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FRAMEWORK FOR DECISION-MAKING An analytical and scientific framework for decision implies the following systematic steps Defining the problem. Establish the decision criteria. Formulation of

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FRAMEWORK FOR DECISION-MAKING An analytical and scientific framework for decision implies the following systematic steps Defining the problem. Establish the decision criteria. Formulation of a model. Generating alternatives. Evaluation of the alternatives. Implementation and monitoring. DEFINING THE PROBLEM Defining the problem enables to identify the relevant variables and the cause of the problem. Careful definition of the problem is crucial. Finding the root cause of a problem needs some questioning and detective work. If a problem defined is too narrow, relevant variable may be omitted. If it is broader, many tangible aspects may be included which leads to the complex relationships. ESTABLISH THE DECISION CRITERIA Establish the decision criterion is important because the criterion reflects the goals and purpose of the work efforts. For many years profits served as a convenient and accepted goal for many organisations based on economic theory. Nowadays organisation will have multiple goals such as employee welfare, high productivity, stability, market share, growth, industrial leadership and other social objectives. FORMULATION OF A MODEL Formulation of a model lies at the heart of the scientific decision-making process. Model describes the essence of a problem or relationship by abstracting relevant variables from the real world situation. Models are used to simplify or approximate reality, so the relationships can be expressed in tangible form and studied in isolation. Modeling a decision situation usually requires both formulating a model and collecting the relevant data to use in the model. Mathematical and statistical models are most useful models for understanding the complex business of the problem. Mathematical models can incorporate factor that cannot readily be visualized. With the aid of computers and simulation techniques, these quantitative models reflexible. GENERATING ALTERNATIVES Alternatives are generated by varying the values of the parameters. Mathematical and statistical models are particularly suitable for generating alternatives because they can be easily modified. The model builder can experiment with a model by substituting different values for controllable and EVALUATION OF THE ALTERNATIVES Evaluation of the alternatives is relatively objective in an analytical decision process because the criteria for evaluating the alternatives have been precisely defined. The best alternative is the one that most closely satisfies the criteria. Some models like LPP model automatically seek out a maximizing or minimizing solution. In problems various heuristic and statistical techniques can be used to suggest the best course of action. IMPLEMENTATION AND MONITORING Implementation and monitoring are essential for completing the managerial action. The best course of action or the solution to a problem determined through a model is implemented in the business world. Other managers have to be convinced of the merit of the solution. Then the follow-up procedures are required to ensure about appropriate action taken. This includes an analysis and evaluation of DECISION METHODOLOGY The kind and amount of information available helps to determine which analytical methods are most appropriate for modeling a given decision. Figure 2.2 illustrates some useful quantitative methods that are classified

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