Idea Group Publishing.
Wickramasinghe, N. (2005b). Knowledge creation. In D. Schwartz (Ed.), A meta- framework (pp. 326-335). Hershey, PA: Idea Group Publishing.
Wickramasinghe, N. (2005c). Knowledge creation: A meta-framework. International Journal of Innovation and Learning (in press).