SKU clustering for supply chain planning efficiency
Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, February 2016. (Axel Barbará).
| Main Authors: | , |
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/103735 |
| _version_ | 1826213381453905920 |
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| author | Barbará, Axel (Axel Nahuel) Dominguez Molet, Tomás |
| author2 | Edgar Blanco. |
| author_facet | Edgar Blanco. Barbará, Axel (Axel Nahuel) Dominguez Molet, Tomás |
| author_sort | Barbará, Axel (Axel Nahuel) |
| collection | MIT |
| description | Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, February 2016. (Axel Barbará). |
| first_indexed | 2024-09-23T15:48:11Z |
| format | Thesis |
| id | mit-1721.1/103735 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:48:11Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1037352019-04-12T11:35:11Z SKU clustering for supply chain planning efficiency Stock Keeping Uint clustering for supply chain planning efficiency Barbará, Axel (Axel Nahuel) Dominguez Molet, Tomás Edgar Blanco. MIT Supply Chain Management Program. Massachusetts Institute of Technology. Engineering Systems Division. MIT Supply Chain Management Program. Engineering Systems Division. MIT Supply Chain Management Program. Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, February 2016. (Axel Barbará). Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, June 2015. (Tomás Dominguez Molet). Cataloged from PDF version of thesis. Includes bibliographical references (page 54). Globalized companies seek growth while dealing with more complex and compelling challenges such as economic volatility, fluctuating commodity prices, supply-chain inefficiencies and increasing customer expectations. While companies cannot control all of these challenges, there is much they can do to remain competitive. Companies can gain competitive edge through improved demand forecasting and efficient inventory management. SKU segmentation is a concept that intends to demonstrate that there is a economic benefit behind treating and handling some products differently from another. Our thesis optimized SKU segmentation for a global CPG and restaurant brand. This aided inventory managers and supply planners adequately assess the varying needs of diverse products, to cluster them according to comparable needs, to reduce supply chain costs and optimize their supply chain. To explore this problem, we analyzed 53 weeks of forecast and demand data for over 15,000 SKUs. Utilizing a variety of clustering techniques, we identified a more cost-effective clustering strategy for the subject case. We analyzed the comparative costs between our theoretical classification and the actual classification used by the subject case study. Once we identified the disconnect, we calculated the incurred costs for being out of the optimal solution. This included both the effect of safety stock and the stock out costs. Our research created new insights into the comparable cost of under-forecasting and over-forecasting on safety stock and customer service level. by Axel Barbará and Tomás Dominguez Molet. M. Eng. in Logistics 2016-07-18T20:05:11Z 2016-07-18T20:05:11Z 2015 2015 Thesis http://hdl.handle.net/1721.1/103735 953455550 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 54 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Engineering Systems Division. MIT Supply Chain Management Program. Barbará, Axel (Axel Nahuel) Dominguez Molet, Tomás SKU clustering for supply chain planning efficiency |
| title | SKU clustering for supply chain planning efficiency |
| title_full | SKU clustering for supply chain planning efficiency |
| title_fullStr | SKU clustering for supply chain planning efficiency |
| title_full_unstemmed | SKU clustering for supply chain planning efficiency |
| title_short | SKU clustering for supply chain planning efficiency |
| title_sort | sku clustering for supply chain planning efficiency |
| topic | Engineering Systems Division. MIT Supply Chain Management Program. |
| url | http://hdl.handle.net/1721.1/103735 |
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