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dc.contributor.advisorLawrence Lapide.en_US
dc.contributor.authorJha, Ratan (Ratan Mohan)en_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2009-04-29T17:11:15Z
dc.date.available2009-04-29T17:11:15Z
dc.date.copyright2008en_US
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/45225
dc.descriptionThesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.en_US
dc.descriptionIncludes bibliographical references (leaf 74).en_US
dc.description.abstractMany 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.en_US
dc.description.statementofresponsibilityby Ratan Jha.en_US
dc.format.extent74 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.titleCustomer focused collaborative demand planningen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.in Logisticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc304341829en_US


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