Big Data Sustainability – An Environmental Management Systems Analogy

by Dennis D. Hirsch and Jonathan H. King

At this formative moment of mass big data adoption, we can learn from environmental management practices developed to manage negative externalities of the industrial revolution. Today, organizations globally wrestle with how to extract valuable insights from diverse data sets without invading privacy, causing discrimination, harming their brand or otherwise undermining the sustainability of their big data projects. Leaders in these organizations are thus asking: What is the right management approach for achieving big data’s many benefits while minimizing its potential pitfalls? Leveraging our analogy, we propose in this paper that adapting an Environmental Management System or “EMS” is a good reference model for organizations to consider for managing their big data developments.

We support our proposal by first further examining the utility of the analogy between the externalities of the information revolution and the industrial revolution. We then summarize the evolution of traditional environmental management from a siloed, command and control structure to a more collaborative, environmental management system approach. Finally, we argue why an environmental management system provides a good reference case for big data management.