BoundedRationality_TheAdaptiveToolbox.pdf

7
The Fiction of Optimization
Gary Klein
Klein Associates Inc., 1750 Commerce Center Blvd. North,
Fairborn, OH 45324, U.S.A.
ABSTRACT
One of the definitions of optimizing a decision choice is to be able to maximize expected
utility. Several analytical procedures have been developed to help people pursue this
goal, even though researchers and practitioners realize that in field settings, it will not be
possible to maximize expected utility. This chapter lists a number of barriers to selecting
an optimal course of action and further asserts that optimization should not be used as a
gold standard for decision making. An alternative approach, based on the strategies of
chess grandmasters, is proposed as a substitute.
INTRODUCTION
Optimization refers to the attempt to find the best option out of a set of potential
courses of action. Simon (1955, 1972) contrasted optimization with satisficing.
He defined optimization as the selection of best choice, the one with the highest
expected utility. (A more technically accurate term would be "maximizing," as
in maximizing expected utility, rather than "optimizing.") Unfortunately, according
to Simon, the computational requirements for optimizing are usually
too high for decision makers. Therefore, people will satisfice, which means selecting
the first course of action that appears to be successful, even if it is not the
best. Satisficing is a heuristic that allows decision makers to overcome their limited
information-processing capacities.
The concept of optimization relies on a number of assumptions. These assumptions
are very restrictive. I have not identified any decision researcher or
analyst who believes that these assumptions will be met in any setting, with the
possible exception of the laboratory or the casino. In the majority of field set
tings, there is no way to determine if a decision choice is optimal owing to time
pressure, uncertainty, ill-defined goals, and so forth. Some of these problems