We study the performance of sales forecasts which linearly combine model-based forecasts and expert forecasts. Using a unique and very large database containing monthly model-based forecasts for many pharmaceutical products and forecasts given by thirty-seven different experts, we document that a combination almost always is most accurate. When correlating the specific weights in these "best" linear combinations with experts' experience and behaviour, we find that more experience is beneficial for forecasts for nearby horizons. And, when the rate of bracketing increases the relative weights converge to a 50%-50% distribution, when there is some slight variation across forecasts horizons.

combining forecasts, experts forecast, model-based forecasts
Statistical Decision Theory; Operations Research (jel C44), Forecasting and Other Model Applications (jel C53), Retail and Wholesale Trade; Warehousing; e-Commerce (jel L81), Business Administration and Business Economics; Marketing; Accounting (jel M), Marketing (jel M31)
Erasmus Research Institute of Management
hdl.handle.net/1765/10769
ERIM Report Series Research in Management
ERIM report series research in management Erasmus Research Institute of Management
Erasmus Research Institute of Management

Franses, Ph.H.B.F, & Legerstee, R. (2007). A Manager's Perspective on Combining Expert and Model-based Forecasts (No. ERS-2007-083-MKT). ERIM report series research in management Erasmus Research Institute of Management. Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/10769