Judgmental Forecasts

Judgmental forecasts are based on subjective views — often the opinions of experts in the field.  Sometimes there is a complete absence of data, and at other times the data is unreliable or irrelevant to the future.

Quantitative forecasts are always more reliable, but when you don’t have the necessary data, you have to use a judgmental method. There are five widely used methods.

Personal insight. This uses a single person who is familiar with the situation to produce a forecast based on his/her own judgment. This is the most widely used forecasting method  — but is unreliable abd often gives very bad results.

Panel Consensus. This collects together a group of experta to mak experts to make a fore cast. If there is no secrecy  and the panel talk talk freely and openly, you can find a genuine consensus. On the other hand, there may be difficulties in combining  the views of different people.

Market surveys. Sometimes even groups of experts don’t have enough knowledge to give a reasonable forecast about, for example, the launch of a new product. Then market surveys collect data from a sample of potential customers, analyse their views and make inferences about the population at large.

Historical analogy. If you are introducing a new product, you might have a similar product that you launched recently, and assume that demand for the new product will follow the same pattern. If a publisher is selling a new book, it can forecast the likely demand from the actual demand for a similar book it published earlier.

Delphi method. For this you contact a number of experts by post and give each a questionnaire to complete. Then you analyze the replies from the questionnaire to complete. Then you analyze the replies from the questionnaires and send the summaries back to experts. You ask them if they would like to reconsider their original reply in the light of the summarized replies from others. This is repeated several times — usually between three and six — until the range of opinions is narrow enough to help with decisions.

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