The Statistical Value Chain - a Benchmarking Checklist for Decision Makers to Evaluate Decision Support Seen from a Statistical Point-Of-View

Ivan Tengbjerg Herrmann, Geraldine Henningsen, Christian D. Wood, James I. R. Blake, Jørgen Birk Mortensen, Henrik Spliid

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Abstract

When decisions are made, by decision makers (DMs) in private and public organizations the DMs are supported by analysts (ANs) who provide decision support to the DM. Therefore, the quality of decision support provided by the AN directly affects the quality of a DM’s decision. At present, many quantitative methods exist for evaluating uncertainty—for example, Monte Carlo simulation—and such methods work very well when the AN is in full control of the data collection and model-building processes. In many cases, however, the AN is not in control of these processes. In this article we develop a simple method that a DM can employ in order to evaluate the process of decision support from a statistical point-of-view. We call this approach the “Statistical Value Chain” (SVC): a consecutive benchmarking checklist with eight steps that can be used to evaluate decision support seen from a statistical point-of-view.
Original languageEnglish
JournalInternational Journal of Decision Sciences
Volume4
Issue number2
Pages (from-to)71-83
ISSN2229-5879
Publication statusPublished - 2013

Keywords

  • Statistical Value Chain
  • Decision Theory
  • Benchmarking Checklist
  • Decision Makers
  • Evaluate
  • Decision Support
  • Statistics
  • Data Analysis
  • Uncertainty
  • Quality

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