Milton Friedman’s doctrine that a business’s only responsibility is to increase profits feels outdated in a world where the long-term environmental and societal impacts of unbridled capitalism cry out from news stories every day.
Many investors now demand that companies report on their ESG impact quarterly in the same way they report their financials. Governments are implementing regulations to ensure widespread reporting. The International Sustainability Standards Board is spearheading a global framework for emissions disclosure, while nations begin to mandate Modern Slavery reporting and Biodiversity risk reporting.
However, to be able to report your ESG impact, you need data, and it’s still extremely difficult to get objective data across a company’s supply chain. While you know the suppliers you buy from directly, you don’t know who they buy from, which carries all the way down the supply chain. You may believe you’re doing good by buying solar panels for your building, but your solar panels could be built by forced labour in China’s Xinjiang province, or through the exploitation of workers in the Amazon region of Ecuador.
In theory, you could ask your supplier to tell you who their suppliers are, and their suppliers, all the way down the supply chain for every product you buy, but it’s not scalable across thousands of products, and won’t stay up to date. As a result, businesses cobble together whatever data they can access and benchmark themselves against ESG risk scores from data providers which themselves are subjective and often conflict with other data providers’ scores – yes, it’s as complicated as it sounds.
Kim Randle, a human rights lawyer, encountered this problem when trying to seek objective data to help companies report on their Modern Slavery risk, and became determined to find a technology solution. In a moment of serendipity, she met Dr Arne Geschke, a world-renowned industrial mathematician specialised in using global trade data to understand climate risk. Kim inspired Arne with a mission to build the first-ever Modern Slavery footprint to help companies understand their risk up to ten tiers deep in their supply chain.
The result of this collaboration was FairSupply, a SaaS platform that provides objective data and insights to help companies understand and manage their exposure to ESG risks across their supply chain. The platform combines proprietary algorithms with data from public sources to help companies map out their exposure to risks including Modern Slavery, Carbon Emissions, and Biodiversity. These footprints allow companies to benchmark their performance, identify areas of risk, and re-architect their supply chain. Over time they want to extend their data sources and build new algorithms to help companies understand risk across all of the UN’s Sustainable Development Goals.
By allowing companies and investors to access objective data in a scalable way, they not only help companies report on risk but also evolve their supply chains to eliminate that risk.
When we invest at Series A, we’re looking for a team with complementary skills and a unique insight into the problem they’re solving, in a market that’s desperate for a solution. FairSupply ticks all those boxes — a human rights lawyer with a deep understanding of the customer combined with an industrial mathematician uniquely able to solve the problem, in a market where understanding the environmental and societal risk in your supply chain has suddenly become an urgent priority. We’re delighted to lead their Series A and help them accelerate the world’s transition to sustainable supply chains.