Attending the Private Equity focused Responsible Investment Forum in New York, it was clear that investors, both General Partners (GPs) and Limited Partners (LPs), want to know more about the supply chains of the companies in which they invest. The majority in the room however, indicated that gathering and interpreting supply chain data was an onerous and almost impossible task.
The challenge of understanding the risk that may lie in a company’s supply chain is manageable, but when you consider that LPs invest in numerous GPs, who in turn invest in tens or even hundreds of companies - each with extensive, global supply chains made up of thousands of suppliers - you can understand the challenges associated with the volume of data that would need to be analyzed.
LPs are asking that risk is mitigated and managed in the most cost and time effective manner, and that the management teams of the companies being invested in are aware of and capable to manage the risks that may be lurking in their supply chains. ESG risks can come in many forms and typically vary by geography and sector, so the challenge for investors is finding a way to be thorough during diligence and through the hold period, recognizing that the process must be efficient and not unduly inhibit the transaction, nor the company’s management team.
One LP managing a large North American endowment noted that proxies for supply chain risk, nuanced by sector and geography, are the most effective way to identify potential risks and ensure the management team both at the GP and company level have a plan to manage, mitigate and report these risks, should they surface.
This approach aligns with our thinking on this topic. At Anthesis we work extensively with companies to identify risk and opportunity in their supply chains, however we recognize the need for a more efficient and aggregated approach when supporting investors. Our proprietary software tool, RiskHorizon™ which was showcased at the Responsible Investment Forum in New York last month, takes this sector and geography-level view to aggregating potential risk factors .
By way of example, we have used this to identify risk in the cotton supply chain. Using Country of Origin data and educated estimates, the environmental, social and geo-political risks were mapped out. Strategies for mitigating identified risks – using certified cotton or restricting sourcing from particular countries – could then be assessed using this lens.