Forecasting and Inventory Management: Bridging the Gap

The aim of this project is to bring together the strengths of statistical and judgemental forecasting with the complementary benefits of System Dynamics (SD), to initiate a new research agenda for inventory modelling. Currently, the Operational Research (OR) and Industrial Engineering (IE) disciplines are very fragmented, as shown by the different conferences (and corresponding audiences) organized by different societies (eg, SD, Forecasting, Inventories Research) that in turn produce different journals, with inadequate cross-referencing. Consequently, these sub-disciplines have grown into disciplines in their own right, prohibiting a constructive exchange of ideas for the benefit of solving problems of common interest. There is great scope for the cross-utilization of the modelling approaches employed by these disciplines, to develop more effective computerized solutions and to educate modellers and decision-makers. In particular, it is viewed as imperative to bring together their complementary strengths in order to solve complex inventory problems, an example of which is the 'Bullwhip effect' (i.e. of magnifying inventories as we move backwards in a supply chain). These complex problems demonstrate the industrial importance of inventory management and the considerable benefit that their solution may offer to modern organizations. Such a solution necessitates novel inter-disciplinary approaches to problem formulation and modelling and this is the first proposal to provide them. Complex issues related to the interactions between statistical demand forecasting and stock control are currently being addressed in the first grant EP/D062942/1 EPSRC project led by Aris Syntetos. The enhancement of the current research portfolio will occur through the explicit consideration of SD and judgemental forecasting.