A Case Study of Big Data Analytics Capability and the Impact of Cognitive Bias in a Global Manufacturing Organisation

Watts, Helen ORCID: https://orcid.org/0000-0002-8286-8764, Taroun, Abdulmaten and Jones, Richard (2024) A Case Study of Big Data Analytics Capability and the Impact of Cognitive Bias in a Global Manufacturing Organisation. In: Artificial Intelligence of Things (AIoT) for Productivity and Organizational Transition. Advances in Computational Intelligence and Robotics (ACIR) . IGI, Hershey, Pennsylvania, pp. 1-25. ISBN 9798369309933 • EISBN13: 9798369309940

Abstract

With the rise of big data analytics in recent years, organisations now have more data than ever before to make decisions. Whilst AI solutions are developing to aid big data decision making, employees continue to analyse big data introducing bias and variability into the process. This chapter details a case study examining the efficacy of the big data analytic capability (BDAC) model, and how it can be augmented to account for cognitive bias to improve the model's organisational value. Qualitative semi-structured interviews were conducted within a global data-driven manufacturing organisation. Thematic analysis elucidated that cognitive bias impacts decision making when analysing big data. This case study yields recommendations for a modified big data analytics capability model to recognise an additional sub-dimension under the ‘intangibles' dimension of ‘objective decision-making'. Implications for manufacturing organisations and the role of AI in both removing and adding bias are discussed.

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