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dc.contributor.advisorJeanne W. Ross.en_US
dc.contributor.authorYildirim, Cem, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2017-03-10T15:06:19Z
dc.date.available2017-03-10T15:06:19Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/107344
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, System Design and Management Program, 2014.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 44-45).en_US
dc.description.abstractToday's digital business environment is imposing a great transformation challenge on the enterprises to effectively use vast amount data in order to gain critical business insights to stay competitive. In their aim to take advantage of data many large organizations are launching data management programs. In these attempts organizations recognize that taking full advantage of data requires enterprise wide changes in organizational aspects, business processes, and technology. The lack of recognition of this enterprise-wide scope haunts most data management programs. Research shows that most of these programs fail and get abandoned after long efforts and investments. This study aims to highlight critical reasons why these programs fail and a different approach to address the fundamental problems associated with the majority of these failures. It is important to be successful in the data efforts due to the fact that data driven businesses are gaining significant competitive edge. Data Centric Business Transformation Strategy (DCBT) is a holistic approach for the enterprise to transform into a data driven and agile entity. DCBT is also away to achieve better alignment in the enterprises. DCBT aims to achieve two goals to transform the organization; become a smarter organization by instilling continuous learning and improvement culture in all aspects of the business and achieve agility in enterprise-wide organizational learning and technology. To achieve these two goals, understanding the current state of the organization in the tree fundamental DCBT areas of organizational learning capacity, business processes and technology is essential to incrementally and continuously improve each one in concert. Required improvements should be introduced to smaller parts of the organization delivering the value of data. Strategically chosen pipeline of projects would allow the ramp up of the organization to a continuously learning and changing organization. In the age of digital economy, agile organizations can learn quicker from large amounts of data to have the competitive edge. This study will also look into how a data management program relates to DCBT and can be used in concert to enable DCBT.en_US
dc.description.statementofresponsibilityby Cem Yildirim.en_US
dc.format.extent45 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectSystem Design and Management Program.en_US
dc.subjectEngineering Systems Division.en_US
dc.titleData-Centric Business Transformationen_US
dc.title.alternativeDCBTen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.identifier.oclc972910875en_US


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