Qualitative forecasting definition
/What is Qualitative Forecasting?
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.
When to Use Qualitative Forecasting
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.
Qualitative forecasting 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.
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Qualitative Forecasting Biases
The results produced by qualitative forecasting can be biased, for the reasons noted below.
Recency. Experts may tend to give greater emphasis to recent historical events in extrapolating future trends. This is because people have a strong tendency to remember the most recently-occurring events, and forget those that occurred earlier. This tends to result in forecasting based largely on recent events, even though recent events might represent an anomaly from the historical trend line.
Personal worldview. Experts may have constructed their own views of how the industry works, and tend to throw out newer influences impacting that market. This is especially common for people who have been in the industry for a long time, and who therefore have an entrenched view of how it operates.
Cognitive load. Experts may be overwhelmed with too much information. If so, this can make it difficult to sort through the available information and determine which items are most relevant to a forecast. It is quite possible for even a highly-experienced person to be sidetracked by certain data, or to ignore other data that are crucial to the construction of a quality forecast.