Modern Quantitative Decision Making Tools and Process

     This chapter introduced operations research (OR) and some of its distinguishing characteristics. It then presented five of the main areas of concern for operations management personnel. The chapter next examined some of the modern quantitative decision-making tools and processes, most of them falling under the heading of operations research. These varied in complexity and mathematical rigor, but all are of value to managers in the decision-making process.

     Linear programming assists the manager in determining price-volume relationships for effective utilization of the organization's resources. The example used in this chapter illustrated how the technique could be employed to allocate scarce resources while simultaneously maximizing profit. The second technique discussed, the economic order quantity formula, helps the decision maker determine at what point and in what quantities inventory should be replenished. The third technique discussed game theory, is useful in providing the manager with important insights into the elements of competition. Sometimes this competition is best represented as a zero-sum game with a saddle point, but more often it is typified by a non-zero-sum game without a saddle point, in which case it is necessary to use a mixed strategy in solving the problem. A fourth quantitative technique is queuing (waiting line) theory, which employs mathematical equations in balancing waiting lines and service. When it becomes difficult to evaluate alternatives by means of equations alone, many managers turn to the Monte Carlo technique, which uses a simulation approach and provides the decision maker with an opportunity to evaluate the effect of numerous decisions within the simulated environment On the basis of simulation results, the manager is in a position to  make the decision that best attains the objective.

     Still another OR tool, and one that has been receiving increased attention in recent years, is the decision tree. This technique, which is less mathematical than those already mentioned, helps the manager weigh alternatives based on immediate and long-run results by encouraging the individual to: (a) identify the available courses of action; (b) assign Probability estimates to the events associated with these alternatives; and (c) calculate the payoffs corresponding to each act-event combination. Heuristic Programming, which was examined last, is the least mathematical of all OR techniques. Yet it is used far more often by the manager in every-day decision making (through rules of thumb and the use of trial and error) than any of the other OR tools.