Redistributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective

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Abstract

Digitalization and the growth of big data promise greater customization as well as change in how manufacturing is distributed. Yet, challenges arise in applying these new approaches in consumer goods industries that often emphasize mass production and extended supply chains. We build a conceptual framework to explore whether big data combined with new manufacturing technologies can facilitate redistributed manufacturing (RDM). Through analysis of 24 consumer goods industry cases using primary and secondary data, we investigated evolving manufacturing configurations, their underlying drivers, the role of big data applications, and their impact on the redistribution of manufacturing. We find some applications of RDM concepts, although in other cases existing manufacturing configurations are leveraged for high volume consumer goods products through big data analytics and market segmentation. The analysis indicates that the framework put forward in the paper has broader value in organizing thinking about emerging interrelationships between big data and manufacturing.

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Zaki, M., Theodoulidis, B., Shapira, P., Neely, A., & Tepel, M. F. (2019). Redistributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective. Production Planning and Control, 30(7), 568–581. https://doi.org/10.1080/09537287.2018.1540068

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