dc.contributor.advisor | Jeanne W. Ross. | en_US |
dc.contributor.author | Yildirim, Cem, S.M. Massachusetts Institute of Technology | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Engineering Systems Division. | en_US |
dc.date.accessioned | 2017-03-10T15:06:19Z | |
dc.date.available | 2017-03-10T15:06:19Z | |
dc.date.copyright | 2014 | en_US |
dc.date.issued | 2014 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/107344 | |
dc.description | Thesis: 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.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 44-45). | en_US |
dc.description.abstract | Today'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.statementofresponsibility | by Cem Yildirim. | en_US |
dc.format.extent | 45 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Institute for Data, Systems, and Society. | en_US |
dc.subject | System Design and Management Program. | en_US |
dc.subject | Engineering Systems Division. | en_US |
dc.title | Data-Centric Business Transformation | en_US |
dc.title.alternative | DCBT | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. in Engineering and Management | en_US |
dc.contributor.department | System Design and Management Program. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Engineering Systems Division | |
dc.contributor.department | Massachusetts Institute of Technology. Institute for Data, Systems, and Society | |
dc.identifier.oclc | 972910875 | en_US |