Demand or sales forecasting is a scientific exercise. It has to go through a number of steps. At each step, you have to make critical considerations. Such considerations are categorically listed below:
1) Nature of forecast: To begin with, you should be clear about the uses of forecast data- how it is related to forward planning and corporate planning by the firm. Depending upon its use, you have to choose the type of forecasts: short-run or long-run, active or passive, conditional or non-conditional etc.
2) Nature of product: The next important consideration is the nature of product for which you are attempting a demand forecast. You have to examine carefully whether the product is consumer goods or producer goods, perishable or durable, final or intermediate demand, new demand or replacement demand type etc. A couple of examples may illustrate the importance of this factor. The demand for intermediate goods like basic chemicals is derived from the final demand for finished goods like detergents. While forecasting the demand for basic chemicals, it becomes essential to analyze the nature of demand for detergents. Promoting sales through advertising or price competition is much less important in the case of intermediate goods compared to final goods. The elasticity of demand for intermediate goods depends on their relative importance in the price of the final product.
Time factor is a crucial determinant in demand forecasting. Perishable commodities such as fresh vegetables and fruits can be sold over a limited period of time. Here skilful demand forecasting is needed to avoid waste. If there are storage facilities, then buyers can adjust their demand according to availability, price and income. The time taken for such adjustment varies from product to product. Goods of daily necessities that are bought more frequently will lead to quicker adjustments. Whereas in case of expensive equipment which is worn out and replaced after a long period of time, adaptation of demand will be spread over a longer duration of time.
3) Determinants of demand: Once you have identified the nature of product for which you are to build a forecast, your next task is to locate clearly the determinants of demand for the product. Depending on the nature of product and nature of forecasts, different determinants will assume different degree of importance in different demand functions.
In the preceding unit, you have been exposed to a number of price-income factors or determinants-own price, related price, own income-disposable and discretionary, related income, advertisement, price expectation etc. In addition, it is important to consider socio-psychological determinants, specially demographic, sociological and psychological factors affecting demand. Without considering these factors, long-run demand forecasting is not possible.
Such factors are particularly important for long-run active forecasts. The size of population, the age-composition, the location of household unit, the sex-composition-all these exercise influence on demand in. varying degrees. If more babies are born, more will be the demand for toys; if more youngsters marry, more will be the demand for furniture; if more old people survive, more will be the demand for sticks. In the same way buyers’ psychology-his need, social status, ego, demonstration effect etc. –also effect demand. While forecasting you cannot neglect these factors.
4) Analysis of factors &determinants: Identifying the determinants alone would not do, their analysis is also important for demand forecasting. In an analysis of statistical demand function, it is customary to classify the explanatory factors into (a) trend factors, which affect demand over long-run, (b) cyclical factors whose effects on demand are periodic in nature, (c) seasonal factors, which are a little more certain compared to cyclical factors, because there is some regularly with regard to their occurrence, and (d) random factors which create disturbance because they are erratic in nature; their operation and effects are not very orderly.
An analysis of factors is specially important depending upon whether it is the aggregate demand in the economy or the industry’s demand or the company’s demand or the consumers; demand which is being predicted. Also, for a long-run demand forecast, trend factors are important; but for a short-run demand forecast, cyclical and seasonal factors are important.
5) Choice of techniques: This is a very important step. You have to choose a particular technique from among various techniques of demand forecasting. Subsequently, you will be exposed to all such techniques, statistical or otherwise. You will find that different techniques may be appropriate for forecasting demand for different products depending upon their nature. In some cases, it may be possible to use more than one technique. However, the choice of technique has to be logical and appropriate; for it is a very critical choice. Much of the accuracy and relevance of the forecast data depends accuracy required, reference period of the forecast, complexity of the relationship postulated in the demand function, available time for forecasting exercise, size of cost budget for the forecast etc.
6) Testing accuracy: This is the final step in demand forecasting. There are various methods for testing statistical accuracy in a given forecast. Some of them are simple and inexpensive, others quite complex and difficult. This stating is needed to avoid/reduce the margin of error and thereby improve its validity for practical decision-making purpose. Subsequently you will be exposed briefly to some of these methods and their uses.
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