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:

  1. Qualitative approach—forecasts based on judgment and opinion

    • Executive opinions

    • Delphi technique

    • Sales force polling

    • Consumer surveys

  2. Quantitative approach

    1. Forecasts based on historical data

      • Naive methods

      • Moving average

      • Exponential smoothing

      • Trend analysis

      • Decomposition of time series

    2. 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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