Demand Forecasting

DEMAND FORECASTING

Demand forecasting is an estimate of sales during a specified future period which is tied to a proposed marketing plan and which assumes a particular set of uncontrollable and competitive forces. Therefore, demand forecasting is a projection of firm’s expected level of sales based on a chosen marketing plan and environment. Demand Forecasting is an estimate of future demand. A forecast can be determined by mathematical means using historical, it can be created subjectively by using estimates from informal sources, or it can represent a combination of both techniques.

Why Forecast is important to plan for the future by reducing uncertainty, to anticipate and manage change, to increase communication and integration of planning teams, to anticipate inventory and capacity demands and manage lead times, to project costs of operations into budgeting processes, to improve competitiveness and productivity through decreased costs and improved delivery and responsiveness to customer needs (Banker, S. (2013).

Criteria of a Good Forecasting Method: There are a good many ways to make a guess about future sales. They show contrast in cost, flexibility and the adequate skills and sophistication. Therefore, there is a problem of choosing the best method for a particular demand situation. There are certain economic criteria of broader applicability. They are Accuracy-The forecast obtained must be accurate. How is an accurate forecast possible? To obtain an accurate forecast, it is essential to check the accuracy of past forecasts against present performance and of present forecasts against future performance. Accuracy cannot be tested by precise measurement but buy judgment. Plausibility: The executive should have good understanding of the technique chosen and they should have confidence in the techniques used. Understanding is also needed for a proper interpretation of results. Plausibility requirements can often improve the accuracy of results. Availability-Immediate availability of data is a vital requirement and the search for reasonable approximations to relevance in late data is a constant strain on the forecasters patience. The techniques employed should be able to produce meaningful results quickly. Delay in result will adversely affect the managerial decisions. Simplicity-Statistical and econometric models are certainly useful but they are intolerably complex. To those executives who have a fear of mathematics, these methods would appear to be Latin or Greek. The procedure should, therefore, be simple and easy so that the management may appreciate and understand why it has been adopted by the forecaster Consistency-The forecaster has to deal with various components which are independent. If he does not make an adjustment in one component to bring it in line with a forecast of another, he would achieve a whole which would appear consistent (Barnett, W. (1988).