Managing Codified Knowledge

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Leading management and organization theorists have popularized the concept of treating organizational knowledge as a valuable strategic asset.1 They advise that to remain competitive, an organization must efficiently and effectively create, locate, capture, and share knowledge and expertise in order to apply that knowledge to solve problems and exploit opportunities. As more firms begin to incorporate knowledge management into their overall business strategy, many are showing tremendous interest in implementing knowledge management processes and technologies.

Although knowledge management is gaining wider acceptance, few organizations today are fully capable of developing and leveraging critical organizational knowledge to improve their performance.2 Many organizations are so complex that knowledge is fragmented, difficult to locate and share, and therefore redundant, inconsistent, or not used at all. In today’s environment of rapid change and technological discontinuity, even knowledge and expertise that can be shared often quickly becomes obsolete. However, while the popular press calls for effectively managing knowledge, almost no research has been done regarding how to do it.

This article focuses on how to configure a firm’s resources and capabilities to leverage its codified knowledge. I refer to this broadly as a knowledge management architecture. I based this framework on research that was motivated by several questions:

  • What are the characteristics of explicitly codified knowledge and how should organizations think about managing it?
  • What role should information technology play?
  • How are organizational capabilities and information technology best integrated and applied to managing knowledge?
  • What lessons have companies learned in these endeavors?

To address these questions, I first describe the characteristics of explicit knowledge and its relationship to competitive advantage. Building on research and knowledge about the design of information products,3 I describe an architecture for managing explicit knowledge. I use that framework to derive two fundamental and complementary approaches, each of which is illustrated by a case study. I conclude with a summary of key issues and the lessons learned.

What Is Knowledge?

Knowledge is commonly distinguished from data and information. Data represent observations or facts out of context that are, therefore, not directly meaningful. Information results from placing data within some meaningful context, often in the form of a message. Knowledge is that which we come to believe and value on the basis of the meaningfully organized accumulation of information (messages) through experience, communication, or inference.

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1. For example, see:

J.S. Brown and P. Duguid, “Organizational Learning and Communities-of-Practice: Toward a Unified View of Working, Learning and Innovation,” Organization Science, volume 2, February 1991, pp. 40–57;

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