Demand Forecasting of Over-Promoted FMCG Products in a Manufacturing Company

Abstract

Overuse of trade sales promotion to keep fast-moving consumer goods (FMCG) in the range of retail stores results in a lot of negative impacts on all members of the supply chain network. One of the consequences is also an extreme increase in demand variability for FMCG manufacturers. However, such demand becomes unpredictable if only common forecasting methods are applied. This paper aims to find ways of forecasting the demand that is affected by frequent implementation of promotional events. Based on the case study conducted with a large Czech manufacturer of FMCG products, the paper first discusses the possibilities and barriers of the current theoretical approaches to demand forecasting of promoted products, which subsequently results in a proposal of a statistical forecasting method for over-promoted products. The proposed approach to demand forecasting combines a multiple linear regression (MLR) model with an autoregressive integrated moving average (ARIMA) model. By its application in the company involved in the research, they were able to decrease the simple statistical forecast error by 24%.