With Sustainability Analytics, Big Data Can Save the World
In the coming years, environmental, social, and corporate governance (ESG) data will be as central to making business decisions as financial and marketing data is today. Pressure from regulatory agencies and consumers alike will require brands and manufacturers to accurately report and substantiate the environmental and social impact of their products across the supply chain. This is a scary thought for many companies because, frankly, getting accurate data from raw materials partners, manufacturing partners, logistics partners, and other players in the value chain can feel like the corporate equivalent of herding cats.
The same can hold for many manufacturing facilities and other value chain partners: without a clear understanding of why data is requested and proper incentives, it’s difficult to get the data you need to support accurate and actionable sustainability insights. Hopefully, the day isn’t far off when demonstrating lower environmental and social impact will become a competitive differentiator for manufacturers and other value chain partners, but to get there it will take strong relationships to make decisions based on shared data around carbon emissions, energy consumption, wastewater, and other data points. In the meantime, however, companies need to approach ESG data collection and collation strategically.
5 Things You Can Do Right Now to Sustain the Momentum
Sustainability analytics requires a lot of data from many different sources. Some of that data already exists and is standardized, while other data is coming from new sources with no established standards. In order for companies to collect and organize ESG data in a meaningful and efficient way, I recommend that companies start doing five things as they begin building out their sustainability insights platform.
1. Focus on the problem you’re trying to solve. This sounds obvious, but there is a massive potential for sustainability analytics to become too big to handle. Identify which issues and impacts are your priority and focus on that data first. If your goal is to reduce carbon emissions, identify your biggest energy users and take the time to understand the improvement opportunities. If your goal is to reduce water consumption, understand how water-usage data is gathered from your supply chain partners and the ways that water is used in their facilities.
2. Don’t collect data without context. There’s a tendency to assume that data alone is useful, but it can be difficult to analyze when taken out of context. For example, measuring energy use alone won’t help if you don’t understand how energy is purchased and used in a facilityand how that supports processes. Targeting your data collection based on identified hotspots helps to focus your efforts on areas that matter, and helps to prioritize reduction efforts.
