Games and Decisions
Decision makers do not always operate in decision environments that are certain. While this is true for most organizations in the private sector, it can also apply to public organizations where decisions are not always made with perfect knowledge. Perfect knowledge is a condition where all the information necessary to make a decision is known with certainty. Unfortunately, there is hardly a situation in the real world where one has all the information necessary or available to work with. As a result, decisions are often made with a certain degree of uncertainty. Theoretically one could think of information availability as a situation on a continuum between two extremes, complete certainty and complete uncertainty. Most decisions are made with information that lies somewhere in between.
With a few notable exceptions, much of our discussion in the previous chapters concentrated on methods that were deterministic in nature, meaning that all the information necessary to solve a problem was known with certainty. In this chapter we present several methods and techniques that are specifically designed to deal with conditions that are uncertain. Three types of uncertainty conditions are discussed in the chapter: risk or partial uncertainty, complete uncertainty, and conflict.
Decision makers in government are not necessarily risk takers, but there are situations where a decision has to be made under conditions of risk. A risk can be defined as a situation (event) where one does not have complete information to make a decision, but where it is possible to estimate the outcome (result of an event) with some degree of uncertainty or probability. Probability and uncertainty, therefore, go hand in hand. As long as there is an element of uncertainty in any decision making, the outcome will always be uncertain, i.e., probabilistic. Probability thus becomes an integral part of all three conditions of uncertainty: risk, complete uncertainty, and conflict.