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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Knowledge Engines for Critical Decision Support

Knowledge Engines for Critical Decision Support
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Author(s): Richard M. Adler (DecisionPath, Inc., USA)
Copyright: 2011
Pages: 21
Source title: Gaming and Simulations: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-195-9.ch803

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Abstract

Current knowledge capture and retention techniques tend to codify “what-is” and “who knows” more effectively than “how-to”. Unfortunately, “how-to” knowledge is more directly actionable, and indispensable for critical organizational activities such as strategic analysis and decision-making. KM theorists often despair over “how-to” expertise as a form of tacit knowledge that is difficult to articulate, much less transfer. We argue that tacit strategic performance-based knowledge can often be captured and deployed effectively, via frameworks that combine scenario planning methods with “what-if” simulation. The key challenges are two-fold: (1) modeling complex situational contexts, including known behavioral dynamics; and (2) enabling knowledge workers to manipulate such models interactively, to safely practice situational analysis and decision-making and learn from virtual rather real mistakes. We illustrate our approach with example knowledge-based decision support solutions and provide pointers to related literature.

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