Managing a Big Data project: The case of Ramco Cements Limited

被引:149
作者
Dutta, Debprotim [1 ,2 ]
Bose, Indranil [1 ]
机构
[1] Indian Inst Management Calcutta, Kolkata 700104, India
[2] Amazon India, Bangalore 560055, Karnataka, India
关键词
Big Data analytics; Cement industry; Data driven decision making; Manufacturing; Outbound logistics; Visualization; SUPPLY CHAIN; INFORMATION; ERP; INTELLIGENCE; INTEGRATION; ANALYTICS; QUALITY; TRENDS;
D O I
10.1016/j.ijpe.2014.12.032
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Currently many organizations are in the process of implementing Big Data related projects in order to extract meaningful insights from their data for better decision making. Though there are various frameworks postulating the best practices which should be adopted while implementing analytics projects, they do not cater to the complexities associated with a Big Data project. In this paper our goal is two-fold: to develop a new framework that can provide organizations a holistic roadmap in conceptualizing, planning and successfully implementing Big Data projects and to validate this framework through our observation of a descriptive case study of an organization that has implemented such a project. Although the manufacturing sector has been slow in incorporating analytics in their strategic decision making, the situation is changing with increasing use of analytics for product development, operations and logistics. We explore the Big Data project at a manufacturing company, Ramco Cements Limited, India, describe the system developed by them and highlight the benefits accrued from it. We investigate the entire process by which the project is implemented using the lens of our proposed framework. Our results reveal that a clear understanding of the business problem, a detailed and well planned step-by-step project map, a cross functional project team, adoption of innovative visualization techniques, patronage and active involvement of top management and a culture of data driven decision making are essential for the success of a Big Data project. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:293 / 306
页数:14
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