By Anna Hawley and Jeff Shen, PhD
In the view of many, ESG investing is concessional in order to achieve the bottom line. Our history shows that this is not true and that unique ESG data can be predictors of business results. Sustainability goals and environmental, social and governance (“ESG”) metrics are no longer new concepts as they become more mainstream investment topics. Investors, companies and regulators are increasingly struggling to understand why investments with positive ESG attributes are important to mainstream. However, they might still struggle to get better ESG results or know what ESG-related information is needed to make the right investment decisions. In this overview, Anna Hawley and Jeff Shen reveal why ESG and future profitability are linked, and how big data can help investors understand which companies could outperform their peers over the long term.
An inflection point for ESG
Currently, there is no single standard for how ESG information should be analyzed and disclosed. For this reason, investors tend to rely heavily on generalized ESG “scores” provided by a handful of providers. The scores, however, have very little consistency across vendors, and none of them validate the link to business performance on the E, S, or G dimension. In order to gain a deeper and more sophisticated understanding of the ESG-related alpha drivers, investors are increasingly leveraging big data and artificial intelligence to collect and analyze ESG information. While ESG scores provide a static view, alternative data provides more dimensions of information. Technology and innovation become the key to a successful sustainable investment.
Similar to our observation with big data in 2008, sustainability insights benefit investment decisions by predicting company fundamentals without the need to rely on traditional data sources. ESG-related data also provides a distinct way to capture how companies, across every sector and industry, are innovating and adapting to thrive as the economy moves towards carbon neutrality. This is just one of many powerful alpha opportunities that can be uncovered through the analysis of ESG data.
The ESG is on the verge of a major inflection point. Now, investors are able to measure sustainability at a much deeper level than simple filters based on value judgments. The availability of new datasets and the ability to uniquely measure sustainability has contributed to increased demand for ESG-sensitive investments.
As systematic investors, we test and validate each insight through a rigorous research process, similar to scientific methods. It helps to see unfounded environmental friendliness and past baseline ESG ratings. Most importantly, this science-based approach demands that results are grounded in sound economic theory and that every investment decision adds up to a portfolio.
The ESG “prism”
ESG objectives are not just about investing in companies that promote the best environmental, societal and governance outcomes. On the contrary, looking at the investment universe from the point of view of an ESG prism provides investors with an even more comprehensive framework for identifying companies best positioned for future long-term profitability and, therefore, alpha opportunities for investors.
The ESG prism highlights four key components to assess companies on: risk mitigation, human capital, society and transition. Companies aligned with these ESG goals prioritize these areas, and data can help investors predict which companies are doing this most effectively.
Risk mitigation insights seek to identify – and avoid – business pitfalls. Related data includes, but is not limited to, controversial information, information flow, cyber defense data, and fiscal transparency.
Human capital the insights reflect the impact of employee well-being on engagement and productivity. Related data includes, but is not limited to, employee sentiment, diversity and benefits statistics.
Company ideas focus on improving social outcomes that also impact financial results. Related data includes, but is not limited to, social policies and ESG information.
Transition the overviews identify how businesses are preparing for the post-transition economy. Related data includes, but is not limited to, carbon and water efficiency, FEMA research, and environmental innovation information.
ESG data, in practice
Take the “E” in ESG, for example. While it may not be obvious, a company’s strong environmental policies could have long-term benefits on its bottom line as it strives to thrive in a post-transition economy. While one might assume that the opposite is true – that companies that disregard environmental policies have lower overhead costs – ESG and profitability are inextricably linked. Looking below the surface, our data and analysis confirmed a clear link.
An example that illustrates the impact of companies’ environmental policies on their bottom line is the LEED data on leadership in energy and environmental design. How does LEED certification data influence returns? Companies that occupy LEED-certified buildings tend to consume less energy, use renewable materials, and incorporate better construction methods into their buildings. Overall energy efficiency translates into lower operating costs.
Companies that seek LEED certifications also tend to be run more efficiently. This thinking often permeates many aspects of an organization, and LEED data helps us identify it. effective behavior which has far-reaching implications for a company’s profitability potential.
This combination of using big data and scientific analytical methods to identify ESG-aligned profitability is how BlackRock’s Systematic Active Equity (SAE) team manages our series of Advantage funds. We invest in alpha wherever we find it and strongly believe that successful businesses need to evolve and adapt to a changing world and a transitioning economy.
Identify changemakers and future winners
An important distinction to make is that analyzing ESG data is about finding relative differences – selecting companies in each sector that show better metrics on those ESG dimensions than their peers. ESG integration does not mean in the future a complete exclusion of oil companies and other companies with an impact on the environment. Oil companies will still exist in 2050, but their businesses will need to evolve into something that is consistent with an ESG conscious future. While no one can know for sure what these types of businesses will look like 20 or 30 years from now, we can leverage the data we have today to identify which ones have the best potential to thrive over the long term. SAE’s data-driven processes allow us to examine more attributes for more companies, uncovering more alpha opportunities in unique ways. For funds whose investment objective includes the integration of ESG criteria, there may be corporate actions or other situations that may cause the fund to passively hold securities which may not meet ESG criteria.
The main thing about double result is that investors don’t have to compromise on performance to achieve sustainable results. ESG data is an indicator of future performance potential and should be integrated into the investment mosaic of all the different types of data used to predict performance. Sustainability and financial profitability are inextricably linked, and the goal is to understand which companies will win in the long run. This is where the alpha is.
This post originally appeared on iShares Market Insights
Editor’s note: The summary bullet points for this article were chosen by the Seeking Alpha editors.