# Decision analysis

Decision analysis (DA) is the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision, for prescribing a recommended course of action by applying the maximum expected utility action axiom to a well-formed representation of the decision, and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker and other stakeholders.

## History and methodology

Graphical representation of decision analysis problems commonly use influence diagrams and decision trees. Such tools are used to represent the alternatives available to the decision maker, the uncertainty they involve, and evaluation measures representing how well objectives would be achieved in the final outcome. Uncertainties are represented through probabilities. The decision maker's attitude to risk is represented by utility functions and their attitude to trade-offs between conflicting objectives can be expressed using multi-attribute value functions or multi-attribute utility functions (if there is risk involved). In some cases, utility functions can be replaced by the probability of achieving uncertain aspiration levels. Decision analysis advocates choosing that decision whose consequences have the maximum expected utility (or which maximize the probability of achieving the uncertain aspiration level). Such decision analytic methods are used in a wide variety of fields, including business (planning, marketing, and negotiation), environmental remediation, health care research and management, energy exploration, litigation and dispute resolution, etc.

Decision analysis is used by major corporations to make multibillion-dollar capital investments. In 2010, Chevron won the Decision Analysis Society Practice Award for its use of decision analysis in all major decisions. In a video detailing Chevron's use of decision analysis, Chevron Vice Chairman George Kirkland notes that "decision analysis is a part of how Chevron does business for a simple, but powerful, reason: it works."

## Controversy

Decision analysis, a prescriptive approach, especially concerned with quantitatively dealing with uncertainties (prescriptive decision-making researches how optimal decisions could be made, while descriptive decision-making targets to explain how people actually make decisions, regardless of decision quality), is found to be in fact rarely used in the decision-making of individuals.[1] The hiatus between prescriptive decision analysis and descriptive approaches is greater in high-stakes decisions, made under time pressure.[2] Decision analysts argue that it is not their aim to study the flaws in the way people actually make decisions.[3] Studies have demonstrated the utility of decision analysis in creating decision-making algorithms that are superior to "unaided intuition".[4][5]

Critics cite the phenomenon of paralysis by analysis as one possible consequence of over-reliance on decision analysis in organizations (the expense of decision analysis is in itself a factor in the analysis). Strategies are available to reduce such risk.[6]

The term "decision analytic" has often been reserved for decisions that do not appear to lend themselves to mathematical optimization methods. Methods like applied information economics, however, attempt to apply more rigorous quantitative methods even to these types of decisions.

## References

1. Klein G (2003). The Power of Intuition. New York: Doubleday. ISBN 0-385-50289-3.
2. Klein G (1999). Sources of Power. Boston, MA: MIT Press. ISBN 0-262-11227-2.
3. Keeney R (2002). Value Focused Thinking: A Path to Creative Decisionmaking. ISBN 0-674-93197-1.
4. Robyn M. Dawes & Bernard Corrigan (1974). "Linear Models in Decision Making". Psychological Bulletin. 81 (2): 93–106. doi:10.1037/h0037613.
5. B. Fischhoff; L. D. Phillips & S. Lichtenstein (1982). "Calibration of Probabilities: The State of the Art to 1980". In D. Kahneman & A. Tversky. Judgement under Uncertainty: Heuristics and Biases. Cambridge University Press.
6. Kane, Becky (8 July 2015). "The Science of Analysis Paralysis: How Overthinking Kills Your Productivity & What You Can Do About It". Todoist Blog. Retrieved 14 May 2016.

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