SI Dilemma: Do we need perfect ESG data?

The challenge that sustainable investors have is that we want to be sure that we invest in sustainable companies – as well as get financial returns – while also being able to measure the impact (positive or negative) that these companies have on the world. A tall order.

In this discussion, we often fail to acknowledge that the origins of sustainable investing long predate the easy availability of ESG data. The first ‘ethical’ mutual funds are believed to have emerged in 1971 in the US and in 1984 in the UK. ESG indices started taking off in the 1990s (MSCI, Sustainalytics, and then DJSI in 1999), while the Global Reporting Initiative encouraging companies to report publicly on non-financial issues was founded in 1997.

Accessible ESG data came even later – MSCI ESG Ratings launched in 1999, Trucost Carbon Intelligence in 2000, and Bloomberg ESG Solutions in 2006. Even the term ‘ESG integration’ is believed to have been coined only in 2005, a year before the UN Principles for Responsible Investment launched. So, investors have been investing according to their non-financial goals for a long time, doing their own research and making decisions based on the knowledge available to them.

Today, most companies publish a sustainability report, investors have a wealth of ESG information at their fingertips, and the alternative data market is exploding, particularly in the area of natural language processing and geospatial data. In comparison with the turn of the century, we are overwhelmed with data, and regulation will likely drive an avalanche of additional company reporting in the next few years.

We are therefore undoubtedly able to make better-informed decisions today than we have been able to at any time in the past. But too much data could even create new challenges, making it more difficult for investors to identify the most important indicators amid all the noise.

Environmental and social data is often compared unfavorably to financial data. Critics point to global accounting standards, stock exchange listing rules, regulatory requirements for financial statements to be audited, and severe penalties for accounting fraud as reasons why financial data is superior to non-financial E and S data.

However, financial data is not perfect either. There are enough examples of accounting fraud to know that if companies want to hide information, they will, and many get away with it. We only hear about the cases that are discovered.

It is certainly true that the environmental and social metrics are harder to measure than cash flows. Differences in measurement definitions and the intangible nature of many environmental metrics mean mistakes and inconsistencies are likely, and comparability between measurements from different companies is hard.

However, even financial information has issues. Investment analysts always need to adjust their valuation models to reflect different business decisions around, for example, capital structure and acquisitions, to fully understand how one company is performing versus another. Standardized accounts do not present the whole picture.

Additionally, fundamental investors do not make decisions based solely on financial statements anyway. The financial numbers only tell us what happened in the past. More interesting is the company’s strategic outlook – what are their plans for next year; what do they see happening in their company and industry?

Investors also want to know how the industry is likely to evolve and how peers are behaving. They want insights into what employees and customers think of the company in order to assess how likely it is that the management will execute their strategy and achieve their goals to create future value.

The same is true for ESG data. Backward-looking metrics only give us a starting point, and more research is needed to predict the future. This is the job of investment analysts, and it is an art, not a science.

Another criticism of ESG data is that ESG ratings are not in agreement. However, this is based on a misunderstanding of what ratings are, and how they should be used. A rating is a subjective opinion, not an objective datapoint. The opinion might be based on different underlying beliefs of the most important ESG issues, or whether financial materiality or sustainability impact is more important.

Again, we can compare ESG ratings to traditional investment recommendations to see the same dynamic at play. Investment analysts looking at a company all have the same financial information to start from, but they do not all arrive at the same investment recommendation.

Asset management (buy-side research) analysts know this, and do not take broker recommendations (sell-side research) at face value. They use the different insights to enhance their own research and arrive at better-informed decisions. Users of ESG ratings need to ensure they understand the rating methodology to ensure they are using the information in an appropriate way.

Sustainable investors have been dealing with imperfect data for years. Investors who can work with the messiness of environmental and social data have an advantage over those who sit and wait for the data to become perfect. How much data is ‘enough’ depends on the extent to which any investment strategy commits to incorporate and report on sustainable and impact considerations.

Minority investors always face the challenge of never knowing everything about an investment, so they have to estimate and make assumptions in order to predict the future performance of an investee company. This applies to both traditional and sustainable investing.

However, expectations of ESG data and strategies seem unrealistic sometimes – why are portfolio managers of sustainable funds who experience a ‘controversy’ in their portfolio criticized more than portfolio managers who experience a profit warning from one of their holdings? Given the general belief that financial data is superior to ESG data, the opposite should be true!

Ultimately, all data is only a tool for investment decisions, whether financial or non-financial, and interpretation of the data is much more important. Trying to forecast the future is, by definition, going to mean that some will get it wrong.

We must not lose sight of the aim of sustainable investing – to channel capital into sustainable economic activities, by investing in sustainable companies that will deliver financial returns and have a positive impact on the world. The collection of data in itself is not the end goal, and the pursuit of perfect data must not be an excuse for inaction.