Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?

Model-based SKU-level forecasts are often adjusted by experts. In this paper we propose a statistical methodology to test whether these expert forecasts improve on model forecasts. Application of the methodology to a very large database concerning experts in 35 countries who adjust SKU-level forecasts for pharmaceutical products in seven distinct categories leads to the general conclusion that expert forecasts are equally good at best, but are more often worse than model-based forecasts. We explore whether this is due to experts putting too much weight on their contribution, and this indeed turns out to be the case.

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