Role of Forecasting

Forecasting A forecast should be as accurate as possible. There are several reasons for this. The first is that forecasts are often used to make business decisions such as purchasing and resource deployment. When the forecast is far from reality, the business decisions will also reflect that. If the point of forecasting is to ensure the right levels of labor, inventory and capital, then a bad forecast will leave the company with an amount of these things entirely inadequate for its needs.

In addition, forecasts are used as control for companies. Managers and other workers are sometimes evaluate on the basis of their ability to meet budgets. Thus, the forecast needs to be fairly accurate. If the forecast is not accurate, then the use of the forecast as a control tool becomes much more difficult, if not outright impossible. People cannot be measured against unrealistic expectations, and the same goes for a division or unit within the company. Therefore, it is important that the budget is realistic as possible.

The control function works better the closer the budget is to the reality -- this allows for deviations to be identified more clearly and the company is then in a better position to make the right adjustments. Companies often feel as though they must make a choice to invest in order to gain a greater level of forecasting accuracy.

Some forecasting can be done at relatively low cost -- regression analysis can be done on Excel, and things like economic projections are compiled and published by different branches of the government. However, there are instances where the company needs to make an investment in better forecasting. The value of this can be determined, however. There are costs associated with bad forecasting. Consider the above scenario wherein the company has a wildly inaccurate forecast for demand in its budget, but bought raw materials to meet that demand.

The company now faces costs associated with warehousing those raw materials. If the materials are perishable, then the cost of that poor forecasting is even higher. A company can calculate the costs associated with bad forecasting, and use those costs to perform a cost-benefit analysis on the added costs to deliver better forecasting. The business will determine whether short-term or long-term forecasting is more important. Each has its value to the organization.

Short-term forecasting typically deals with lower dollar values because of the shorter time frame, but there is real opportunity to make tangible improvements because the short-term forecast is likely to be more accurate in nature. In that sense, short-term forecasting is certainly better as a cost containment and control mechanism. Long-term forecasting tends to be less accurate, because of the longer time horizon and the variables that introduces -- there is always risk associated with longer time frames.

However, there are times when major decisions are made on the basis of long-term forecasts. An example would be a forecast that calls for massive demand increases, leading to a commitment to build a new factory.