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Decision engineering (more recently called Decision Intelligence by The Decision Intelligence Institute International〔http://www.tdi3.org The Decision Intelligence Institute International〕 and companies like Quantellia〔http://www.Quantellia.com Quantellia〕) is a framework that unifies a number of best practices for organizational decision making. It is based on the recognition that, in many organizations, decision making could be improved if a more structured approach were used. Decision engineering seeks to overcome a decision making "complexity ceiling", which is characterized by a mismatch between the sophistication of organizational decision making practices and the complexity of situations in which those decisions must be made. As such, it seeks to solve some of the issues identified around complexity theory and organizations. In this sense, decision engineering represents a practical application of the field of complex systems, which helps organizations to navigate the complex systems in which they find themselves. Decision engineering can also be thought of as a framework that brings advanced analytics techniques to the desktop of the non-expert decision maker, as well as incorporating, and then extending, inductive reasoning and machine learning techniques to overcome the problems articulated in Black swan theory. Decision engineering proponents〔Lorien Pratt and Mark Zangari: (''The new science of decision engineering''. ) Telecom Asia, September 2008.〕 believe that many organizations continue to make poor decisions.〔John Hagerty, Rita L. Sallam, James Richardson: (''Magic Quadrant for Business Intelligence Platforms ) Gartner, February 2012 〕〔 Lorien Pratt and Mark Zangari: (''High Performance Decision Making'' )〕 In response, decision engineering seeks to unify a number of decision making best practices, described in more detail below. Decision engineering builds on the insight that it is possible to ''design'' the decision itself, using principles previously used for designing more tangible objects like bridges and buildings.〔(''Benefits of CMMI'' )〕 The use of a ''visual'' design language representing decisions is an important element of decision engineering, since it provides an intuitive common language readily understood by all decision participants. A visual metaphor〔(''Metaphors and the User Interface'' )〕 improves the ability to reason about complex systems〔Lorien Pratt and Mark Zangari: ( ''Leading the way to complex business models''. ) Telecom Asia, August 10, 2009.〕 as well as to enhance collaboration. In addition to visual decision design, there are other two aspects of engineering disciplines that aid mass adoption. These are: 1) the creation of a shared language of design elements and 2) the use of a common methodology or process, as illustrated in the diagram above. ==Motivation== The need for a unified methodology of decision making is driven by a number of factors that organizations face as they make difficult decisions in a complex internal and external environment. Recognition of the broad-based inability of current methods to solve decision making issues in practice comes from several sources, including government sources and industries such as telecommunications, media, the automotive industry, and pharmaceuticals. Examples: * The ''outcomes'' of decisions are becoming more complex, going well beyond next quarter's revenues or other tangible outcomes to multiple goals that must be satisfied together, some of which are often intangible: * Global increase in complexity: 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Decision engineering」の詳細全文を読む スポンサード リンク
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