Vendor-managed Inventory forecast optimization and integration
Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.
| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2009
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| Online Access: | http://hdl.handle.net/1721.1/45231 |
| _version_ | 1826201149937549312 |
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| author | Kou, Xihang |
| author2 | Lawrence Lapide. |
| author_facet | Lawrence Lapide. Kou, Xihang |
| author_sort | Kou, Xihang |
| collection | MIT |
| description | Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. |
| first_indexed | 2024-09-23T11:47:00Z |
| format | Thesis |
| id | mit-1721.1/45231 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:47:00Z |
| publishDate | 2009 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/452312019-04-10T14:52:47Z Vendor-managed Inventory forecast optimization and integration VMI forecast optimization and integration Kou, Xihang Lawrence Lapide. Massachusetts Institute of Technology. Engineering Systems Division. Massachusetts Institute of Technology. Engineering Systems Division. Engineering Systems Division. Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. Includes bibliographical references (leaves 59-60). In the retail industry, consumer package goods (CPG) manufacturers have been working with retailers to use Vendor-managed Inventory (VMI) to improve the overall supply chain inventory turns and finished product velocity. This thesis explores those opportunities where a consumer packaged goods company can benefit from using VMI information to improve forecasting. First, this thesis discusses a novel way to compare those forecasts at downstream and upstream demand planning levels. Forecast errors are calculated in relation to the forecast data aggregation levels. Second, a causal model is used to analyze the contributing factors of high demand planning forecast. Finally, recommendations are provided on how to use VMI information and thus incorporate VMI forecasts into the upstream supply chain planning process. by Xihang Kou. M.Eng.in Logistics 2009-04-29T17:12:08Z 2009-04-29T17:12:08Z 2008 2008 Thesis http://hdl.handle.net/1721.1/45231 304398331 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 60 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Engineering Systems Division. Kou, Xihang Vendor-managed Inventory forecast optimization and integration |
| title | Vendor-managed Inventory forecast optimization and integration |
| title_full | Vendor-managed Inventory forecast optimization and integration |
| title_fullStr | Vendor-managed Inventory forecast optimization and integration |
| title_full_unstemmed | Vendor-managed Inventory forecast optimization and integration |
| title_short | Vendor-managed Inventory forecast optimization and integration |
| title_sort | vendor managed inventory forecast optimization and integration |
| topic | Engineering Systems Division. |
| url | http://hdl.handle.net/1721.1/45231 |
| work_keys_str_mv | AT kouxihang vendormanagedinventoryforecastoptimizationandintegration AT kouxihang vmiforecastoptimizationandintegration |