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Setting safety stock based on imprecise records

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  • Kumar, Anupam
  • Evers, Philip T.

Abstract

Setting safety stocks traditionally relies upon the random sums approach. The data requirements for successful application of this approach, however, can be difficult to fulfill in certain settings and necessitate that accurate records be kept for determining the input parameters. Furthermore, the random sums approach assumes independence between demand and lead time, a condition that could be violated during demand spikes. This paper examines the impact on safety stocks when record keeping is compromised. An alternative formulation for setting safety stocks is proposed using a multiplication approach for estimating the variance that eliminates the need for pre-specified relationships and accounts for: (1) data quality issues; (2) demand and lead time correlation; and (3) computational simplicity. Using simulation, general applicability of the multiplication method is examined and the performance of alternative formulations is assessed. The multiplication approach, with its ease of application, is found to provide comparable results.

Suggested Citation

  • Kumar, Anupam & Evers, Philip T., 2015. "Setting safety stock based on imprecise records," International Journal of Production Economics, Elsevier, vol. 169(C), pages 68-75.
    • Handle: RePEc:eee:proeco:v:169:y:2015:i:c:p:68-75
    DOI: 10.1016/j.ijpe.2015.07.018
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    References listed on IDEAS

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    1. Braglia, Marcello & Castellano, Davide & Frosolini, Marco, 2014. "Safety stock management in single vendor–single buyer problem under VMI with consignment stock agreement," International Journal of Production Economics, Elsevier, vol. 154(C), pages 16-31.
    2. Thiel, Daniel & Hovelaque, Vincent & Thi Le Hoa, Vo, 2010. "Impact of inventory inaccuracy on service-level quality in (Q,R) continuous-review lost-sales inventory models," International Journal of Production Economics, Elsevier, vol. 123(2), pages 301-311, February.
    3. Steffen T. Klosterhalfen & Stefan Minner & Sean P. Willems, 2014. "Strategic Safety Stock Placement in Supply Networks with Static Dual Supply," Manufacturing & Service Operations Management, INFORMS, vol. 16(2), pages 204-219, May.
    4. Altay, Nezih & Litteral, Lewis A. & Rudisill, Frank, 2012. "Effects of correlation on intermittent demand forecasting and stock control," International Journal of Production Economics, Elsevier, vol. 135(1), pages 275-283.
    5. So, Kut C. & Zheng, Xiaona, 2003. "Impact of supplier's lead time and forecast demand updating on retailer's order quantity variability in a two-level supply chain," International Journal of Production Economics, Elsevier, vol. 86(2), pages 169-179, November.
    6. T L Urban, 2000. "Reorder level determination with serially-correlated demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(6), pages 762-768, June.
    7. Gary D. Eppen & R. Kipp Martin, 1988. "Determining Safety Stock in the Presence of Stochastic Lead Time and Demand," Management Science, INFORMS, vol. 34(11), pages 1380-1390, November.
    8. Salal Humair & John D. Ruark & Brian Tomlin & Sean P. Willems, 2013. "Incorporating Stochastic Lead Times Into the Guaranteed Service Model of Safety Stock Optimization," Interfaces, INFORMS, vol. 43(5), pages 421-434, October.
    9. Fleisch, Elgar & Tellkamp, Christian, 2005. "Inventory inaccuracy and supply chain performance: a simulation study of a retail supply chain," International Journal of Production Economics, Elsevier, vol. 95(3), pages 373-385, March.
    10. Dolgui, Alexandre & Pashkevich, Maksim, 2008. "Demand forecasting for multiple slow-moving items with short requests history and unequal demand variance," International Journal of Production Economics, Elsevier, vol. 112(2), pages 885-894, April.
    11. Boute, Robert N. & Disney, Stephen M. & Lambrecht, Marc R. & Houdt, Benny Van, 2014. "Coordinating lead times and safety stocks under autocorrelated demand," European Journal of Operational Research, Elsevier, vol. 232(1), pages 52-63.
    12. Nicole DeHoratius & Adam J. Mersereau & Linus Schrage, 2008. "Retail Inventory Management When Records Are Inaccurate," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 257-277, November.
    13. Edward A. Silver, 1981. "Operations Research in Inventory Management: A Review and Critique," Operations Research, INFORMS, vol. 29(4), pages 628-645, August.
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    3. Gonçalves, João N.C. & Sameiro Carvalho, M. & Cortez, Paulo, 2020. "Operations research models and methods for safety stock determination: A review," Operations Research Perspectives, Elsevier, vol. 7(C).

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