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Contracting for Infrequent Restoration and Recovery of Mission-Critical Systems

Published: 01 September 2010 Publication History

Abstract

Firms that rely on functioning mission-critical equipment for their businesses cannot afford significant operational downtime due to system disruptions. To minimize the impact of disruptions, a proper incentive mechanism has to be in place so that the suppliers provide prompt restoration and recovery services to the customer. A widely adopted incentive mechanism is performance-based contracting (PBC), in which suppliers receive compensation based on realized system uptime. A key obstacle is that disruptions occur infrequently, making it very expensive for a supplier to commit the necessary resources for recovery because they will be idle most of the time. In this paper, we show that designing a successful PBC creates nontrivial challenges that are unique to this environment. Namely, because of the infrequent and random nature of disruptions, a seemingly innocuous choice of performance measures used in contracts may create unexpected incentives, resulting in counterintuitive optimal behavior. We compare the efficiencies of two widely used contracts, one based on sample-average downtime and the other based on cumulative downtime, and identify the supplier's ability to influence the frequency of disruptions as an important factor in determining which contract performs better. We also show that implementing PBC may create high agency cost when equipment is very reliable. This counterintuitive situation arises because the realized downtimes from which the customer might intuit about the supplier's capacity investment are highly uncertain when there are not many samples of downtimes, i.e., when disruptions occur rarely.

References

[1]
}}Abreu, D., Milgrom, P. and Pearce, D., "Information and timing in repeated partnerships," Econometrica, v59, pp. 1713-1733, 1991.
[2]
}}Allon, G. and Federgruen, A., "Competition in service industries," Oper. Res., v55, pp. 37-55, 2007.
[3]
}}Ata, B. and Shneorson, S., "Dynamic control of an M/M/1 service system with adjustable arrival and service rates," Management Sci., v52, pp. 1778-1791, 2006.
[4]
}}Cohen, M., Agrawal, N. and Agrawal, V., "Winning in the aftermarket," Harvard Bus. Rev., v84, pp. 129-138, 2006.
[5]
}}Cohen, M., Kamesam, P. V., Kleindorfer, P., Lee, H. and Tekerian, A., "Optimizer: IBM's multi-echelon inventory system for managing service logistics," Interfaces, v20, pp. 65-82, 1990.
[6]
}}Frauenheim, E., "Disaster industry finds silver lining," CNET News, 2003.
[7]
}}Gans, N., Koole, G. and Mandelbaum, A., "Telephone call centers: Tutorial, review, and research prospects," Manufacturing Service Oper. Management, v5, pp. 79-141, 2003.
[8]
}}Geary, S., "Ready for combat," DC Velocity, v4, pp. 75-80, 2006.
[9]
}}Gilbert, S. M. and Weng, Z. K., "Incentive effects favor nonconsolidating queues in a service system: The principal-agent perspective," Management Sci., v44, pp. 1662-1669, 1998.
[10]
}}Glader, P., "GE's focus on services faces test," Wall Street Journal, 2009.
[11]
}}Gollier, C., The Economics of Risk and Time, MIT Press, Cambridge, MA, 2001.
[12]
}}Gurvich, I., Armony, M. and Mandelbaum, A., "Service-level differentiation in call centers with fully flexible servers," Management Sci., v54, pp. 279-294, 2005.
[13]
}}Harrington, L., "Getting service parts logistics up to speed," Inbound Logist., 2006.
[14]
}}Hasija, S., Pinker, E. J. and Shumsky, R. A., "Call center outsourcing contracts under information asymmetry," Management Sci., v54, pp. 793-807, 2008.
[15]
}}Kim, S.-H., Cohen, M. A. and Netessine, S., "Performance contracting in after-sales service supply chains," Management Sci., v53, pp. 1843-1858, 2007.
[16]
}}Kim, S.-H., Cohen, M. A. and Netessine, S., "Reliability or inventory? Analysis of product support contracts in the defense industry," 2010.
[17]
}}Kleindorfer, P. R. and Saad, G. H., "Managing disruption risks in supply chains," Production Oper. Management, v14, pp. 53-68, 2005.
[18]
}}Laffont, J.-J. and Tirole, J., A Theory of Incentives in Regulation and Procurement, MIT Press, Cambridge, MA, 1993.
[19]
}}Lu, L. X., Van Mieghem, J. A. and Savaskan, R. C., "Incentives for quality through endogenous routing," Manufacturing Service Oper. Management, v11, pp. 254-273, 2009.
[20]
}}Milgrom, P. R., "Good news and bad news: Representation theorems and applications," Bell J. Econom., v12, pp. 380-391, 1981.
[21]
}}Milner, J. M. and Olsen, T. L., "Service-level agreements in call centers: Perils and prescriptions," Management Sci., v54, pp. 238-252, 2008.
[22]
}}Muckstadt, J. A., Analysis and Algorithms for Service Parts Supply Chains, Springer, New York, 2005.
[23]
}}"Airlines have not yet realized the full benefits of new MRO supplier relationships," 2007.
[24]
}}Plambeck, E. L. and Zenios, S. A., "Incentive efficient control of a make-to-stock production system," Oper. Res., v51, pp. 371-386, 2003.
[25]
}}Ren, Z. J. and Zhou, Y.-P., "Call center outsourcing: Coordinating staffing levels and service quality," Management Sci., v54, pp. 369-383, 2008.
[26]
}}Sheffi, Y., The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage, MIT Press, Cambridge, MA, 2005.
[27]
}}Sherbrooke, C. C., "METRIC: A multi-echelon technique for recoverable item control," Oper. Res., v16, pp. 122-141, 1968.
[28]
}}Sherbrooke, C. C., Optimal Inventory Modeling of Systems: Multi-Echelon Techniques, John Wiley & Sons, New York, 1992.
[29]
}}Sobie, B., "Maintenance for low-cost carriers: Outer limits," Airline Bus., v23, pp. 46-53, 2007.
[30]
}}Stansbury, T., "Choose the right partner," Comm. News, v41, pp. 28-29, 2004.
[31]
}}Tomlin, B., "On the value of mitigation and contingency strategies for managing supply chain disruption risks," Management Sci., v52, pp. 639-657, 2006.
[32]
}}"Performance work statement (PWS) samples: ADPE maintenance," 2006.
[33]
[34]
[35]
[36]
}}"Guidance needed for using performance-based service contracting," 2002.
[37]
}}"Performance-based service acquisition: Contracting for the future," 2003.
[38]
}}Van Mieghem, J. A., "Risk mitigation in newsvendor networks: Resource diversification, flexibility, sharing, and hedging," Management Sci., v53, pp. 1269-1288, 2007.

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  1. Contracting for Infrequent Restoration and Recovery of Mission-Critical Systems

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    Published In

    cover image Management Science
    Management Science  Volume 56, Issue 9
    September 2010
    218 pages

    Publisher

    INFORMS

    Linthicum, MD, United States

    Publication History

    Published: 01 September 2010
    Accepted: 12 April 2010
    Received: 02 January 2008

    Author Tags

    1. after-sales support
    2. disaster recovery
    3. maintenance--repairs
    4. service outsourcing
    5. supply chain

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