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Value stream financial modeling for improved production decision making

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dc.contributor.advisor Roy Welsch and David Simchi-Levi. en_US
dc.contributor.author Hopkins, Christopher Warren en_US
dc.contributor.other Leaders for Global Operations Program. en_US
dc.date.accessioned 2011-09-27T18:39:53Z
dc.date.available 2011-09-27T18:39:53Z
dc.date.copyright 2011 en_US
dc.date.issued 2011 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/66074
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, 2011. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 78-79). en_US
dc.description.abstract Understanding the overall impact of a decision in a manufacturing system can be challenging given the complex production and financial structures in today's companies. While knowing the direct result of a local change may be easy, anticipating the real impact to the rest of the business can be difficult. Nonetheless, managers are faced with this dilemma on a regular basis as they try to support the larger organization, taking appropriate actions as best they can. Based on a project at Novartis Vaccines and Diagnostics for an influenza vaccine, this thesis helps address some of the key questions managers face. It discusses a technique for more accurately determining the implications of these common manufacturing decisions: * How much should be spent to improve a particular component? * What are the impacts of expanding into new markets? " Which parameters in the factory most deserve managerial attention? * What are the appropriate tradeoffs to make when deciding on materials purchasing? Using concepts from throughput accounting, a model is developed from a detailed cost structure analysis, linking the financial and production aspects of the system. Whenever a parameter is changed, the model simulates how the rest of the system would perform through a linear program that replicates the production scheduling process. Thus, a manager is able to experiment with the tool in order to observe the overall impact of the change being considered and levy a decision based on the anticipated costs and benefits projected by the model. As a result, managers can distribute resources in a more efficient manner and align decision making throughout the organization. This thesis discusses the modeling approach, historical validation and initial insights for the current system. It also covers techniques for future applications and identifies the underlying organizational challenges that must be addressed to achieve a global optimum. en_US
dc.description.statementofresponsibility by Christopher Warren Hopkins. en_US
dc.format.extent 86 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 Value stream financial modeling for improved production decision making 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 Sloan School of Management. en_US
dc.contributor.department Massachusetts Institute of Technology. Engineering Systems Division. en_US
dc.contributor.department Leaders for Global Operations Program. en_US
dc.identifier.oclc 753711279 en_US


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