Qualitative forecasting is an estimation methodology that uses expert judgment, rather than numerical analysis. This type of forecasting relies upon the knowledge of highly experienced employees and consultants to provide insights into future outcomes. This approach is substantially different from quantitative forecasting, where historical data is compiled and analyzed to discern future trends.
Qualitative forecasting is most useful in situations where it is suspected that future results will depart markedly from results in prior periods, and which therefore cannot be predicted by quantitative means. For example, the historical trend in sales may indicate that sales will increase again in the next year, which would normally be measured using trend line analysis; however, an industry expert points out that there will be a materials shortage at a key supplier that will force sales downward.
Another situation in which qualitative forecasting can be useful is in the assimilation of large amounts of narrowly-focused local data to discern trends that a more quantitative analysis might not find. For example, a construction company needs to know what style of home to build in a certain area, and relies on a local population expert to find out that the area in question is being abandoned by younger families and replaced by an older, retirement-age group. Consequently, the builder constructs smaller one-level homes with fewer bedrooms.
This approach also works well when a course of action must be derived from inadequate data. In this case, a qualitative analysis will seek to link disparate data to construct a more broad-based view, sometimes incorporating intuition to construct this view.
Another situation in which qualitative forecasting can provide value is when management modifies historically-derived trends based on expert opinions. In this case, quantitative methods are used to create a preliminary forecast, which is then adjusted with a qualitative review. In theory, the result should be a forecast derived from the best of both methods.
The results produced by qualitative forecasting can be biased, for the following reasons:
Recency. Experts may tend to give greater emphasis to recent historical events in extrapolating future trends.
Personal worldview. Experts may have constructed their own views of how the industry works, and tend to throw out newer influences impacting that market.