| Abstract: |
We looked at evidence from comparative empirical studies to identify methods
that can be useful for predicting demand in various situations and to warn
against methods that should not be used. In general, use structured methods
and avoid intuition, unstructured meetings, focus groups, and data mining. In
situations where there are sufficient data, use quantitative methods including
extrapolation, quantitative analogies, rule-based forecasting, and causal
methods. Otherwise, use methods that structure judgement including surveys of
intentions and expectations, judgmental bootstrapping, structured analogies,
and simulated interaction. Managers' domain knowledge should be incorporated
into statistical forecasts. Methods for combining forecasts, including Delphi
and prediction markets, improve accuracy. We provide guidelines for the
effective use of forecasts, including such procedures as scenarios. Few
organizations use many of the methods described in this paper. Thus, there are
opportunities to improve efficiency by adopting these forecasting practices. |