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Businesses like to get a feel for what to expect in the future so they can manage their operations. They use forecasts to make decisions. For instance, a forecast about sales for the year ahead is a basis for stocking up on raw materials and arranging any necessary finance. Businesses use both qualitative and quantitative tools in forecasting.
The Delphi method of forecasting is a qualitative technique. An organization interested in making a forecast gets a group of experts, ideally from different backgrounds, to answer the same set of structured questions. The experts send their responses back to a coordinator. Each expert in the forecasting group receives feedback about the responses of their fellow forecasters without identifying individuals. The forecasters send back their revisions based on the input they see from others. This process could happen a few times until there is some degree of agreement between the forecasters’ responses, and the data is usable as a forecasting tool for the business.
Time series techniques of forecasting use past data to extrapolate the future. A moving average is a common time series quantitative forecasting technique. To forecast sales for an upcoming month, a company could simply add up the sales from the previous months and divide by the number of months to get an average. This gives an idea about what to expect in the coming month. The company could also use a weighted average, assigning a specific weight to each period, with more distant periods getting a smaller weighting.
Indicators are another useful quantitative forecasting method. Economic indicators, for instance, give an idea about the direction of the economy. These include leading economic indicators that incorporate data from such input as manufacturers’ new orders and claims for unemployment to provide an idea about the future direction of the economy. In the United States, the Bureau of Economic Analysis collects data that goes into leading, lagging and coincident economic indicators.