Journal article
The Statistical Value Chain - a Benchmarking Checklist for Decision Makers to Evaluate Decision Support Seen from a Statistical Point-Of-View
Department of Management Engineering, Technical University of Denmark1
Systems Analysis, Department of Management Engineering, Technical University of Denmark2
DTU Climate Centre, Systems Analysis, Department of Management Engineering, Technical University of Denmark3
Energy Systems Analysis, Systems Analysis, Department of Management Engineering, Technical University of Denmark4
University of Southampton5
University of Copenhagen6
Department of Applied Mathematics and Computer Science, Technical University of Denmark7
Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark8
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.
Language: | English |
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Year: | 2013 |
Pages: | 71-83 |
ISSN: | 22295879 |
Types: | Journal article |
ORCIDs: | Henningsen, Geraldine |