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Achieving Breakthrough Service Delivery Through Dynamic Asset Deployment Strategies

Author

Listed:
  • Morris A. Cohen

    (The Wharton School, University of Pennsylvania, 546 Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, Pennsylvania 19104-6340)

  • Narendra Agrawal

    (Department of Operations and MIS, Leavey School of Business, Santa Clara University, Santa Clara, California 95053)

  • Vipul Agrawal

    (MCA Solutions, 2 Penn Center Plaza, Suite 700, 1500 JFK Boulevard, Philadelphia, Pennsylvania 19102)

Abstract

Many firms have shifted their focus from their products to their customers and the value derived from owning and using the products. They see after-sales service as an important source of revenue and profit, customer acquisition and retention, and competitive differentiation. However, they also find it challenging to manage their service-supply chain. Service organizations must position and manage service-supply-chain resources optimally to support the delivery of after-sales service. They must also develop capabilities to respond rapidly to the demand for service in a cost-effective manner. To succeed in implementing a service-centric strategy, firms must determine what items in their products’ service bill-of-material hierarchy should be deployed throughout their geographical hierarchy of service support locations. They must make these complex and interrelated decisions in anticipation of service demand, which is uncertain. Firms must also be flexible and should understand the mechanisms in a service-supply chain needed to fulfill customers’ demands for service and the resulting demands for support assets and capacities. Dynamic asset deployment (DAD), a collection of management policies that promote this flexibility, can be used to develop the capabilities needed to effectively and profitably deliver services. These policies require a real-options-based optimization approach to decision making.

Suggested Citation

  • Morris A. Cohen & Narendra Agrawal & Vipul Agrawal, 2006. "Achieving Breakthrough Service Delivery Through Dynamic Asset Deployment Strategies," Interfaces, INFORMS, vol. 36(3), pages 259-271, June.
    • Handle: RePEc:inm:orinte:v:36:y:2006:i:3:p:259-271
    DOI: 10.1287/inte.1060.0212
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    References listed on IDEAS

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    1. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "An Empirical Study of Service Differentiation for Weapon System Service Parts," Operations Research, INFORMS, vol. 51(4), pages 518-530, August.
    2. Morris A. Cohen & Seungjin Whang, 1997. "Competing in Product and Service: A Product Life-Cycle Model," Management Science, INFORMS, vol. 43(4), pages 535-545, April.
    3. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes," Management Science, INFORMS, vol. 49(6), pages 683-703, June.
    4. Morris A. Cohen & Yu-Sheng Zheng & Yunzeng Wang, 1999. "Identifying Opportunities for Improving Teradyne's Service-Parts Logistics System," Interfaces, INFORMS, vol. 29(4), pages 1-18, August.
    5. Morris Cohen & Pasumarti V. Kamesam & Paul Kleindorfer & Hau Lee & Armen Tekerian, 1990. "Optimizer: IBM's Multi-Echelon Inventory System for Managing Service Logistics," Interfaces, INFORMS, vol. 20(1), pages 65-82, February.
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    Cited by:

    1. Sang-Hyun Kim & Morris A. Cohen & Serguei Netessine, 2007. "Performance Contracting in After-Sales Service Supply Chains," Management Science, INFORMS, vol. 53(12), pages 1843-1858, December.
    2. Karl Inderfurth & Rainer Kleber, 2010. "An Advanced Heuristic for Multiple-Option Spare Parts Procurement after End-of-Production," FEMM Working Papers 100005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    3. Mirzahosseinian, H. & Piplani, R., 2011. "A study of repairable parts inventory system operating under performance-based contract," European Journal of Operational Research, Elsevier, vol. 214(2), pages 256-261, October.

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