Business economists have developed many forecasting techniques to help managers in handling the increasing complexity in management decision making. As a matter of fact, it is a tricky and experimental process. No method of forecasting is complete in itself which may be applied to all enterprises, all products and in all circumstances. in many cases the decisions are based on a combination of several, if not all, forecasting techniques. Broadly speaking, the use of a particular forecasting method depend upon the nature of the enterprise, the products manufactured, information system in use etc.
Forecasts may be derived by means of sophisticated analysis or they may be the result of intuition. Business organizations commonly use five approaches for sales forecasting
A. Subjective Approach
(i) Expert opinion or Judgemental approach,
(ii) Survey of buyer’s intention.
B. Statistical Methods
(i) Extension of past history,
(ii) Association with other events. Each of these techniques has a special use, and the more you understand the better are the chances that your forecasting efforts will be successful.
1. Opinion or Judgemental Forecasts: It is one of the most widely used and influential forecasting technique where the opinions and intuition of management is utilized. The process brings together in an organized manner, personal judgements about the process being analyzed. Main reliance is on human judgement. In this method, the executive uses his own anticipation and what he hears from others. Outside experts are also consulted and the other executive heads are also required to give their opinion in the mailer. Salesmen are to provide information about customer’s attitude and preferences and the activities of competitors. Thus all possible information from the opinions of various persons is combined together to change the subjective opinions into quantitative forecasts. No doubt experts and experienced managers can be useful as guides and serve as reliable source of information, but one has to make his own decision from all the opinions. Thus in this method broad guess is made by the executive in-charge of a business. There are many advantages and disadvantages of opinion technique of forecasting
Advantages of Forecasting Demand
(i) simple and easy to understand,
(ii) no specialized skill is required i.e. less mathematical sophistication.
(iii) low cost,
(iv) is based on the information or opinion of the persons who are directly involved in the system,
(v) can be used when satisfactory date is not available.
Disadvantages of Forecasting Demand
(i) opinion and intuitions are highly subjective,
(ii) personal estimates are likely to be biased,
(iii) time required to take the decision may be more,
(iv) results can be easily distorted,
(v) lacks scientific validity,
(vi) is not based on valid facts,
(vii) the method is not useful for long term planning. The method can be useful for many new products or new service estimator Where sufficient past experience is not available.
2. Consumer’s Opinion Surveys : This is a straight-forward method to make short-term demand forecasts. The consumers are directly contacted by the investigators and their preferences and attitude towards the product as well as future requirements are ascertained. This information is then used to project the sales for future. This method is appropriate when the consumers of the product are industrial producers, purchasing the item in large quantifies. This method is not suitable to make long-term forecasts for the consumer or household products, which are affected by change of attitudes and fashions.
3. Extensions of Past History : Basically all statistical approaches of forecasting project historical information into the future. These are based on the assumption that future.patterns tend to be extensions of past ones and that one can make useful predictions by studying the past behavior i.e. the factors which were responsible in the past will also be operative to the same extent in future. Some companies have detailed sales record for each item as well as territory-wise. These sales record can be utilized to make useful predictions. The information should be complete with respect to events, policies, quality of the product etc. from period to period. Such information in general is known as Time series data. The time series for any phenomenon is composed of three components (i) Trend (ii) Seasonal variation and (iii) Random fluctuations.
Trend exhibits the general tendency of the data and is known as long period or secular trend. This can be either upward or downward, depending on the behavior. Seasonal components give information about the seasonal or cyclical behavior of the phenomenon. These are repetitive in nature. Random variations are chance variations and cannot be used for forecasting.