Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 56). / The oil and gas industry is characterized by unpredictable boom and busts cycles. Companies must manage capacity to be able to quickly meet increasing demand during boom cycles and survive when oil prices go down. During this time, companies resort to in-house sourcing ("Make") or buying externally ("Buy") from suppliers, whichever is rational. Since 2014, the oil field services industry has been in a period of recession, and oil prices have dropped significantly. The company's sourcing team asked us to analyze the Make-vs.-Buy scenarios. Our research has two primary objectives. First, to provide a methodical understanding of key Make-vs.-Buy decision factors for optimized capacity management during an upturn. Second, to develop a 2x2 assessment model that can assist in making the Make-vs.-Buy decision once the recession is over and prices have returned to a normal index. We interviewed research company personnel to get a better sense of their hypotheses: first, quantities ordered vary with boom/bust cycles; second, external pricing rises during boom cycles and falls during bust cycles; third, internal sourcing has a unified price that does not change with the boom/bust cycle. We tested the company's hypotheses with a limited set of product data but could not verify them. To better assess the situation, we researched the factors considered by theorists when making a Make-vs.- Buy decision. Based on this research, we identified four assessment criteria -- strategic, technological, market and economic factors -- that are intrinsic as well as extrinsic to the company throughout the entire decision making process. Furthermore, we created a model to test boom and bust circumstances and provide a better testing mechanism for boom and bust cycles. / by Akansha Nidhi and Fady Riad. / M. Eng. in Supply Chain Management
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/112862 |
| Date | January 2017 |
| Creators | Nidhi, Akansha, Riad, Fady |
| Contributors | Bruce C Arntzen., Massachusetts Institute of Technology. Supply Chain Management Program., Massachusetts Institute of Technology. Supply Chain Management Program. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 56 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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