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Inventory Decisions in Dell's Supply Chain

Author

Listed:
  • Roman Kapuscinski

    (University of Michigan Business School, Ann Arbor, Michigan 48109)

  • Rachel Q. Zhang

    (Johnson Graduate School of Management, Cornell University, Ithaca, New York 14853)

  • Paul Carbonneau

    (McKinsey & Company, 3 Landmark Square, Stamford, Connecticut 06901)

  • Robert Moore

    (Dell Inc., Mail Stop 6363, Austin, Texas 78682)

  • Bill Reeves

    (Dell Inc., Mail Stop 6363, Austin, Texas 78682)

Abstract

The Tauber Manufacturing Institute (TMI) is a partnership between the engineering and business schools at the University of Michigan. In the summer of 1999, a TMI team spent 14 weeks at Dell Inc. in Austin, Texas, and developed an inventory model to identify inventory drivers and quantify target levels for inventory in the final stage of Dell's supply chain, the revolvers or supplier logistics centers (SLC). With the information and analysis provided by this model, Dell's regional materials organizations could tactically manage revolver inventory while Dell's worldwide commodity management could partner with suppliers in improvement projects to identify inventory drivers and to reduce inventory. Dell also initiated a pilot program for procurement of XDX (a disguised name for one of the major components of personal computers (PCs)) in the United States to institutionalize the model and promote partnership with suppliers. Based on the model predictions, Dell launched e-commerce and manufacturing initiatives with its suppliers to lower supply-chain-inventory costs by reducing revolver inventory by 40 percent. This reduction would raise the corresponding inventory turns by 67 percent. Net Present Value (NPV) calculations for XDX alone suggest $43 million in potential savings. To ensure project longevity, Dell formed the supply-chain-optimization team and charged it with incorporating the model into a strategic redesign of Dell's business practices and supervising improvement projects the model identified.

Suggested Citation

  • Roman Kapuscinski & Rachel Q. Zhang & Paul Carbonneau & Robert Moore & Bill Reeves, 2004. "Inventory Decisions in Dell's Supply Chain," Interfaces, INFORMS, vol. 34(3), pages 191-205, June.
  • Handle: RePEc:inm:orinte:v:34:y:2004:i:3:p:191-205
    DOI: 10.1287/inte.1030.0068
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    Citations

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    Cited by:

    1. Abhilasha Prakash Katariya & Sıla Çetinkaya & Eylem Tekin, 2014. "Cyclic Consumption and Replenishment Decisions for Vendor-Managed Inventory of Multisourced Parts in Dell’s Supply Chain," Interfaces, INFORMS, vol. 44(3), pages 300-316, June.
    2. Kai Huang, 2014. "Benchmarking non-first-come-first-served component allocation in an assemble-to-order system," Annals of Operations Research, Springer, vol. 223(1), pages 217-237, December.
    3. Barros, Oscar & Weber, Richard & Reveco, Carlos, 2021. "Demand analysis and capacity management for hospital emergencies using advanced forecasting models and stochastic simulation," Operations Research Perspectives, Elsevier, vol. 8(C).
    4. Olof Stenius & Ayşe Gönül Karaarslan & Johan Marklund & A. G. de Kok, 2016. "Exact Analysis of Divergent Inventory Systems with Time-Based Shipment Consolidation and Compound Poisson Demand," Operations Research, INFORMS, vol. 64(4), pages 906-921, August.
    5. ElHafsi, Mohsen & Fang, Jianxin & Hamouda, Essia, 2020. "A novel decomposition-based method for solving general-product structure assemble-to-order systems," European Journal of Operational Research, Elsevier, vol. 286(1), pages 233-249.
    6. Yingdong Lu & Jing-Sheng Song & Yao Zhao, 2010. "No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems," Operations Research, INFORMS, vol. 58(3), pages 691-705, June.
    7. Lin, Junyi & Naim, Mohamed M. & Spiegler, Virginia L.M., 2020. "Delivery time dynamics in an assemble-to-order inventory and order based production control system," International Journal of Production Economics, Elsevier, vol. 223(C).
    8. Erica L. Plambeck, 2008. "Asymptotically Optimal Control for an Assemble-to-Order System with Capacitated Component Production and Fixed Transport Costs," Operations Research, INFORMS, vol. 56(5), pages 1158-1171, October.

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