Engineers, analysts in planning offices and government agencies, project management consultants, manufacturing process planners, financial and economic analysts, experts supporting medical/technological diagnosis, and so on and so forth use decision analysts to provide quantitative support to decision-makers in a variety of fields.

The decision-maker and the model-builder, referred to as the analyst, are two different people involved in decision-making modeling. The analyst’s job is to help the decision-maker make a choice. As a result, the analyst must have more a set of analytical methods.

Manager may not comprehend this model and, as a result, will either use it mindlessly or reject it outright. The management may believe that the specialist is too stupid and unsophisticated to understand the model, while the specialist may believe that the manager lives in a fantasy world of unrealistic assumptions and irrelevant mathematical language.

Decision Analysis can be used to develop an optimal strategy for decision making especially when faced with various options or alternatives with uncertain or risky pattern of future events. When a careful decision analysis has been carried out, the uncertain future events make the final consequences uncertain. The risk associated with any decision alternative is a direct result of the uncertainty associated with the final consequence. Good decision analysis includes risk analysis that provides probability information about the favorable as well as the unfavorable consequences that may occur.

A decision problem is characterized by decision alternatives, states of nature, and resulting payoffs. The decision alternatives are the different possible strategies the decision maker can employ. The states of nature refer to future events, not under the control of the decision maker, which may occur. States of nature should be defined so that they are mutually exclusive and collectively exhaustive.

The consequence resulting from a specific combination of a decision alternative and a state of nature is a payoff. A table showing payoffs for all combinations of decision alternatives and states of nature is a payoff table. Payoffs can be expressed in terms of profit, cost, time, distance or any other appropriate measure.

Three commonly used criteria for decision making when probability information regarding the likelihood of the states of nature is unavailable are:

- The optimistic approach.
- The conservative approach.
- The minimax regret approach.

The Optimistic Approach is also called the Maximax rule. The optimistic decision maker chooses the largest single value in the payoff table that gives him maximum contribution in terms of profit maximization or least cost in terms of cost minimization decision.

The Conservative Approach. This approach is also called maximin approach. The decision maker is concerned with maximizing the minimum of all the alternatives he has. He is a risk averse. He likes to minimize his risk to the barest minimum.

The Minimax Regret Approach. This approach will determine the regrets (losses) in each state of nature, then will choose the maximum of all the regrets, then finally chooses the minimum of the maximum regrets chosen. I see this as an advance form of conservative approach. It helps to reduce uncertainties in the decision-making process.

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