In a recent PPI presentation, Mark Spearman and Phil Kaminsky weighed in on the differences and applications of operations science and data science. They spoke about how both seek to explain how a
complex world works and referenced IBM’s definition of data science: “Data science is a multidisciplinary approach to extracting actionable insights from the large and ever-increasing volumes of data collected and created by today’s organizations.” They also explained operations science is the science that describes the behavior of operations. They then proposed that operations science be used to model, analyze, optimize, and better understand the production system, while data science should be used to analyze complex data, in real time, to gain insight into the production system’s behavior.