DAVID G. ULLMAN
Robust Decisions
A Robust Decision is the best possible choicee; one found by eliminating all the uncertainty possible within available resources, and then choosing with known and acceptable levels of satisfaction and risk.
Robust Decision-Making techniques are designed to to support decision-making teams when:
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The information is uncertain
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Team members each have different interpretations of the available information
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Each think different things are important
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It is not clear what to do next to reach a decision
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Risks with each option are unclear
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The team must manage alternative and criteria evolution
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They must get buy-in on any decision we make
The Robust Decision approach is based on a wide variety of sources ranging from the writings of Benjamin Franklin to those of Genichi Taguchi; on mathematical methods such as Multi-Attribute Utility Theory, Bayesian Probabilities, and simple Pro-Con lists; and on research from psychology, engineering, artificial intelligence, and sociology.
To read more about this approach see Making Robust Decisions.
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