The Dynamics of Judgemental Adjustments in Demand Planning

Judgement plays a central role in forecasting, as statistical forecasts are often modified before informing user decisions. This is done to augment model forecasts with contextual information from the organisation and the market. There is strong evidence that judgemental adjustments can be beneficial, yet inconsistent, often harming forecast accuracy, and subsequent dependent decisions. This has motivated research into how to best manage judgemental adjustments to maximise any benefits. However, a limitation of existing work is that there is very little research into the dynamics of judgemental adjustments: how experts adjust forecasts across time and whether their effectiveness is consistent across forecast horizons. Furthermore, it is unknown whether experts incorporate the same information, and in the same way, for different horizons. This paper attempts to address these questions by investigating the dynamics of judgemental adjustments using evidence from a UK manufacturer. Our findings show that there is a clear shift in the type of information integrated into statistical forecasts, particularly across forecast horizons, resulting in changing patterns of behaviour and inefficiencies arising from the adjustments