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

Angappa Gunasekaran, Yahaya Y. Yusuf, Ezekiel O. Adeleye, Thanos Papadopoulos

Research output: Contribution to journalArticlepeer-review

83 Scopus citations


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 UK organisations, 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.

Original languageEnglish (US)
Pages (from-to)385-397
Number of pages13
JournalInternational Journal of Production Research
Issue number1-2
StatePublished - Jan 17 2018

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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