Data-driven operations management: organisational implications of the digital transformation in industrial practice

被引:174
作者
Goelzer, Philipp [1 ]
Fritzsche, Albrecht [1 ]
机构
[1] Friedrich Alexander Univ Erlangen Nurnberg FAU, Nurnberg, Germany
关键词
Big Data; operations; Industry; 4.0; BIG DATA; INFORMATION-SYSTEMS; INNOVATION; COMMUNICATION; CHALLENGES; ANALYTICS;
D O I
10.1080/09537287.2017.1375148
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The ongoing digital transformation on industry has so far mostly been studied from the perspective of cyber-physical systems solutions as drivers of change. In this paper, we turn the focus to the changes in data management resulting from the introduction of new digital technologies in industry. So far, data processing activities in operations management have usually been organised according to the existing business structures inside and in-between companies. With increasing importance of Big Data in the context of the digital transformation, the opposite will be the case: business structures will evolve based on the potential to develop value streams offered on the basis of new data processing solutions. Based on a review of the extant literature, we identify the general different fields of action for operations management related to data processing. In particular, we explore the impact of Big Data on industrial operations and its organisational implications.
引用
收藏
页码:1332 / 1343
页数:12
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