Kandrika Pritularga, PhD, University of Lancaster, United Kingdom

Title: Forecast congruence: a quantity to align forecasts and inventory decisions

Abstract: Forecasting is a step undertaken in many business decisions. For instance, in inventory management, demand forecasts are the cornerstone of inventory decisions, namely how much and when to order. It is widely recognised that accurate demand forecasts lead to effective and efficient inventory decisions. However, in practice the forecasts are produced in isolation, ie, the models are selected and evaluated on accuracy metrics that do not account for important aspects of inventory management. Even though there are good reasons in support of this practice, for the alternative approach, to help managers calibrate their forecasting process from a decision standpoint, we lack appropriate measures of forecast quality. We address this limitation by introducing the quantity of forecast congruence, which measures thejitteriness’ of forecasts over the decision period. We investigate its characteristics and connection to accuracy and demonstrate with simulations and a real case on an FMCG manufacturer that congruence is connected with the volatility of inventory decisions. We show that accounting for congruence in forecast design and selection can achieve favourable inventory performance, without necessitating evaluations that rely on complex inventory simulations. We conclude by discussing its connection with estimation uncertainty and the bullwhip effect.