3. Identify the variables affecting the demand for the product and express them in appropriate form.
4. Gather relevant data and approximations to relevant data to represent the variables.
5. Through the use of the statistical techniques determine the most probable relationship between the dependent and the independent variables.
6. Prepare the forecast and interpret the results. Interpretation is more important to the management.
7. For forecasting the company’s share in the demand, two different assumptions can be made :
(a) The ratio of the company sales to the total industry’s sales will continue as in the past.
(b) On the basis of an analysis of likely competition and industry trends the company may assume a market share different from that of the past.
As forecasts are based on certain assumptions they must be revised when improved information is available.
In long term forecasts, the projections may be revised yearly. These are sometimes also known as rolling forecasts.
8. Forecasts may be made cither in terms of physical units or in term of rupees of sales volumes.
9. Forecasts may be made in terms of product groups and then broken for individual products on the basis of past percentages.
These product groups may be divided into individual products in terms of size, brands, labels, colours etc.
10. Forecasts may be made on annual basis and then divided month-wise or week-wise on the basis of past records.
11 For determining the month-wise break-up of the forecast sales of a new product, either (i) use may be made of other firm’s data if available or (ii) some survey may be necessary.