dc.contributor.advisor | Donald Rosenfield and Chris Caplice. | en_US |
dc.contributor.author | Riechel, Patrick | en_US |
dc.contributor.other | Leaders for Global Operations Program. | en_US |
dc.date.accessioned | 2012-09-27T15:28:53Z | |
dc.date.available | 2012-09-27T15:28:53Z | |
dc.date.copyright | 2012 | en_US |
dc.date.issued | 2012 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/73394 | |
dc.description | Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012. | en_US |
dc.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (p. 59-60). | en_US |
dc.description.abstract | This thesis addresses the question of how to optimize a distribution network when the supply chain has undergone an incremental change. A case study is presented for Company A, a major global biotechnology company that recently acquired a new manufacturing facility in Ireland. Company A already has international operations throughout Europe and the rest of the world through its network of 3rd party logistics providers, wholesalers, and distributors, as well as its own Benelux-based international distribution center. It now seeks to optimize its current network by taking into consideration the possibility of distributing product directly out of Ireland and by potentially outsourcing some of the distribution currently sourced from its Benelux facility. The thesis uses a phased approach to optimizing the network in order to tackle the common enterprise challenges of 1) building consensus around the solution and 2) simultaneously learning about the problem while attempting to solve it in order to meet a compressed project schedule. Through a number of simplifications, the thesis reduces the problem scope to a level that both enables the use of this phased approach and provides for a less-complex and less time-intense analysis manageable within the given time frame. The unique characteristics of the biotechnology industry drive the analysis to closely study direct effects of and potential risks to availability and lead-time of the various distribution options while trading off distribution, packaging, inventory, and capital expenditure costs. The recommendations resulting from the analysis described in this thesis are used to inform Company A's future distribution strategy regarding additional warehousing capacities, the continued use of the Benelux facility, as well as potential strategic partnerships with 3rd party logistics service providers. | en_US |
dc.description.statementofresponsibility | by Patrick Riechel. | en_US |
dc.format.extent | 60 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Sloan School of Management. | en_US |
dc.subject | Engineering Systems Division. | en_US |
dc.subject | Leaders for Global Operations Program. | en_US |
dc.title | A phased approach to distribution network optimization given incremental supply chain change | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.description.degree | M.B.A. | en_US |
dc.contributor.department | Leaders for Global Operations Program at MIT | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Engineering Systems Division | |
dc.contributor.department | Sloan School of Management | |
dc.identifier.oclc | 810126866 | en_US |