Working Paper Alfred P. Sloan School of Management Decomposition and the Control of Errors in Decision Analytic Models* Decomposition and the Control of Errors in Decision Analytic Models* Decomposition and the Control of Errors in Decision Analytic Models*

Decision analytic models rely upon the general principle of problem decomposition: Large and complex decision problems are reduced to a set of relatively simple judgments. The component judgments are then combined using mathematical rules derived from normative theory. This paper discusses the value of decomposition as a procedure for improving the consistency of decision making. Various definitions of error and consistency are discussed. Linear decomposition models are argued to be particularly useful for the control of random response errors in the component judgments. Implications for decision analysis research and practice are considered, and decision makers' evaluations of the costs and benefits of decision analysis are discussed.