All judgmental forecasts will be affected by the inherent unreliability, or inconsistency, of the judgment process. Psychologists have studied this problem extensively, but forecasters rarely address it. Researchers and theorists describe two types of unreliability that can reduce the accuracy of judgmental forecasts: (1) unreliability of information acquisition, and (2) unreliability of information processing. Studies indicate that judgments are less reliable when the task is more complex; when the environment is more uncertain; when the acquisition of information relies on perception, pattern recognition, or memory; and when people use intuition instead of analysis. Five principles can improve reliability in judgmental forecasting:1. Organize and present information in a form that clearly emphasizes relevant information.2. Limit the amount of information used in judgmental forecasting. Use a small number of really important cues.
3.Use mechanical methods to process infomation.
4.Combine several forecasts.
Require justification of forecasts.Keywords: Accuracy, combining forecasts, error, information acquisition, information processing, psychometrics, reliability.People are not consistent. Imperfect reliability (sometimes called "inconsistency") is observed in nearly all human behavior. Observe a person on separate occasions that are identical in every important respect, and you will observe different behavior on each occasion. If a person takes the same test on two different occasions, the two test scores will differ. If Stewart, T. R. (2001). Improving reliability of judgmental forecasts. In J. S. Armstrong (Ed.), Principles of Forecasting: A Handbook for : Kluwer Academic Publishers.
82PRINCIPLES OF FORECASTING a person judges the loudness of a sound one day and then judges the same sound the next day, the judgments will usually differ. If a forecaster made a judgmental forecast and then could be somehow transported back in time to repeat the same forecast under identical conditions, she would almost certainly make a different forecast. In short, unreliability is a source of error in judgmental forecasting. In the long run, it can only reduce the accuracy of forecasts. Lack of reliability or consistency has nothing to do with potentially beneficial behavioral changes over time, such as changes due to learning, obtaining new information, or adapting to new circumstances. Unreliability is simply error introduced into the forecast by the natural inconsistency of the human judgment process.If human judgment is so important in forecasting, and unreliability is a pervasive and well known (at least to psychologists) source of error in judgment, then why isn't improving reliability a major concern of those who produce and use forecasts? 1 don't know. One possible reason is that reliability is difficult or impossible to measure directly outside the laboratory. As a result, although we can argue persuasively that a problem exists, it is difficult to demonstrate its importance in operational settings. Another re...