Customer focused collaborative demand planning
Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2009
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| Online Access: | http://hdl.handle.net/1721.1/45225 |
| _version_ | 1826195372670713856 |
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| author | Jha, Ratan (Ratan Mohan) |
| author2 | Lawrence Lapide. |
| author_facet | Lawrence Lapide. Jha, Ratan (Ratan Mohan) |
| author_sort | Jha, Ratan (Ratan Mohan) |
| collection | MIT |
| description | Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. |
| first_indexed | 2024-09-23T10:11:38Z |
| format | Thesis |
| id | mit-1721.1/45225 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:11:38Z |
| publishDate | 2009 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/452252019-04-10T14:52:39Z Customer focused collaborative demand planning Jha, Ratan (Ratan Mohan) 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 (leaf 74). Many firms worldwide have adopted the process of Sales & Operations Planning (S&OP) process where internal departments within a firm collaborate with each other to generate a demand forecast. In a collaborative demand planning process buyers and sellers collaborate with each other to generate a mutually agreed upon forecast which takes into account the needs and limitations of both buyers and sellers. In this research we concentrate on finding out the value from both statistical and qualitative forecasts. We apply standard forecasting algorithms to generate a statistical forecast. We also generate a hybrid model that is a weighted technique using both a statistical and qualitative forecast. Then we evaluate the statistical, hybrid, and qualitative collaborative forecasts using an error analysis methodology. Finally we recommend an approach for forecasting a family of items based on our analysis and results. We also recommend changes to the existing process so that our recommendations on the forecasting approach can get seamlessly integrated into the overall process. by Ratan Jha. M.Eng.in Logistics 2009-04-29T17:11:15Z 2009-04-29T17:11:15Z 2008 2008 Thesis http://hdl.handle.net/1721.1/45225 304341829 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 74 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Engineering Systems Division. Jha, Ratan (Ratan Mohan) Customer focused collaborative demand planning |
| title | Customer focused collaborative demand planning |
| title_full | Customer focused collaborative demand planning |
| title_fullStr | Customer focused collaborative demand planning |
| title_full_unstemmed | Customer focused collaborative demand planning |
| title_short | Customer focused collaborative demand planning |
| title_sort | customer focused collaborative demand planning |
| topic | Engineering Systems Division. |
| url | http://hdl.handle.net/1721.1/45225 |
| work_keys_str_mv | AT jharatanratanmohan customerfocusedcollaborativedemandplanning |