Managing the Knowledge Life Cycle
Most executives today recognize that their organizations must be able to manage knowledge effectively — it’s a strategic imperative. Just how they should go about developing that ability is the challenge. As in most other areas of management advice, there is no shortage of useful frameworks, models and checklists to choose from. Unfortunately, these solutions are generally undifferentiated; they are presented as applicable in any and all situations, and managers are left to make their own mistakes as they use one tool or another to ill effect. To take only one example, communities of practice, while immensely valuable in some contexts, have limited utility in others.
We believe that executives can begin to take a more nuanced approach to this issue if they realize that knowledge has a life cycle. Life-cycle models have already been usefully developed as a tool for thinking about products and technology, and the idea that knowledge changes form as it diffuses through a population is well established.1 The practical implications of the knowledge life cycle, however, have not been discussed in detail.
Over the course of a five-year study, we have devised a model to help explain the life of an idea in commercial settings. The model shows that new knowledge is born as something fairly nebulous (often in the head of one individual) and that it takes shape as it is tested, matures through application in a few settings, is diffused to a growing audience, and eventually becomes widely understood and recognized as common practice. ( For an overview of our study, see“About the Research.”) In this article, we develop the concept of the knowledge life cycle in detail and then describe appropriate strategies for managing ideas at each stage of the cycle. We also outline the model’s implications for companies’ knowledge strategies as a whole.
Knowledge-management tools are not universally applicable; different tools are required at different stages of an idea’s life. Executives who understand the dynamics of the life cycle in their industry will be better able to determine what kind of knowledge their organization needs and how they can effectively select and develop the tools and techniques to manage it.
References
1. See, for example, M.H. Boisot, “Knowledge Assets: Securing Competitive Advantage in the Information Economy” (New York: Oxford University Press, 1999); E.M. Rogers, “Diffusion of Innovations” (New York: Free Press, 1962); and K. Moore and J. Birkinshaw, “Managing Knowledge in Global Service Firms: Centres of Excellence,” Academy of Management Executive 12 (November 1998): 81–92.
2. Our model builds particularly on the ideas developed by M. Boisot in “Knowledge Assets.” The key point is that while more and more companies or individuals are aware of and have access to a form of knowledge as it moves up the vertical axis in later stages, the knowledge is not necessarily more valuable to them or applicable without substantial effort. In some cases, knowledge can be fully diffused but not applied or used appropriately.
3. Patent protection, of course, may limit other companies’ ability to use new knowledge. In this article, we do not give much consideration to patent protection since it rarely applies to knowledge services like management consulting.
4. See E. Wenger and W. Snyder, “Communities of Practice: The Organizational Frontier,” Harvard Business Review (January–February 2000): 139–146.
5. M. Arend, “New Chase CIO Setting up Centers of Excellence,” ABA Banking Journal (March 1992): 62.
6. See http://www.livinginnovation.org/displaySection.html?id=99&cold= 34&secList=99+100+101+102.
7. Our argument is at odds with the often-quoted distinction between personalization and codification strategies set out by M. Hansen, N. Nohria and T. Tierney in “What’s Your Strategy for Managing Knowledge?” Harvard Business Review (March–April 1999): 106–116. They argue that a company should essentially choose one knowledge strategy or the other. Our belief is that organizations should follow strategies according to the life-cycle stage of the knowledge in question. A company bridging stages two and three is likely to need both personalization and codification capabilities.