Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006. / Includes bibliographical references (leaves 73-75). / Globalization increases product variety and shortens product life cycles. These lead to an increase in demand uncertainty and variability. Outsourcing to low-cost countries increases supply lead-time and supply uncertainty and variability. Coupled with the increase of mergers and acquisitions, which increase supply chain complexity, and the unforgiving nature of having too little or too much inventory, these factors have accelerated the importance and adoption of the Sales and Operations Planning (S&OP) process. S&OP is driven by a cross functional team, with the purpose of balancing supply and demand with the objective of maximizing a company's goals. It manages the supply and demand uncertainties, balances the different internal and external stakeholders' interests, and aligns the operations towards its strategy and vision. In support of the Supply Chain 2020 Project at MIT, this thesis focuses on analyzing the S&OP function across industries. Using the Phase I SC 2020 theses, literature, white papers, and interviews with industry experts, this thesis compares and contrasts the S&OP practices across nine industries. / (cont.) It examines their best practices and underlying principles, as well as the macro factors that have shaped the practices for the last ten to fifteen years, as well as what is expected in the future. Companies with the "best" S&OP processes collaborate internally to balance sales and operations, and align all internal stakeholders' interests. Furthermore, they collaborate externally with suppliers and customers to reduce supply and demand uncertainties. They also understand and manage demand and supply uncertainties, and align their effort towards their goals. These companies synchronize operations and are agile to changing environments. / by Peng Kuan Tan. / M.Eng.in Logistics
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/36139 |
| Date | January 2006 |
| Creators | Tan, Peng Kuan |
| Contributors | Larry Lapide., Massachusetts Institute of Technology. Engineering Systems Division., Massachusetts Institute of Technology. Engineering Systems Division. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 75 leaves, application/pdf |
| Rights | 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 |
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