Now the salient characteristic of the decision tools employed in management science is that they have to be capable of actually making or recommending decisions, taking as their inputs the kinds of empirical data that are available in the real world, and performing only such computations as can reasonably be performed by existing desk calculators or, a little later electronic computers. For these domains, idealized models of optimizing entrepreneurs, equipped with complete certainty about the world - or, a worst, having full probability distributions for uncertain events - are of little use. Models have to be fashioned with an eye to practical computability, no matter how severe the approximations and simplifications that are thereby imposed on them... The first is to retain optimization, but to simplify sufficiently so that the optimum (in the simplified world!) is computable. The second is to construct satisficing models that provide good enough decisions with reasonable costs of computation. By giving up optimization, a richer set of properties of the real world can be retained in the models... Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science.

It is impossible for the behavior of a single, isolated individual to reach a high degree of rationality. The number of alternatives he must explore is so great, the information he would need to evaluate them so vast that even an approximation to objective rationality is hard to conceive. Individual choice takes place in rationality is hard to conceive... Actual behavior falls short in at least three ways, of objective rationality:

Global rationality, the rationality of neoclassical theory, assumes that the decision maker has a comprehensive, consistent utility function, knows all the alternatives that are available for choice, can compute the expected value of utility associated with each alternative, and chooses the alternative that maximizes expected utility. Bounded rationality, a rationality that is consistent with our knowledge of actual human choice behavior, assumes that the decision maker must search for alternatives, has egregiously incomplete and inaccurate knowledge about the consequences of actions, and chooses actions that are expected to be satisfactory (attain targets while satisfying constraints).

A number of proposals have been advanced in recent years for the development of ‘general systems theory’ which, abstracting from properties peculiar to physical, biological, or social systems, would be applicable to all of them. We might well feel that, while the goal is laudable, systems of such diverse kinds could hardly be expected to have any nontrivial properties in common. Metaphor and analogy can be helpful, or they can be misleading. All depends on whether the similarities the metaphor captures are significant or superficial.
It may not be entirely vain, however, to search for common properties among diverse kinds of complex systems... The ideas of feedback and information provide a frame of reference for viewing a wide range of situations, just as do the ideas of evolution, of relativism, of axiomatic method, and of operationalism... hierarchic systems have some common properties that are independent of their specific content...

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Decision theory can be pursued not only for the purposes of building foundations for political economy, or of understanding and explaining phenomena that are in themselves intrinsically interesting, but also for the purpose of offering direct advice to business and governmental decision makers. For reasons not clear to me, this territory was very sparsely settled prior to World War II. Such inhabitants as it had were mainly industrial engineers, students of public administration, and specialists in business functions, none of whom especially identified themselves with the economic sciences. Prominent pioneers included the mathematician, Charles Babbage, inventor of the digital computer, the engineer, Frederick Taylor and the administrator, Henri Fayol.
During World War II, this territory, almost abandoned, was rediscovered by scientists, mathematicians, and statisticians concerned with military management and logistics, and was renamed “operations research” or “operations analysis.” So remote were the operations researchers from the social science community that economists wishing to enter the territory had to establish their own colony, which they called “management science”.

Since my world picture approximates reality only crudely, I cannot aspire to optimize anything; at most, I can aim at satisficing. Searching for the best can only dissipate scarce cognitive resources; the best is the enemy of the good. (p.361)

The first task of administrative theory is to develop a set of concepts that will permit the description, in terms relevant to the theory, of administrative situations. These concepts, to be scientifically useful, must be operational; that is, their meanings must correspond to empirically observable facts or situations.

The fact that goals may be dependent for their force on other more distant ends leads to the arrangement of these goals in a hierarchy - each level to be considered as an end relative to the levels below it and as a mean to the levels above it.

Administration is not unlike play-acting. The task of the good actor is to know and play his role, although different roles may differ greatly in content. The effectiveness of the performance will depend on the effectiveness of the play and the effectiveness with which it is played. The effectiveness of the administrative process will vary with the effectiveness of the organization and the effectiveness with which its members play their parts.