Incorporating demand uncertainty and forecast error in supply chain planning models
- 1 March 2011
- journal article
- Published by Taylor & Francis Ltd in Journal of the Operational Research Society
- Vol. 62 (3), 483-500
- https://doi.org/10.1057/jors.2010.40
Abstract
This paper develops a framework for examining the effect of demand uncertainty and forecast error on unit costs and customer service levels in the supply chain, including Material Requirements Planning (MRP) type manufacturing systems. The aim is to overcome the methodological limitations and confusion that has arisen in much earlier research. To illustrate the issues, the problem of estimating the value of improving forecasting accuracy for a manufacturer was simulated. The topic is of practical importance because manufacturers spend large sums of money in purchasing and staffing forecasting support systems to achieve more accurate forecasts. In order to estimate the value a two-level MRP system with lot sizing where the product is manufactured for stock was simulated. Final product demand was generated by two commonly occurring stochastic processes and with different variances. Different levels of forecasting error were then introduced to arrive at corresponding values for improving forecasting accuracy. The quantitative estimates of improved accuracy were found to depend on both the demand generating process and the forecasting method. Within this more complete framework, the substantive results confirm earlier research that the best lot sizing rules for the deterministic situation are the worst whenever there is uncertainty in demand. However, size matters, both in the demand uncertainty and forecasting errors. The quantitative differences depend on service level and also the form of demand uncertainty. Unit costs for a given service level increase exponentially as the uncertainty in the demand data increases. The paper also estimates the effects of mis-specification of different sizes of forecast error in addition to demand uncertainty. In those manufacturing problems with high demand uncertainty and high forecast error, improved forecast accuracy should lead to substantial percentage improvements in unit costs. Methodologically, the results demonstrate the need to simulate demand uncertainty and the forecasting process separatelyKeywords
This publication has 31 references indexed in Scilit:
- Dynamic versus static control policies in single stage production-inventory systemsInternational Journal of Production Research, 2008
- Against Your Better Judgment? How Organizations Can Improve Their Use of Management Judgment in ForecastingInforms Journal on Applied Analytics, 2007
- Supply planning under uncertainties in MRP environments: A state of the artAnnual Reviews in Control, 2007
- MRP performance effects due to forecast bias and demand uncertaintyEuropean Journal of Operational Research, 2002
- The Effect of Collaborative Forecasting on Supply Chain PerformanceManagement Science, 2001
- Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and InformationManagement Science, 2000
- Generalising about univariate forecasting methods: further empirical evidenceInternational Journal of Forecasting, 1998
- Forecasting Systems for Production and Inventory ControlInternational Journal of Operations & Production Management, 1992
- COST INCREASES DUE TO DEMAND UNCERTAINTY IN MRP LOT SIZINGDecision Sciences, 1983
- A Note on the Generation of Random Normal DeviatesThe Annals of Mathematical Statistics, 1958