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As ESG criteria become increasingly important denominators among the investment community, specific metrics for measuring ESG performance are coming to the fore. But with such a broad range of issues falling under the ESG remit, investors should be considering a wider set of metrics, many of which are much harder to quantify.
The growing importance of environmental, social, and governance (ESG) criteria to the investment community is undeniable. A quick run down of the stats shows that globally, the percentage of retail and institutional investors that apply ESG principles to a quarter or more of their portfolios jumped from 48% in 2017 to 75% in 2019. In 2018, sustainable investing assets totalled $14.1trn in Europe and $12trn in the United States. By 2025 ESG assets in the US are expected to hit $35trn.
With so much value being placed on sustainable investing, investors need accurate ways to measure ESG performance, and identify ESG risks to inform the investment process. By doing so, they hope to identify companies likely to see good financial performance in the long-term due to their ESG-focused business models. Because impact investing gets results. A report by BofA Merrill Lynch revealed that a portfolio based on buying stocks in companies ranking well against various ESG metrics would have beaten the broader market by 3% every year for the last five.
Which is why investors need to identify the best ESG performers when constructing their investment strategy. One route is through the voluntary GRI Sustainability Reporting Standards, established in 2016 by the Global Reporting Initiative to support best practice in impact disclosure. Covering topics from tax to emissions, anticorruption, biodiversity and occupational health and safety, they aim to offer a flexible framework for creating integrated ESG reports.
More recently, in September 2020, the World Economic Forum (WEF) released a set of ‘stakeholder capitalism metrics’, designed to assist in the benchmarking of sustainable business performance. The metrics are centred on four pillars, encompassing a number of ESG factors:
The WEF is encouraging businesses to include a full set of metrics in their corporate and financial reporting, but some of these areas currently carry more weight with investors than others. These are generally the most easily measurable, and therefore mostly likely to be included in annual reports, and covered by mainstream media. According to surveys by IHS Markit, seven of the top ESG metrics commonly sought by PE fund investors are:
While the above metrics are being widely employed, and the WEF guidance represents a much-needed route to defining broader ESG metrics, measurement, and quality of ESG data remains an issue. Self-disclosure, encouraged by the WEF, is a recipe for inconsistency, subjectivity, and opacity. There are many areas of ESG activity that aren’t represented in easily reportable figures, don’t have generally accepted measurement criteria, or which defy clear definition. They don’t generate a pithy soundbite to include in annual reports, or statistics to present to the board. There is no neat package for complete ESG reporting.
Furthermore, the importance and prevalence of different areas of ESG activity varies from sector to sector and indeed from company to company. Part of the reason the above metrics are popular with investors is because they are more or less uniformly applicable across the majority of industries. There is clearly value in this, but it runs the risk of oversimplifying ESG reporting to just what can easily and consistently be measured, rather than what actually matters.
Consequently, there is a need for other tracking measures, both for investors and so that companies can understand their own position on ESG. Such metrics should seek to incorporate the following characteristics to close the current reporting gap:
Such a system by its very nature would need to reflect the reality of ever-shifting perspectives real-time analysis of publicly available print, online, broadcast, and social media content to derive an ESG score. To increase robustness, the scores could be indexed against a benchmark such as the Sustainability Accounting Standards Board (SASB) standard taxonomy.
To achieve an effective analysis of this volume of data would require the use of machine learning and natural language processing (NLP) technology.
Through such a system, a reliable, objective overview of ESG risk and potential can be delivered to shareholders to inform investment decisions.