Have you heard the phrase “big data is the new oil”? It’s true in the sense that data, like oil, is a critical resource on which society depends. But it’s also true in the sense that big data, like big oil, can generate major, if unintended, negative impacts. While big oil produces oil spills, smog, and climate change, big data can lead to data spills, privacy violations, identity pollution, and harmful discrimination.
So what is the right management approach to take advantage of big data’s many benefits while minimizing its potential pitfalls, and ensure big data sustainability? Join me in this first of three posts that will first illustrate the nature of big data and big data sustainability and then examine possible enivronmental management strategies gleaned from lessons learned by traditional industry.
Download the paper Big Data Sustainability: An Environmental Management Systems Analogy
Managing the risks of data analytics
It can be hard for organizational leaders to see through the hype of big data, let alone properly manage potential negative impacts. It is unclear whether any given project may have more risks than benefits or whether big data concerns are just a more complicated “Y2K” over-exaggeration.
A true story helps to illustrate the challenge that data analytics companies face today. inBloom was a non-profit financed by USD 100 million in Gates Foundation and Carnegie Corporation funding. inBloom sought to collect student data from public school districts across the country, develop analytics-based educational recommendations for individual students, and then funnel the recommendations to classroom dashboards.
Teachers would then use the recommendations to provide their students with more personalized education. Sounds great, right? But inBloom soon ran into problems.
Data collection security and its pitfalls
Parents of the school children worried that the 400 fields of data inBloom was collecting about students—including information on family violence, student disabilities, and other topics—might become attached to their children as they moved through life and constrain their educational and employment opportunities. The parents grew concerned about who else would gain access to this data, either when inBloom intentionally shared it or if inBloom suffered from a data security breach. Parents began to protest. First school districts, and then entire states, refused to share student information with inBloom.
Deprived of the data that it needed to operate, this promising, well-intentioned initiative shut itself down.
Learning big data sustainability from smokestack industries
The inBloom story, and the business difficulties that it illustrates, bear a strong resemblance to the challenges that smokestack industries have faced on the environmental front. Here, too, beneficial business activities create significant externalities (real or perceived) that engender public opposition and become a constraint on further industrial development.
Companies have made substantial progress with environmental management. Some of the same firms that once polluted with abandon now prioritize environmental compliance and have adopted sustainability as part of their core mission. Others have gone beyond compliance and found ways to turn environmental performance into competitive advantage by making more environmentally friendly products, building trust in their brand, and reducing regulatory costs.
Benefit from environmentally conscious strategy
And the same goes with big data. Leaders who are tasked today with implementing big data projects and technologies can benefit from the very same environmentally conscious strategies and management practices.
Article written with Prof. Dennis Hirsch.