2026-09-19T12:16:31Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1225762021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Stephen Graves and David Simchi-Levi.
Imlay, Ashton David.
Sloan School of Management.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.
Leaders for Global Operations Program.
Sloan School of Management
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Leaders for Global Operations Program
2019-10-11T22:24:20Z
2019-10-11T22:24:20Z
2019
2019
2019
https://hdl.handle.net/1721.1/122576
1119388569
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 54-55).
For top wholesale retail companies, the demand for products from US-based customers (wholesale, digital, and direct to consumer) is extremely high. However, the available supply of a product is contingent upon the success of long-term forecasting, manufacturers across the globe, and intercontinental transportation. Therefore, there is not always enough supply to meet demand. In these situations, wholesale retailers must decide which orders to prioritize in the allocation of available supply. This thesis presents a method for improving order prioritization by utilizing readily available data to wholesale retail companies and a method for predicting the effectiveness of the new prioritization methodology utilizing historical data. By prioritizing orders that meet certain characteristics deemed to be in-line with company strategy and simulating multiple conditions, it is possible to deliver improved service on a specific set of orders. The impact of this work has been verified through a simulation model. The model was used to simulate three months of supply and demand and indicated a possible increase of 10-90% in the number of units made available to ship to specific marketplace segments.
by Ashton David Imlay.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
55 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Civil and Environmental Engineering.
Leaders for Global Operations Program.
Improving order prioritization for the allocation of constrained supply
Thesis
application/pdf
2019-10-11T22:24:19Z
Publication
Master
Sloan
CivEng
unknown
unknown
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<Abstract>For top wholesale retail companies, the demand for products from US-based customers (wholesale, digital, and direct to consumer) is extremely high. However, the available supply of a product is contingent upon the success of long-term forecasting, manufacturers across the globe, and intercontinental transportation. Therefore, there is not always enough supply to meet demand. In these situations, wholesale retailers must decide which orders to prioritize in the allocation of available supply. This thesis presents a method for improving order prioritization by utilizing readily available data to wholesale retail companies and a method for predicting the effectiveness of the new prioritization methodology utilizing historical data. By prioritizing orders that meet certain characteristics deemed to be in-line with company strategy and simulating multiple conditions, it is possible to deliver improved service on a specific set of orders. The impact of this work has been verified through a simulation model. The model was used to simulate three months of supply and demand and indicated a possible increase of 10-90% in the number of units made available to ship to specific marketplace segments.</Abstract>
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