A diagnostic analysis of retail out-of-stocks

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2007.

Bibliographic Details
Main Author: Foo, Yong Ning
Other Authors: Stephen C. Graves.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2008
Subjects:
Online Access:http://hdl.handle.net/1721.1/41734
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author Foo, Yong Ning
author2 Stephen C. Graves.
author_facet Stephen C. Graves.
Foo, Yong Ning
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description Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2007.
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spelling mit-1721.1/417342019-04-10T09:57:37Z A diagnostic analysis of retail out-of-stocks Diagnostic analysis of retail OOSs Foo, Yong Ning Stephen C. Graves. Massachusetts Institute of Technology. Computation for Design and Optimization Program. Massachusetts Institute of Technology. Computation for Design and Optimization Program. Computation for Design and Optimization Program. Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2007. Includes bibliographical references (p. 101). In the highly competitive retail industry, merchandise out-of-stock (OOS) is a significant and pertinent problem. This thesis performs a diagnostic analysis on retail out-of-stocks using empirical data from a major retailer. In this thesis, we establish the empirical relationship of OOS rate with the amount of safety stock carried, the time between orders and the forecast error, providing insights to the effects of these three factors on the probability of OOS occurrences. The root causes of OOS are also examined in the thesis. We find that up to 34% of OOS can be attributed to forecast error while up to 22% can be attributed to delay in order replenishment. For the OOSs that were associated with order delay, we can trace 60% of these to out-of-stock at the store's distribution center (DC). The thesis also examines a peculiarity in the occurrence of OOSs. We found that the OOS rate of Class C items is significantly higher in stores with higher sales volume. We can attribute much of this phenomenon to three factors: stores with higher sales volume hold less safety stock for Class C items, have a shorter time between orders and have relatively larger forecast errors. by Yong Ning Foo. S.M. 2008-05-19T16:13:07Z 2008-05-19T16:13:07Z 2007 2007 Thesis http://hdl.handle.net/1721.1/41734 225092330 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 101 p. application/pdf Massachusetts Institute of Technology
spellingShingle Computation for Design and Optimization Program.
Foo, Yong Ning
A diagnostic analysis of retail out-of-stocks
title A diagnostic analysis of retail out-of-stocks
title_full A diagnostic analysis of retail out-of-stocks
title_fullStr A diagnostic analysis of retail out-of-stocks
title_full_unstemmed A diagnostic analysis of retail out-of-stocks
title_short A diagnostic analysis of retail out-of-stocks
title_sort diagnostic analysis of retail out of stocks
topic Computation for Design and Optimization Program.
url http://hdl.handle.net/1721.1/41734
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