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Programmability of Decision Making

A usual reference in studies and textbooks related to decision making, the programmability of a decision problem, also referred to as the structure of a decision problem, is concerned with the extent to which managers facing decisions have a complete understanding of the factors that have a bearing on the situations they faced. The concept is associated with Herbert Simon, a leading writer in management science and 1978 Nobel laureate in economics for his pioneering research into the decision-making process within economic organizations. It was Simon who first reflected on the degree of structure of decision situations. As Simon’s thoughts gradually turned toward the power of computers and the potential of artificial intelligence (a field that he contributed to establishing), he introduced the oft-quoted distinction between programmed decision and nonprogrammed decision. Simon’s reflection was guided by the idea that organizations, like computers, are systems designed for “complex information processing.” Thus, programmed decisions can be coded in computer programs or other programs that are computerizable, while nonprogrammed decisions must be treated as “problem solving” and therefore are not amenable to processing by computer systems to any extent. This entry considers the richness of the concept of programmability of decisions and its implications for research and practice in a number of areas.

Fundamentals

Simon’s basic scientific progress must be viewed in terms of his attempt to study the manager as a decision maker. In seeking to theorize about managerial decision making, Simon initially discussed the difference between facts and values. Facts can be verified or falsified, whereas values are the objectives of the decision maker and, beyond this, his or her actual wishes. This is important for both research and practice because it indicates that decisions made by managers can be evaluated properly only when the objectives of the decision maker are known. Thus, to evaluate the quality of a decision, researchers must know the utility of the decision maker and understand his or her preferences and expectations in terms of the probabilities of future events. These factors are directly related to the degree to which a decision problem can or cannot be programmed.

Simon also observed that the problems that managers faced and that are found to trigger decision-making processes are not facts but constructs: They do not present themselves “carefully wrapped in bundles.” There are basic uncertainties relating to the cause-and-effect relationship between the key factors in the analysis of these problems as well as in their solution. Second, Simon observed that decision “is a matter of compromise”; that is, all decision makers have several more or less contradictory objectives in mind.

James D. Thompson and A. Tuden have formalized this issue in their influential model that classified uncertainty in decision making based on how well managers understand how the world works on the one hand and on whether managers agree among themselves about the objectives they pursue on the other hand. They presented their model as a two-by-two matrix, where both above dimensions—ambiguity of objectives and uncertainty of cause and effect—can be either high or low, thereby distinguishing between decisions by computation (most certain), decisions by judgment, decisions by compromise, and decisions by inspiration (least certain).

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