Agile manufacturing practices: the role of big data and business analytics with multiple case studies

Gunasekaran, Angappa, Yusuf, Yahaya orcid iconORCID: 0000-0001-6045-3245, Adeleye, Ezekiel O. and Papadopoulos, Thanos (2017) Agile manufacturing practices: the role of big data and business analytics with multiple case studies. International Journal of Production Research, 56 (1-2). pp. 385-397. ISSN 0020-7543

[thumbnail of Author Accepted Manuscript]
Preview
PDF (Author Accepted Manuscript) - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

373kB

Official URL: https://doi.org/10.1080/00207543.2017.1395488

Abstract

The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four U.K. organizations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes.


Repository Staff Only: item control page