A decision system for routing returned product to the optimal recovery channel
Name
659825144-MIT.pdf
Description
Full printable version
Size
5.84 MB
Format
Adobe PDF
Checksum (MD5)
3c85c70559fe45749f1135c6bf62f9b3
Author(s)
Lin, Christopher C. (Christopher Cheyih)
Advisor(s)
David Simchi-Levi and Roy Welsch.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
Dell, a leading computer manufacturer, must deal with systems returned from its customers. Historically, it has refurbished most of its returned systems for resale on its Dell Outlet website. While this has provided high net recoveries (revenue less incurred costs) compared to its peers, Dell believes there is ample opportunity in cannibalizing some returned systems for the piece parts (i.e. "teardown"). These harvested piece parts can be used to service field systems, repair refurbished systems, or directly sold to customers as spare parts. Dell is concerned about ensuring an optimal disposition of system to teardown vs. direct resale. Written as part of research internship at Dell, this paper proposes, simulates, and evaluates a decision support system to address the question of disposition. The decision engines use historical data and statistics to estimate net recoveries in resale and forecasted demand to estimate net recoveries through teardown. Linear regressions were found to have poor power in predicting overall net recoveries; however, simple heuristics were found to identify likely low recovery systems. Overall, the implementation of the decision support system will drive improved net recoveries, with savings estimated to be greater than $1 million annually.
Description
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 62-63).
Subjects
Sloan School of Management.
Electrical Engineering and Computer Science.
Leaders for Global Operations Program.
MIT Department
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Sloan School of Management
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