Updated 11/18

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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:

  • The information  is uncertain

  • Team members each have different interpretations of the available information

  • Each think different things are important

  • It is not clear what to do next to reach a decision

  • Risks with each option are unclear

  • The team must manage alternative and criteria evolution

  • 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.