Why the new ESG stories must be grounded in data

By Lyons O’Keeffe, ESG Director at IQ-EQ

Cynics have suggested that as money has poured into ESG investment over the last decade, companies and investors have rushed to take advantage and in doing so, willfully misrepresented their credentials.

But this overly simplistic view ignores the good intentions behind this flow of capital, unfairly maligning companies and managers. I believe the majority of ‘greenwashing’ cases are down to over-enthusiasm and the nascency of the space, rather than conspiracy. Wherever you sit on the spectrum – from ESG sceptic to evangelist – it cannot be denied that the last decade has marked a sea change in how we consider the impact of investments on people and the planet. This can only be welcomed.

While there have certainly been instances of clumsy claims, there was initially very little guidance to determine which companies and investment products could fairly say they were ‘doing good’. And around the world, regulators are still grappling with this question. Just this month the UK’s Financial Conduct Authority (FCA) welcomed a consultation aimed at creating a draft code of conduct for ESG data and ratings providers. This follows news earlier this year in which MSCI – a major data provider – stripped hundreds of its funds of their ESG credentials, as part of a push to tighten up its own criteria.

Investee companies and asset managers are wisely moving to a new stage in their thinking: how can they take a perceived qualitative good and turn it into a provable and standardised data story that can be used to report, benchmark, and measure progress? This self-motivated demand for rigour means the new ESG stories are being sourced from data, not marketing brainstorms.

Yet given the millions of proof points that can be used to support ESG investment strategies, the task at hand can seem overwhelming. We can draw inspiration from the way in which nations, regulators, and global companies worked together during the 20^th century to agree international accounting standards – a common language we take for granted today. This historical perspective could potentially shed light on the development and evolution of ESG data standards.

But to understand where we’re going, it is best to start with where we are – and the easiest way to look at this is to break ESG down into its respective ‘subheadings’: E, S, and G. Many argue that governance data is the easiest to tackle as it primarily involves hard information such as board composition, policies, adherence to laws, regulations, and sanctions. However, understanding and quantifying the culture of a company, also a key part of governance, can prove much more challenging.

Environmental data brings its own hurdles, particularly requirements to report on Scope 3 emissions: these relate to supply chains, and often account for a large majority of firms’ carbon output. Likewise, nature loss risks (eg arising from water scarcity, pollution, biodiversity loss, and resource over-exploitation) tend to not be well understood by organisations.

Compared to environmental and governance data, social data tends to be much less developed, more subjective, and less scrutinised. Measuring social impacts accurately, including factors like placemaking or community cohesion, can be hugely complex.

The complexity outlined above tends to result in very poor fulfillment rates when investors request ESG data from companies – especially smaller companies. Imagine running a small scale-up and having a general partner (GP) ask you 100 questions around topics like the use of renewable energy in your supply chain. Firms simply don’t have the capacity, meaning the portion of questions meaningfully responded to is very low. In many cases it's not simply a matter of gathering existing data; rather, it requires active data generation.

The solution to all this is part art, part science. The human component should not be overlooked. Managers who select the right specialist partners can hone in on the right questions to ask, therefore obtaining the right information for regulator and stakeholder communication. Only humans possess the flexible brainpower and industry nous to ask the right questions and generate meaningful outcomes. Crucially, they can also provide context and explain the rationale behind the questions being asked. Combine this with good data collection and workflow technology and the challenge can be effectively met.

This brings us onto the hard data, ‘science’ side of the equation. As scrutiny on greenwashing grows, it is imperative managers have data to hand to back up their claims. For instance, if a fund claims to reduce carbon emissions annually, they must ensure that carbon-related inquiries are directed to the portfolio companies. This way, the manager can report back with utter confidence that they have achieved their goals. Standardised metrics and unified reporting technology also enable meaningful benchmarking, comparison, and healthy competition between companies. The aim is to demonstrate the portfolio's results and ultimately showcase continuous improvement over time.

ESG professionals often find themselves consumed by regulatory compliance, data collection, and anxieties surrounding these aspects. This can limit their ability to delve into strategic portfolio improvements and innovative sustainability initiatives. Technology can help create time for these professionals to engage in data interpretation, decarbonisation efforts, impactful transformations and activism. Ultimately, our aim is to create an environment where responsible business practices thrive, and ESG professionals are empowered to make a lasting impact.