Demand forecasting adjustments for service-level achievement

Argyrios Syntetos · John E. Boylan

43 citations0/0 files storedIMA Journal of Management Mathematics

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Supply Chain and Inventory Management Reliability and Maintenance Optimization Forecasting Techniques and Applications

Abstract

Demand forecasting and stock control are traditionally examined as independent of each other. Even though this weakness has been highlighted in the academic literature, little empirical work has been conducted on forecasting adjustments addressing the interaction between forecasting and stock control. In this paper, the relevant literature is critically reviewed. Subsequently, the empirical performance of some modifications and adjustments, on slow-moving items, is examined in detail. The data set consists of the individual demand histories of 753 intermittent line items from the Royal Air Force (UK). Overall, the results indicate that there is a scope for improving the performance of parametric stock control systems, and adjustments are indeed required in order to account for the interaction between forecasting and stock control.

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References

1999Inventory management and production planning and scheduling 2000Supply Chain Management: Strategy, Planning and Operations 1972Forecasting and Stock Control for Intermittent Demands 2004The accuracy of intermittent demand estimates 2003A new approach to forecasting intermittent demand for service parts inventories 2004The Bullwhip Effect—Impact of Stochastic Lead Time, Information Quality, and Information Sharing: A Simulation Study 2001On the bias of intermittent demand estimates 2004Forecasting for the ordering and stock-holding of spare parts

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2021Forecasting of lead-time demand variance: Implications for safety stock calculations 2019Forecasting for remanufacturing: The effects of serialization 2019On the performance of adjusted bootstrapping methods for intermittent demand forecasting 2020On the empirical performance of some new neural network methods for forecasting intermittent demand 2010Judgement and supply chain dynamics

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