Big Data Sustainability: An Environmental Management Systems Analogy
14 Pages Posted: 18 Jan 2016 Last revised: 1 Jun 2016
Date Written: December 10, 2015
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 management approach should businesses employ to sustainably achieve the tremendous benefits of big data analytics while minimizing the potential negative externalities?
In this paper we argue that leaders can learn from environmental management practices developed to manage the negative externalities of the industrial revolution. First we show that, along with its many benefits, big data can create negative externalities that are structurally similar to environmental pollution. This suggests that management strategies to enhance environmental performance could provide a useful model for businesses seeking to sustainably develop their personal data assets. Second, we chronicle environmental management’s historical progression from a back-end, siloed approach to a more collaborative and pro-active “environmental management system” approach. An approach modeled after environmental management systems – a Big Data Management System approach – offers a more effective model for managing data analytics operations to prevent negative externalities. Finally, we show that a Big Data Management System approach aligns with: A) Agile software development and Dev Ops practices that companies use to develop and maintain big data applications, B) best practices in Privacy by Design and engineering and C) emerging trends in organizational management theory. At this critical, formative moment when organizations begin to leverage personal data to revolutionary ends, we can readily learn from environmental management systems to embrace sustainable big data management from the outset.
Keywords: Big Data, Privacy, Data Protection, Analytics, Governance, Management, Environment, Dev Ops, Agile Development, Privacy By Design, Lean
Suggested Citation: Suggested Citation