August 31, 2023
August 31, 2023
Data and Disclosure: The Current Challenges with Greenhouse Gas Emissions Data
August 31, 2023
SUSTAINABLE FINANCE SUMMIT | KEY TAKEAWAYS
While more companies and investors are increasingly able to understand the importance and relevance of Greenhouse Gas emissions, the data for Scope 3 emissions in particular isn’t where it needs to be able to avoid making evaluation of company performance difficult. At Morgan Stanley’s recent Sustainable Finance Summit, Varun Mehta, Head of Investment Management Sustainability Data & Technology, moderated a discussion between Andrew Ford (Vice President, Global Sustainable Finance at Morgan Stanley), Joe Allanson (EVP, Finance ESG, Salesforce) and Jessica Taylor (Head of ESG Client Engagement at S&P Global Sustainable1). Center to the discussion was the challenge of Scope 3 emissions data, how companies are responding, and the outlook for how this may change in the coming years.
Data-Standardization Process in Early Stages
With emissions reporting not required by most regulators globally, the environment is similar to financial analysis prior to the 1933 Securities Act. While the correlation between vendor data in Scopes 1-2 is fairly high, Scope 3 is more of a challenge and it’s also often the most material. There is much less disclosure available, and companies are still grappling with which categories of Scope 3 are material for their business. Regulatory bodies will be helpful in pushing this forward, but we are still in the very early innings.
Companies Face Challenges in Scope 3 Data
Getting organized has been much more challenging for companies than many realize, partially because there’s a tension within companies between the need to progress on reporting and the quality of the data that would allow this to happen. People want the ability to engage with data so it can get into the C suite and use it to drive better outcomes in a more real-time fashion. That is not where we are right now.
When data is unavailable or unreliable, estimates are often used by vendors and market participants. For direct emissions (Scopes 1 and 2) we have a view of the world economy and have estimation factors based on years of reported data. For Scope 3 emissions, econometric models similar to those used for tax modeling purposes can be helpful − for example, if you’re an auto manufacturer building cars, we can fairly accurately estimate the supply-chain needs such as lithium, copper, steel, etc. They are highly sophisticated models, but provide a good idea of likely upstream emissions. Downstream is significantly more challenging given the limited disclosures and need for granular product-specific emissions estimates.
Artificial Inteligence of Limited Help — For Now
While the promise of AI as a tool for gathering and interpreting Scope 3 emissions1 data is exciting, there are still hurdles. Reading and understanding the text around the data is critical, even with Scope 1 and Scope 2 emissions. Natural language processing is an area that can reduce some of the burden and time − for example, by scraping words like “NetZero target” − but even then, AI may have problems determining whether a company has set a target or is just talking about it as a theme.
Become Part of the Conversation
Most US companies are very concerned about greenwashing, greenwishing, greenhushing, etc. Owning the narrative is important because otherwise investors are going to make that assumption for you. Companies are increasingly using their core competencies to drive the greater good, but articulating the motivation and materiality remains a critical communications challenge.
Vice President, Global Sustainable Finance, Morgan Stanley