Week 47: Better ESG Data Is Not Going to Save The World
Sasja Beslik
Chief Investment Strategy Officer @ SDG Impact Japan | Economics, Business, Asset Management
Dear all,
Many in the financial industry argue that the numbers are all-important. When discussing mainstream finance, decisions are consistently guided by the numbers, which reflect the expected risks and returns.
This involves data, definitions and established procedures that dictate how to calculate value and expectations. With this perspective, it's only logical that sustainable investing has evolved into a data-driven industry.
But what if the most crucial numbers needed are unavailable? What if we lack the conventions and definitions that are customary in 'normal' finance? What if we simply do not have the right data?
I’d say that this leads to erroneous choices, a haphazard approach, overlooking vital elements, and relying on backward-looking investment styles. If we don’t have better data, we simply must have more common sense.
This newsletter has become quite long. Next time I try to keep it shorter (no promises!). At the end you find some of the news from the last weeks.
What is the data we look for?
Imagine you reckon the world needs a bit of sprucing up, and you fancy harnessing the might of money to make that happen. Splendid notion! You might seek out top-notch ideas, companies, and investment prospects that, through their innovations, practices, or processes, edge us closer to this noble aspiration. It's reasonable, isn't it? Yet, sustainable finance doesn't quite operate along these lines.
It's not about ideas or intentions; it's all about DATA! Data serves as a stand-in for ideas and intentions, or so they claim. If your investment goal is risk-return, using data is crystal clear. However, when it comes to sustainability, you definitely need more.
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Having been in sustainable finance for some time now, I've encountered a fair amount of data concerning sustainability and the various approaches one can adopt. It's no longer just about using data to enable investing for a better world; it's about risk management, compliance, reporting, and occasionally an endeavour to channel capital towards a sustainable purpose.
Here 's a brief overview of ESG approaches from George Serafeim, but there are also other methodologies. In general, finding the right data isn't exactly a walk in the park. With numerous providers, varied definitions, data gaps, and ever-evolving regulations, it often rather feels like aiming at a moving target.
In my view, the myriad types of data and their utilisation in Sustainable Finance can be categorised as follows:
Frequently, these approaches or requirements tend to be muddled. While one might champion a best-in-class oil company (ignoring the risk of it becoming a stranded asset), crafting an ESG best-in-class fund could involve numerous polluting industries (accompanied, perhaps, by pledges of improvement).
However, the same cannot be said based on impact data. Nevertheless, it's not always evident (depending on the data source) what positive impact these companies truly make. Some argue that every company generates a positive impact by creating jobs (SDG 8) while conveniently overlooking the negative repercussions.
Moreover, there are several issues associated with all these types of data. The lack of uniform definitions (resulting in varying data across providers), frequent reliance on proxies instead of actual data, subjective and inconsistent measurement methods, and occasional absence of data for entire portfolios pose significant challenges.
I won't delve into all these problems here. On a related note, ?the EU is actively addressing some of these issues surrounding diverse climate data.
There is no better excuse than data
Let's revisit the application of data and the initial concept of sustainable finance, which, as mentioned earlier, aims for a more sustainable world. One would anticipate that using ESG data facilitates the identification of such investments.
However, the reality is, not surprisingly, often quite different. According to Jan Fichtner, Robin Jaspert and Johannes Petry, the majority of listed ESG funds, constituting the lion's share of sustainable finance, channel capital towards almost the same companies as a non-sustainable benchmark. Therefore, ESG data is primarily employed for categories 1 and 4 in the aforementioned list and, to a lesser extent, category 2.
Moreover, they argue that the concentration in the data services industry (ESG providers) results in peculiar effects and interdependencies, exacerbated by the absence of regulation (see figure). Asset owners pay fees to asset managers, who in turn pay fees to ESG providers for the use of their ESG indices/benchmarks or ratings.
ESG providers are responsible for rating companies, while asset managers are tasked with maximizing returns based on the mandate set by asset owners. However, if they must restrict the investment universe (as dictated by data from ESG providers due to the mandate), this limitation might negatively impact performance. Consequently, both asset owners and asset managers have a more or less vested interest in maintaining some ambiguity about what the data truly indicates.
However, given their sustainable mandate, they are obliged to demonstrate some form of commitment. Here’s a few convenient excuses that you often hear:
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Indeed, all valid points, when viewed from a traditional market perspective.
What does the actual data tell?
A nice paper by Sakis Kotsantonis and George Sarafeim tells the actual data story. Their most important conclusions:
There is much more to it. In addition to ESG data, there is also impact data. This data measures the impact of product and services on society, typically expressed in the contribution to (objectives) of the Sustainable Development Goals (SDGs).
This implies often (but not always!) that for instance solar panels or wind turbine manufacturers get a high score, as well as pharmaceutical companies. Typically, the fossil fuel industry has a low score. These data have the same problems as ESG data: no uniform definition, measurement problems, and inconsistencies.
And this is only in the area where we have the best data available: listed companies. Part of the problems will be overcome in the coming years by standard-setting (such as PCAF for carbon), regulation (CSRD for example). But then, we have large parts of banking activities where data is hard to get: SME bank finance, private debt and equity, venture capital, et cetera.
And since there is no data available, anyone can claim almost everything.
Why better ESG data is not the answer
This last sentence is important. While incorrect or incomplete data give a false sense of knowing what you are doing, no data might also not be the solution. How to proceed?
It has been argued for a long time that “What gets measured gets managed — even when it’s pointless to measure and manage it, and even if it harms the purpose of the organisation to do so”.
While we scrutinize and steer based on data, achieving some predefined targets often misses the mark. I contend that solely focusing on enhancing existing ESG or impact data practices is not the solution, for three reasons.
Firstly, we typically fail to establish boundaries or thresholds, thus allowing compensation for bad behaviour. Average ESG or impact scores offer an incomplete narrative, as it's possible to offset poor ecological performance with commendable social or governance practices. Even worse, we may tolerate ESG risks deemed not 'financially material' – a term from financial sector parlance denoting issues that may not harm financial performance but are inherently undesirable (e.g., harming the environment or people or lacking proper governance).
Only by evaluating distinct elements separately from an inside-out perspective (assessing the investment's impact on the external world) can we derive meaningful insights into its sustainability impact. (For the experts: yes, this embodies double materiality, but when investing for a better world, focusing on inside-out criteria should be the primary selection criterion.)
Secondly, all data is retrospective, focusing on past ESG or impact performance. It's akin to investing in a company solely based on historical results – a practice no investor would endorse. Analysts typically extrapolate future return potential based on past performance. Why is this not the norm with sustainability data? It makes little sense to predict future contributions to a better world solely based on past information.
Thirdly, and interconnected, most ESG data merely outlines relative performance compared to a benchmark. Essentially, this doesn't assert that a company is doing well but rather, most of the time (especially regarding ecological aspects), doing less harm than the average.
Doing less harm, however, falls short of doing good. Impact data tell a slightly different story, illustrating the contribution of products and services to (achieving) a better world. For example, electric vehicles, solar panels, and wind turbines represent solutions in the energy transition. However, this does not tell anything about the contribution to a future state of the world.
We need better data to save the world
If we aim to use data to safeguard the world, we require new data – data that guides us towards where we need to be, not where we've been. We need data that informs investors about where they can maximise the impact of their money. How do we achieve this? I believe, akin to 'conventional' investing, a structured approach is necessary:
Then, invest. Not in ESG, but in future impact. Undoubtedly, this is challenging. But if we lack the right data to save the world, we should place more trust in our values and instincts rather than relying on inadequate data.
Other news, apart from many reports in the run-up to COP28:
Nevertheless, have a good week!
Take care,
Hans
Environmental, Social and Climate Change Risk Manager | Santander Corporate & Investment Banking
11 个月The ESG ratings usually are a "tick the box" process for investors, asset managers, investment banks that don't rely on robust internal processes and teams. Of course, as data providers there could be value in the information that is gathered and made accessible for those with sufficient budgets to hire these services. But, be aware of the details and methodologies!!! A company with bad performance in "environmental management", for example, can simply "offset" any downgrade in its "ESG rating" by putting more women on its board. Or, pursue an ISO 14001 certification in case there is a serious mismanagement of human rights in the supply chain.
Founder of Zero Ideas | Board member at WePlanet | ex Co-lead of climate and sustainability at Oliver Wyman | ex Chief Stategy Officer at Lippincott
11 个月Thanks for the insights Sasja Beslik and Hans Stegeman. At Responsible Investor’s RI USA 2023 conference in New York this month there were reassuringly widespread observations that we are over-relying on reporting as a way to drive change, with all the drawbacks you highlight. I was particularly struck by someone from the ESG reporting team at Chevron describing the data complexities they face: how the numbers for fracking operations are different from those for liquefied natural gas, and how it will take years for them to get it all together. I can’t blame them – I am sure they’re right, given the system we are operating. But do we need such data complexity to know what we need to know about Chevron? And on blurring risk and impact data. If the world were on track for 1.5C, the two might generally coincide: Pursuing a strategy not aligned with 1.5C would risk stranded assets, loss of customers etc. This is the win-win ESG argument that encourages the blurring. But as we increasingly diverge from 1.5C, the lowest risk strategy may be to position the business for the slower-transition future world we expect, not the 1.5C world we want – so a risk-driven approach will increasingly diverge from an impact-driven one.
Managing Partner at MS Innovation Lab
11 个月Sasja Beslik ... i suggest reading Nicholas Georgescu-Roegen
ESG and impact specialist
11 个月Thank you for sharing this. It describes well many of the headaches we have. I did not conceptualize the four data categories in that manner in my thoughts. I view impact data as?data with a minimum quality requirement (coming from impact assessment theory) applicable to all decision-oriented data (thus the 3 other categories) because those are in fact portraying some sort of impact - although in an incomplete or inconsistent way. However, this perspective sheds light on the practical utilization of data and its broad acceptance in such contexts. Your conclusion is giving encouraging perspective in a race for data quality that lacks purpose and longer term vision.
Partner Deloitte Spanish Latam, Sustainability and Climate Change - My comments in this network express personal views / 17k followers.
11 个月Thanks Hans. Very good insights and a lot to think about the future of ESG data.