Dear ESG Vendor:
Having recently completed a comprehensive review of the ESG data offerings from most of the prominent ESG vendors, we want to share some of what we learned about the state of ESG research and data. These comments are not an evaluation of any one vendor. In fact, our evaluation determined that each vendor has strengths and weaknesses. Our hope is that the ESG research community can take these comments as a challenge to improve the availability and utility of data to the investment marketplace.
Ratings versus Raw Data: We don’t like black boxes. At Aperio, we value and are more likely to use raw data. We customize our evaluations of companies to match the interests and beliefs of our clients. By definition, ratings embed a perspective or bias and are therefore less useful to us. If you made the criteria for ratings construction completely transparent so that your ratings would be replicable, then we might be able to use them. Otherwise, we prefer not to use ratings in our process.
Company Coverage: We work in a global investment marketplace across the full range of market capitalization. Particularly for passive investors like Aperio, major holes in either country coverage or market-cap coverage can render a data set much less useful. Whether you are a broad-spectrum ESG research shop or specialize in a specific issue, we need a broad universe of coverage. Active managers might be able to use small data sets that fit their investment theses, but the marketplace and passive investors like Aperio need full coverage.
Missing Data: Missing data is a fact of life, so we’re not going to chastise you for holes in your data set. However, data may be missing for a number of different reasons, and accurate documentation for the user detailing why a particular piece of data is missing can be really helpful. Some reasons data may be missing include: it’s not disclosed by the company; it’s not considered “material” by the researcher (with potential added nuance regarding why it’s not material for a specific company); it’s never available in a specific market; a recent corporate action (merger, IPO, etc.) means there hasn’t been time for even an initial level of disclosure; the value is zero or null; or it is missing for some other reason. From a data use standpoint, the worst possibility is that a single coding for missing data may be used for more than one reason. Any rating of companies has to determine how it will address missing data in the evaluation. Your data sets need to incorporate appropriate methods for users like Aperio to understand what’s missing and why.
Global Data Sets and Research Criteria: Ideally, a data set will develop a consistent set of factors across a global universe of companies. Unfortunately, a global data set can generate a lot of missing data (see above). We live in a complex world, and while the goal might be to have completely consistent data across a global universe of companies, this isn’t always possible or helpful. Investors in different markets have different concerns (think racial and ethnic diversity concerns in the United States), so limiting data sets to those issues that can be covered globally may do a disservice to some investors. Because voluntarily disclosed information creates so much missing data, data sets that rely on mandatory disclosure, most frequently based on a regulatory requirement, can be very helpful in evaluating companies. Such a regulatory requirement, however, almost certainly means a lack of consistency across countries. As an example, US Environmental Protection Agency data has frequently been used as a source for data based on mandatory disclosure, but since it is not consistent with European or Asian equivalent data, it has been dropped from many data sets because it’s not global. Aperio recognizes the advantages of globally consistent data, but we don’t want to forgo robust data sets when they are additive, particularly in large markets. Given our suggested approach to labeling missing data (see above), we believe it would be possible to pull in important data sets that may be more local in structure.
Materiality: While not the most frequently used definition within the ESG investing space, at its core, materiality is really an analysis looking to determine the issues that have the most impact on a company. This approach raises a valid set of questions and some interesting analysis. However, a number of investors and other stakeholders are more interested in what impact the company is having on the issues. Data sets that use a materiality lens may be ignoring issues and data that are relevant to this second group of investors.
Lack of Company Disclosure: We know that the lack of data makes your job extremely difficult. Companies need to step up and provide more information that is useful in evaluating them in relation to ESG issues. Aperio’s approach to proxy voting consistently supports requests for corporate disclosure, and we encourage other investors, active and passive, to promote corporate transparency in any way they can.
One current relevant example on lack of company disclosure: very few companies disclose racial and gender demographic data regarding their workforces. They have the information; in the United States, they disclose this information annually to the federal government. What companies don’t do is disclose it publicly. Across a host of issues, but on this issue, particularly in the current moment, this lack of disclosure by companies of diversity data is unacceptable.
As a group, ESG vendors have pushed the field forward by prompting companies to make more information available, consolidating information into (relatively) easy-to-use data sets, and innovating when corporate disclosure isn’t complete. We look forward to further innovation in the field.
Aperio’s SRI Team
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