DAVID G. ULLMAN
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.