2026-09-19T18:28:25Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/452252026-06-06T01:03:38Zcom_1721.1_7582com_1721.1_7581com_1721.1_101402col_1721.1_131023col_1721.1_101610
Lawrence Lapide.
Jha, Ratan (Ratan Mohan)
Massachusetts Institute of Technology. Engineering Systems Division.
Massachusetts Institute of Technology. Engineering Systems Division
2009-04-29T17:11:15Z
2009-04-29T17:11:15Z
2008
2008
http://hdl.handle.net/1721.1/45225
304341829
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
74 leaves
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Engineering Systems Division.
Customer focused collaborative demand planning
Thesis
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