Managing Demand Forecasting with Moral Hazard and Demand Censoring

Abstract

Demand forecasting has recently become a prime candidate for outsourcing. This research investigates how to design an information quality incentive (IQI) mechanism to manage the quality of demand forecasting in a multi-stage model where the company uses a forecaster's demand forecast to manage the production activity. The posterior demand follows a normal distribution with a precision determined by the forecaster's effort. At the end of the planning horizon, the company conducts a review with the forecaster to determine the amount of a transfer payment. If the forecaster's ability is known and the company is allowed to charge a small penalty for any forecast that is out of an acceptable range, we propose an IQI contract that enables the company to achieve the first-best outcome by overcoming moral hazard and demand censoring. In a more difficult case where any negative transfer payment is banned, the company cannot avoid paying an information rent to the forecaster. We show that in terms of reducing information rents, a transfer payment function based on absolute forecast errors is more efficient than a counter part that is based on squared forecast errors. We also extend the analysis to the case where the forecaster's ability is private.