ESG Data: What Fund Managers Need to Know
This blog is the executive summary of our white paper “ESG Data: What Fund Managers Need to Know”. In the full paper, we set out to clear the confusion around ESG data and its applications, and aim to provide managers with a practical guide for navigating the dynamic ESG space. The full paper straightens common misconceptions, outlines different types of data, and gives recommendations for how to bring your ESG practices to the next level.
Christina Rehnberg, Senior Associate
In the past year, global society as we know it was fundamentally reshaped. The wildfires, pandemic, Black Lives Matter movement, and spread of misinformation, to name a few, highlighted the urgent need for action and innovation on more sustainable ways of working and living. This also resonated within economies and how investors view their portfolios. The events we all experienced in 2020 were perhaps the inevitable outcomes of past inaction and failure to price externalities effectively, and had already been brewing in the background for a while. Nonetheless, the challenges we face today are also sources of opportunities, and there are many reasons to be hopeful in 2021.
In this changing business environment, countries, companies, and investors are crafting their best courses of action. “If you can’t measure it, you can’t improve it”, said Peter Drucker famously about good business management, and the same applies to responsible investing irrespective of whether the focus is at the individual, corporate, national, or global level. For an asset manager, therefore, one of the most crucial challenges is the availability, accuracy, and transparency of data.
During the past decade, numerous data providers have emerged aiming to address the rapidly growing demand for data on environmental, social, and governance (“ESG”) issues. Since the underlying data is sparse and inconsistent and ESG ratings often disagree, there are opportunities to be seized for those who are informed, critical, and innovative in their use of the data. As ESG becomes more common, it may become harder to find alpha rather than beta from high level ratings and assessments based on self-reported data. Therefore, being creative in the use of alternative and unstructured data sources and conducting proprietary research could uncover material ESG events and new investment risks and opportunities. Take-Away
Anyone aiming to effectively integrate ESG into their investment process should assess the different means through which ESG information can be obtained. If third party data is used, it is crucial to understand the underlying methodologies and assumptions made by data providers and be aware of what signals realistically can be expected from the data. ESG data products may for example measure the quality of ESG disclosure, actual operational ESG, the ESG impact of products and services, or ESG sentiment, and as such, different data fits different approaches to responsible investing.Fund managers should then clearly define why and how they are using ESG information: Is the aim to identify and exclude, or short, companies with poor ESG practices that are unfit for a low carbon future? To discover those companies improving their license to operate? To factor in material operational risks that otherwise would have gone unnoticed? To include public sentiment in price movement predictions? To invest in companies that create positive ESG impact? To identify newer sources of alpha or alternative beta? Not all data fits all use cases, and therefore it is crucial to spend some time to define the purpose and the relation between ESG and different value drivers.Key Concepts
What are ESG issues? The E, S, and G factors can be broken down into more specific ESG issues that are relevant for a particular country or company. There are no ‘agreed’ naming conventions for ESG issues but reporting frameworks and industry initiatives offer their own categories that can be applied. Importantly, not all ESG issues are relevant for all investments and how you incorporate these into your investment process might depend on your investment thesis, strategy, asset class, and industry focus. Examples include: Environmental: Climate change risk exposure, water management, waste management, product lifecycle management, biodiversity, etc.Social: Talent attraction and retention, human rights, labour standards, diversity, data privacy and security, product safety, community relations, etc.Governance: Business ethics, board independence and diversity, ownership structure, political lobbying, executive pay, shareholder rights, director elections, etc.
What are ESG metrics? ESG metrics are the KPIs aiming to measure a specific ESG issue. The metrics can be both qualitative and quantitative in nature and, more often than not, they are backward looking and tend to measure ‘inputs’ rather than outcomes. For example, a binary metric showing whether or not a company has a diversity policy in place is a backward-looking measure of the input (or intention) of diversity performance of the company. It does not measure the quality of the policy, its outcome, or give an indication of improvement targets. Forward-looking metrics are still rare, but organisations such as FCLTGlobal, CECP, or the TCFD are pushing for this to change. Metrics at the country level tend to be on a government’s plans and national policies for sustainable development, lawsuits, and outcome metrics such as poverty rates, country emissions, or access to technology. Country level ESG data can be used to predict how countries may respond to shocks like Covid-19 or natural disasters. At the company level, there are no agreed global standards for which ESG metrics a company should disclose its performance on, and therefore most structured ESG data to date is based on self-reported sustainability disclosures or survey responses. Importantly, data providers are increasingly leveraging machine learning tools to collect data from NGO websites, sell-side reports, and news to construct ESG datasets based on metrics that are not self-reported. Compared to private firms, there is much more data readily available on publicly listed companies – partly because of listing requirements (on governance in particular), pressure from investors, and simply having more resources to be able to measure ESG performance. Most products from data providers therefore cover publicly listed companies.See, for example, the UN PRI for more guidance.What is Financial Materiality?There are many definitions of materiality, but in a nutshell, ESG issues are considered financially material if they are likely to have a significant impact on a company’s financial performance and if they are investment decision relevant. Being able to identify which ESG issues might be financially material and what metrics best capture that issue is crucial for managers aiming to integrate ESG into their investment process. For example, the Sustainability Accounting Standards Board (SASB) has created an industry specific Materiality Map to help guide investors when they are trying to understand materiality and managers may use this as a starting point. Many data providers have also developed their own ESG materiality frameworks, which guide the data collection and assessments.Snapshot of ESG Data Flows – Corporates
Where to begin?
When thinking about how to effectively integrate ESG data into the investment process, the manager should consider the following actions to start building the internal capabilities: 
The full paper covers the following:What ESG data is, in practiceCommon challenges with ESG dataThe latest global regulatory developmentsOverview of key ESG data providersWhat to ask a potential ESG data provider
Please get in touch at info@northpeakadvisory.com if you would like to have access to the full paper or discuss how you can spark lasting change within your firm.