Data driven management in Industry 4.0: a method to measure Data Productivity

Abstract In the early 1900s, together with the birth of mass production, modern managerial approaches were conceived, under the motto “you can’t manage what you don’t measure”. Since then, operations managers throughout the world had been getting used to measure the productivity of materials, machines and workers to control and improve their own businesses. Nowadays, in the Industry 4.0 era, the emphasis is shifting toward data, under the new motto “data is the new oil”. Despite many managers pledging allegiance to the principles of data driven decision making, still no comprehensive approach exists to measure how good a company is at exploiting the potential of its own information assets; in other words, no “data productivity” measure exists. In this paper, we present a first method to define and measure data productivity. Relying on a comprehensive literature review, and inspired by the traditional OEE framework, this new method brings some innovative perspectives. First, data productivity is broken into data availability, quality and performance of the decision-making process using those data. Second, it includes both technical and organizational factors, helping companies to evaluate their current level of productivity, and actions to improve it. The model has been tested through three cases studies and it results as effectively implementable. The results obtained from its application reflect the expectations of companies’ managers accelerating the cultural shift needed to fully express the potential of Industry 4.0.