Value of Smart Data for Supply Chain Decisions in a Data Rich, Uncertain World

Abstract

Data-driven decisions are becoming increasingly relevant for supply chains as traditional paradigms are being replaced with concepts and approaches more suited for the advent of big data. However, the prevailing consensus is that companies are struggling to cope with an overabundance of data, which presents the following pertinent question: how to efficiently analyze data applying filters of relevance and insightfulness to make effective decisions? There is currently a lack of research focus on providing quantitative tools to do such analyses. This paper, besides offering thoughts on decision-making uncertainty in a digital sup- ply chain context, describes an approach to address the research gap. The ap- proach (which involves developing a quantitative model) is further elucidated by utilizing an example in the agricultural supply chain that illustrates how value of data can be quantified by measuring the performance impact of insights delivered using uncertainty reduction as the leverage.