U. S. DOE Office of Field Management' , " roject Management Prioritization Guide"
(reference [p]) and its referenced RBP approaches.
Presidential Commission' , " isk Assessment and Risk Management in Regulatory
Decision Making"(reference [m]).
National Academy of Science' , " cience and Judgment in Risk Assessment"
National Research Council' , " nderstanding Risk: Informing Decisions in a
Democratic Society"(reference [f]).
National Research Council' , " uilding Consensus Through Risk Assessment and
U. S. DOE Office of Environmental Management' , " isks and the Risk Debate:
Searching for Common Ground"(Reference [s]).
These documents were reviewed to extract useful RBP insights, but only to the extent that
these insights were not contrary to the concepts in the higher-tier documents.
4.2 Decision Structuring. Formulating decision options is sometimes a difficult challenge.
The formulation of decision alternatives needs to be prepared and reviewed with
considerable care (1) to eliminate biases and gaming, (2) to ensure that all the
infrastructure implications and concomitant effects of the alternatives are appropriately
factored in, and (3) to verify that the alternatives are amenable to treatment with the
proposed prioritization model, e.g., to eliminate interdependencies that the model may not
be equipped to account for.
Decision makers tend to take a negative view of prefabricated decisions that preempt the
use of their judgment and management skills. Similarly, interested parties tend to resent
decision processes that hide their priorities in an opaque analysis, even if the analysis has
done a technically sound job of capturing their values. Therefore, probably the most
important initial steps in RBP may be the proper up-front structuring and formulation of the
problem and decision to be made, the decision objectives or goals to be reached, and the
alternatives or options for reaching these goals. These initial steps may also be the most
difficult steps to do well, given the existence of multiple (and sometimes competing)
decision objectives, the need to make credible decisions despite potential uncertainties, and
the need to accomplish goals with finite resources.
Applications of RBP tend to be most successful when they are seen to illuminate and not
prejudge decisions developed in close collaboration with the decision maker or requestor of
4.3 Use of Multi-Attribute Utility Theory (MAUT). MAUT is a flexible, quantitative-based
decision analysis technique and management tool for clearly documenting the advantages
and disadvantages of policy choices in a structured framework. It merits special
consideration because it provides rigorous, sound, and demonstrated ways to combine
quantitatively dissimilar measures of costs, risks, and benefits, along with decision maker
preferences, into high-level, aggregated measures that can be used to evaluate
alternatives. Goals of MAUT are to provide a defensible framework for identifying,
organizing, and displaying information needed to support complex policy issues and/or
technical decisions; deriving the logical implications of such information; and providing
insights and recommendations for decision making. MAUT allows full aggregation of
performance measures into one single measure of value that can be used for ranking
alternatives. MAUT techniques can provide a mechanism to facilitate constructive
discussion and mediate potential conflict.