The effects of integrating management judgement into intermittent demand forecasts

Abstract

Empirical research suggests that quantitatively derived forecasts are very frequently judgementally adjusted. Nevertheless, little work has been conducted to evaluate the performance of these judgemental adjustments in a practical demand/sales context. In addition, the relevant analysis does not distinguish between slow and fast moving items. Currently, there are neither conceptual developments nor empirical evidence on the issue of integrating judgements and statistical forecasts for slow/intermittent demand items. Moreover, no results have ever been reported on the stock control implications of these human judgements. Our work analyses monthly intermittent demand forecasts for the UK branch of a major international pharmaceutical company. The company relies upon a commercially available statistical forecasting system to produce forecasts that are subsequently judgementally adjusted based on marketing intelligence gathered by the company forecasters. The benefits of the intervention are evaluated by comparing the actual sales to system and final forecasts using both forecast accuracy and inventory control (accuracy implication) metrics. Our study allows insights to be gained on potential improvements to intermittent demand forecasting processes and, subsequently, the design effectiveness of forecasting support systems.