should be responsive to the decision maker’s requirements at all levels of detail that are supported by the analysis.

Many decision makers do not like to be told what they should do; their job is to make decisions. The MS&A team’s job is to present the information in a way that makes choices transparent and to clarify the crucial parameters on which the choice depends (decision makers typically consider many factors other than those considered by MS&A). Simple, transparent models that allow decision makers to control input parameters and immediately observe outputs can be an effective way to develop their confidence in models. If the underlying model is very complex and time consuming to run, simplified models that capture the essence of the complex underlying model should be used.

In short, MS&A practitioners should document their activities and results in a transparent and traceable way. At all levels of presentation, all terms and assumptions should be stated explicitly, sensitive and robust features should be identified, and shortcomings and weaknesses should be discussed openly. Strategies should be identified and implemented to increase the flexibility, adaptability, and robustness of MS&A activities and results. The MS&A community should work closely with communications experts to develop and institutionalize effective techniques to communicate MS&A results.

Decision making is a highly individual and often idiosyncratic process, so it should not be surprising that a disconnect often exists between the MS&A practitioner and the decision maker. Every effort should be made to ensure that both have the same understanding of the problem, the assumptions that are necessary to model and analyze it, the alternative solutions offered, and the uncertainties associated with each. This is an area that requires technical, verbal, and presentation skills, all of which need to be adequately represented on the MS&A team.

REFERENCES

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Davis, Paul K., Jonathan Kulick, and Michael Egner. 2005. Implications of Modern Decision Science for Military Decision Support. Santa Monica, Calif.: RAND.

Gigerenzer, G., and R. Selten, eds. 2002. Bounded Rationality: The Adaptive Toolbox. Cambridge, Mass.: MIT Press.

Hammond, J.S., R.L. Keeney, and H. Raiffa. 1999. Smart Choices: A Practical Guide to Making Better Decisions. Cambridge, Mass.: Harvard Business School Press.

Kahneman, Daniel, and Amos Tversky. 2000. Choices, Values, and Frames. New York, N.Y., Cambridge, England: Cambridge University Press.

Kahneman, Daniel, Paul Slovic, and Amos Tversky. 1982. Judgment Under Uncertainty: Heuristics and Biases. New York, N.Y., Cambridge, England.: Cambridge University Press.

Keeney, Ralph. 1992. Value-Focused Thinking. Cambridge, Mass.: Harvard University Press.

Spetzler, C. 2007. “Building decision competency in organizations.” Advances in Decision Analysis: From Foundations to Applications. W. Edwards, R.F. Miles, and D. von Winterfeldt, eds. Cambridge, England: Cambridge University Press, in press.

Sterman, John D. 2000. Business Dynamics: System Thinking and Modeling for a Complex World. New York, N.Y.: McGraw-Hill.

von Winterfeld, Detlof, and Ward Edwards. 1986. Decision Analysis and Behavioral Risk. Cambridge, England: Cambridge University Press.

von Winterfeldt, Detlof, with E. Schweitzer. 1998. “An assessment of tritium supply alternatives in support of the U.S. nuclear weapons stock-pile.” Interfaces 28.



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