Qualitative (Subjective) Techniques
The previously discussed techniques (time-series and correlation analysis) are based on the idea that historical demand may follow some patterns, and the goal of the techniques is to identify and numerically document these patterns, then project these patterns into the future. However, it is often the case that the future will not look exactly like the past. For example, there may be no historical demand data available, as is the case with new products. There may also be new conditions that arise, such as a changing competitive landscape or changes in distribution patterns, that make previous demand patterns less relevant. Thus, there is a need for qualita- tive, or subjective, forecasting techniques. Subjective techniques are procedures that turn the opinions of experienced personnel (e.g., marketing planners, salespeople, corporate executives, and outside experts) into formal forecasts. An advantage of subjective techniques is that they take into account the full wealth of key personnel experience and require little formal data. They are also valuable when little or no historical data is available, such as in new product introductions.
Subjective forecasting, however, takes a considerable amount of key personnel time. Because of this drawback, subjective techniques are typically used as a part of long-range, corporate-level forecasting, or for adjustment purposes in short-range product forecasting. For example, the forecast committee of one auto parts manu- facturer with whom we have worked meets once a quarter to subjectively generate a three-year forecast and once a month to subjectively adjust the product forecasts by product line (e.g., all product forecasts in a particular product line may be raised by 3%). Individual product forecasts by inventory location, however, are left to an appropriate time-series technique determined by the forecast managers. Individual