Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand

Recent research suggests that the bullwhip effect, or increasing variability of inventory replenishment orders as one moves up a supply chain, illustrates inventory management inefficiencies. This paper quantifies the bullwhip effect in the case of serially correlated external demand, if autoregress...

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Bibliographic Details
Published inEuropean journal of operational research Vol. 166; no. 2; pp. 337 - 350
Main Authors Chandra, Charu, Grabis, Jānis
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 16.10.2005
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Applied sciences
Bullwhip effect
Exact sciences and technology
Forecasting
Inventory
Inventory control, production control. Distribution
Inventory management
Material requirements planning
Operational research and scientific management
Operational research. Management science
Operations research
Simulation
Studies
Supply chains
Bullwhip effect
Forecasting
Inventory
Manufacturing resource planning
Supply chain
Replenishment
Material requirements planning
Inventory control
Autoregressive model
Make to stock
Resource management
Logistics
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Summary:Recent research suggests that the bullwhip effect, or increasing variability of inventory replenishment orders as one moves up a supply chain, illustrates inventory management inefficiencies. This paper quantifies the bullwhip effect in the case of serially correlated external demand, if autoregressive models are applied to obtain multiple steps demand forecasts. A materials requirements planning (MRP) based inventory management approach is proposed to reduce the order variance. Simulation modeling is used to investigate the impact of the forecasting method selection on the bullwhip effect and inventory performance for the most downstream supply chain unit. The MRP based approach is shown to reduce magnitude of the bullwhip effect while providing the inventory performance comparable to that of a traditional order-up approach. The application of autoregressive models compares favorably to other forecasting methods considered according to both the bullwhip effect and inventory performance criteria.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2004.02.012