Forecasting Methods

There are a number of techniques through which forecasts can be made. No technique can universally apply in similar business situations. These techniques, singly or in combination, are used depending upon the business situations when they have to be used.

The techniques of forecasting generally fall into two categories:

1. Quantitative Forecasting:

It applies mathematical models to past and present information to predict future outcomes. These techniques are used to have access to hard or quantifiable data. Some of the quantitative techniques are time series analysis, regression models and econometric models.

2. Qualitative Forecasting:

It applies when data are not available or very little data are available. Managers use judgement, intuition, knowledge and skill to make effective forecasts. Some of the qualitative techniques are jury of executive opinion method, sales force composite method and users’ expectation method.

These techniques are used for:

1. External environmental forecasting and 
2. Internal environmental forecasting

External Environmental Forecasting:

No firm, large or small, over a period of time, remains in a static condition. It experiences upward or downward swing. Robert C. Turner, an economist, states, “Business forecasting is unavoidable. Every business decision involves a forecast, implicit or explicit, because every business decision pertains to the future. Although business decision makers should neither accept any forecast as infallible nor rely exclusively on it, they would be well advised to give forecasts a significant weight in their own planning.”

Forecasts related to external environment are:

1. Economic forecasting,
2. Technological forecasting,
3. Forecasting regarding Government policies, and 
4. Sales forecasting.

Choice of Forecasting Methods:

In practice, no single technique of forecast can apply to make predictions. A combination of different techniques is followed by the forecasters, where positive attributes of all the techniques are unified into a single forecast.

In a joint opinion method to make forecasts, all those concerned with the problem area jointly make judgments and forecasts are made through consensus of opinion. The best forecasting technique is a blend of statistical and industry/group/ industry judgment.

1. Accurate:

The forecast method should be accurate in terms of predicting results. No method can, however, be 100 per cent accurate. A range of deviations is, therefore, accepted by the forecasters. A range of 5 to 10 per cent is usually accepted by forecasters depending upon the nature of product, market, industry and the forecast.

2. Flexible:

Forecasting method should be flexible. It should change according to changing environmental conditions. Deviations in actual implementation become the basis of adopting another method of forecasting to make predictions.

3. Efficient:

Every forecasting method has benefits and costs. Forecasts should adopt a method whose benefits are more than the costs to achieve optimum results.

4. Timeliness:

Forecasts should provide timely information of future behaviour of consumers, sales and industry trends. If forecasts exceed the time for actual sales in the market, they will become inefficient forecasts as costs would exceed the expected revenues. Though they should not relate to very near future, they should cover a period long enough to make rational forecasts.

5. Availability of information and personnel:

Good forecasts depend upon reliable, timely, accurate and comprehensive information about future. Lack of information will lead to wrong estimates and wrong forecasts. Besides availability of information, people who use this information should also be qualified to process the formation to market rational forecasts.

Quality information will not generate quality forecasts if people do not have knowledge to process that information. People, therefore, have to be trained to make best use of information to make accurate forecasts.