A measurement model of value of data for decision-making in the digital era

Ganesh Sankaran, Martin Knahl, Guido Siestrup and Ismini Vasileiou

International Journal of Integrated Supply Management, 2021, vol. 14, issue 1, 50-76

Abstract: Despite burgeoning opportunities for data-driven decisions, research shows that decision makers are failing to make sense of data within a broader context of organisational change which presents the following pertinent questions: 1) How can decision makers measure the value of data by giving a holistic account?; 2) How should the organisation-specific blending of machine and human rationality be factored in the measurement model? This study tackles these questions by proposing a novel approach that combines system dynamics and the ability to incorporate data science methods. In addition to a conceptual description, this paper also describes a feasibility test conducted on a small-scale prototype set in a supply chain context. The results show that the use of sophisticated models that have a local scope ('locally rational') might have unintended global consequences. It underscores the need for a holistic model in the decision makers' toolkit providing the ability to run targeted simulations to assess digital investments.

Keywords: digital technologies; digital transformation; data-driven decisions; big data; quantifying value of data; bounded rationality; system dynamics; human-AI collaboration; supply chain management. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisma:v:14:y:2021:i:1:p:50-76

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