QUANTITATIVE TECHNIQUES FOR DECISION MAKING

Decision making basically is problem solving. The increasing complexity of organization problem requires the discovering and applying of improved quantitative techniques/tools for the evaluation of decision alternatives. Every alternative solution has favorable as well as unfavorable consequences, which should be analyzed and compared against one another or against a decision criteria such as desired rate of return, sales volume, etc. A number of quantitative techniques have been developed to help the decision-maker in evaluating alternatives. The most commonly used quantitative techniques are discussed below:

(1) Operation Research

Operation research is the application of scientific or mathematical methods to the analysis and evaluation of alternative solution to a problem situation. It consists of bringing together available data on a specific problem, processing these data, and obtaining quantitative report of various potential courses of action. Mathematical models are then constructed. An operations research model is a simplified representation of a problem, incorporating only its crucial elements. Hence, decision-maker obtains data in choosing the solutions which best satisfies the goals.

(2)Payoff Matrix

A payoff matrix is a statistical tool of decision making. It provides a method of computing outcomes of alternatives available to decision-maker. A payoff matrix depicts the probable value of each of the decision alternatives and the probabilities of their occurrence. A probability is the degree of likelihood that a particular event will occur. Probabilities range in value from 0(Zero-no chance of occurrence) to 1.00(certain occurrence).

(3)Decision Tree

A decision tree is a graphic representation of the sequential decisions and events that constitute decision making. The graphical model consists of tree like structure with branches to represent the possible event combinations. Relative values for the predicted outcomes of each decision are evaluated and taken into account. The outcomes that has the highest desirable end value is the course to follows. From a decision point the decision tree links a number of possible actions and possible events by means of straight lines.

(4) Simulation

Simulation is the process of experimentation with a model of same real system or situation in order to gain understanding or solve a problem in the real world. A simulation model is usually applied to evaluate alternative actions and determine which action probably would be most effective in the real situation. It has been used for analyzing the effects of organizational change, waiting line problems, job-shop scheduling and model changes in assembly line operations.