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Breadth of range and depth of stock: forecasting and inventory management at Euro Car Parts Ltd

Author

Listed:
  • F R Johnston

    (Euro Car Parts)

  • E A Shale

    (University of Warwick)

  • S Kapoor

    (Euro Car Parts)

  • R True

    (Euro Car Parts)

  • A Sheth

    (Euro Car Parts)

Abstract

This paper investigates inventory management issues in a distribution network. The study is motivated by examining the operation of a wholesaling car parts company. Customer service requirements are of paramount importance in this market sector. The nature of the demand facing the company is characterised. The breadth of range of stock keeping units (SKUs) held at a stocking location and the quantity of each SKU held are normally treated in isolation but in this case, the rule developed to select the range of SKU was extended to determine the level of stock to hold. It is intuitively obvious that these two factors should be linked, yet the authors have not found any other literature developing the connection in a practical context. Forecasting issues are explored as the rule on stock range depends on a forecast of the number of orders received for each SKU at each stocking unit. Some implementation issues and extensions are indicated.

Suggested Citation

  • F R Johnston & E A Shale & S Kapoor & R True & A Sheth, 2011. "Breadth of range and depth of stock: forecasting and inventory management at Euro Car Parts Ltd," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 433-441, March.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:3:d:10.1057_jors.2010.189
    DOI: 10.1057/jors.2010.189
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    References listed on IDEAS

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    1. Kutanoglu, Erhan & Mahajan, Mohit, 2009. "An inventory sharing and allocation method for a multi-location service parts logistics network with time-based service levels," European Journal of Operational Research, Elsevier, vol. 194(3), pages 728-742, May.
    2. F R Johnston & J E Boylan & E A Shale, 2003. "An examination of the size of orders from customers, their characterisation and the implications for inventory control of slow moving items," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 833-837, August.
    3. Dominey, M. J. G. & Hill, R. M., 2004. "Performance of approximations for compound Poisson distributed demand in the newsboy problem," International Journal of Production Economics, Elsevier, vol. 92(2), pages 145-155, November.
    4. Syntetos, A. A. & Boylan, J. E., 2001. "On the bias of intermittent demand estimates," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 457-466, May.
    5. Paul Zipkin, 1991. "Evaluation of base‐stock policies in multiechelon inventory systems with compound‐poisson demands," Naval Research Logistics (NRL), John Wiley & Sons, vol. 38(3), pages 397-412, June.
    6. Matheus, Peter & Gelders, Ludo, 2000. "The (R, Q) inventory policy subject to a compound Poisson demand pattern," International Journal of Production Economics, Elsevier, vol. 68(3), pages 307-317, December.
    7. E A Shale & J E Boylan & F R Johnston, 2006. "Forecasting for intermittent demand: the estimation of an unbiased average," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 588-592, May.
    8. Mantrala, Murali K. & Levy, Michael & Kahn, Barbara E. & Fox, Edward J. & Gaidarev, Peter & Dankworth, Bill & Shah, Denish, 2009. "Why is Assortment Planning so Difficult for Retailers? A Framework and Research Agenda," Journal of Retailing, Elsevier, vol. 85(1), pages 71-83.
    9. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
    10. Kennedy, W. J. & Wayne Patterson, J. & Fredendall, Lawrence D., 2002. "An overview of recent literature on spare parts inventories," International Journal of Production Economics, Elsevier, vol. 76(2), pages 201-215, March.
    11. Porras, Eric & Dekker, Rommert, 2008. "An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods," European Journal of Operational Research, Elsevier, vol. 184(1), pages 101-132, January.
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