14.2. Forecasting Methods
The company may choose from a wide range of forecasting techniques. There are basically two approaches to forecasting, qualitative and quantitative:
Qualitative approach—forecasts based on judgment and opinion
Executive opinions
Delphi technique
Sales force polling
Consumer surveys
Quantitative approach
Forecasts based on historical data
Naive methods
Moving average
Exponential smoothing
Trend analysis
Decomposition of time series
Associative (causal) forecasts
Simple regression
Multiple regression
Econometric modeling
Exhibit 14.2 summarizes the forecasting methods. The list presented in the exhibit is neither comprehensive nor exhaustive. Sophisticated time series methods such as Box-Jenkins are reserved for an advanced forecasting text.
Quantitative models work superbly as long as little or no systematic change in the environment takes place. When patterns or relationships do change, by themselves, the objective models are of little use. It is here where the qualitative approach, based on human judgment, is indispensable. Because judgmental forecasting also bases forecasts on observation of existing trends, they too are subject to a number of shortcomings. The advantage, however, is that they can identify systematic change more quickly and interpret better the effect of such change on the future.
We discuss the qualitative method in this chapter. Several quantitative methods, along with their illustrations, are taken up in the next two chapters.
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