7 main Techniques of Decision-making

Decision taken must be accurate and should not lead to confusion; the decisions taken must also be scientific and available for accuracy and verification. The important techniques that aid the manager in decision making are operations research and other quantitative techniques.

1. Operations Research:

Definition:”Operations Research is the application of methods of science to complex problems arising in the direction and management of large system of men, machines, materials and money in industry, business, government and defense”.

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Robert Thierauf:

“Operations Research utilized the planned approach and an interdisciplinary team in order to represent functional relationships as mathematical models for the purpose of providing a quantitative basis for decision making and uncovering new problems for quantitative analysis”.

Operations Research helps the decision maker to make objective decisions. OR does this by providing factual basis to guide and support judgment, easing the burden of effort and time on the executive.

Operations Research is a particular way of viewing the problem, team, task force and mathematical reasoning to the alternatives meant for solving them. The common approach in any operations research is the construction and study of a mathematical model.

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Some of the managerial problems usually subjected to operations research analysis include production scheduling, inventory control, sales policies, expansion of plant etc.

Management accountant holds key for the ultimate success or failure of operations research. The quality of decision making will improve with the application of mathematical model but the feasibility of a mathematical model application will depend on the adequacy and accuracy of accounting information. (More details on OR at the later pages of this chapter).

2. Models:

Model building is the central concept in the application of OR while making use of quantifying models. Models are simple convenient and relatively economic resource conservation device for testing hypothesis.

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Mathematical models help the optimization concept in decision making. This is very important in the calculation and choice of best possible alternative solutions for a given problem.

3. Simulation:

This technique is used to test the feasibility and possible outcome of various decision alternatives. “Simulation is a quantitative technique for evaluating alternative courses of action based upon facts and assumptions with a computerized mathematical model in order to represent actual decision making under conditions of uncertainty.

4. Linear Programming:

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This is defined as “How could a company with limited resources make optimum use with their resources, combination for the achievement of the desired objective, or goal was, the central idea of this mathematical technique”.

A linear or straight line relationship exists between variables and that the limits of variation can be determined. It adopts an analytical instead of intuitive approach in decision making. It is also concerned with problem of planning. A group of complex independent activities are expressed by means of developing mathematical formula.

5. Games Theory:

Games theory attempts to work out optimum solution in which an individual in a given situation can develop a strategy irrespective of what a competition does with maximizing gains or minimizing losses. It involves mathematical study of tactics under conditions of uncertainty.

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6. PERT and CPM:

Programme Evaluation and Review Technique is useful to analyze and control the timing aspects of programmes. In planning and controlling a programme, PERT helps in obtaining lower costs and reducing programme time, bringing about better utilization of human and physical resources.

Critical Path Method (CPM) is a commonly used term for all network analysis and for a particular version of these techniques.

PERT relies on three estimates, an optimistic, most likely and pessimistic of the time each activity may take. CPM relies only one ‘most likely’.

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7. Probability Theory Analysis:

Probability refers to a chance that a particular event will occur. The events must be random and be effected by chance and not by design. The probability of success is defined as the number of successful outcomes divided by the total number of outcomes. It cannot be denied that some element of probability does exist in all decision making.