The Forecaster's Dilemma
Abstract
Influential forecasts occur when the forecast itself determines whether the forecast is tested. New product sales forecasts are often influential because a low forecast may cause a firm not to launch a new product so that actual sales are never observed.
This paper considers a dilemma we face as influential forecasters. Our client requests an unbiased forecast but pressures sometimes exist to provide a bias forecast. From theoretical and empirical perspectives, we discuss the impact of these pressures on the quality of forecasts. We find that:
• Noninfluential forecasts, generally, create no pressure for statistically biased forecasts.
• As influence increases, the pressures increase.
• When our forecasts eliminate alternatives, (e.g., product designs, advertising campaigns), not all forecasts are tested.
• Not validating all forecasts causes two effects: Survivor's Curse and Prophet's Fear.
• Survivor's Curse makes statistically unbiased forecasts appear optimistic (i.e., overestimate actual sales) because, often, only optimistic forecasts are tested.
• Forecasts appearing statistically unbiased or pessimistic might cause concern. Perhaps, some failures are justified.
• Prophet's Fear encourages pessimistic forecasts because these forecasts cause hidden opportunity losses while optimistic forecasts cause observable actual losses.
• Tested forecasts may appear completely unbiased despite a pessimistic pre-launch bias.
• Although no perfect solution exists, clients may lessen bias with experimentation and by seeking more accurate forecasts. Forecasters may lessen bias with forecasts conditioned on launching and by seeking more accurate forecasts.

