New sustainability reporting directives have already rolled out in the EU, and the SEC is expected to announce its own rules in 2024. That means having a strong ESG data foundation is no longer optional. Patrick McCarthy of Precisely attempts to help companies get their arms around the data governance challenges ahead.
Editor’s note: Patrick McCarthy, author of this article, is chief revenue officer at Precisely, a software company specializing in data integrity tools.
The ESG movement is now at an inflection point, with reporting efforts shifting from a largely voluntary exercise to being needed to meet regulatory standards. The shift has already begun in the European Union, which recently strengthened its disclosure requirements to ensure investors and other stakeholders have access to the sustainability information they need to assess investment risks. The SEC isn’t far behind with its own disclosure requirements expected in 2024 — and surveys suggest companies intend to comply with the delayed rules regardless of when they become final.
But the basics of ESG reporting are universally challenging. A Deloitte survey of more than 3,000 professionals found that less than half (46%) said they were confident in the ability of their organizations’ financial reporting teams to gather and report on ESG metrics for regulatory compliance purposes. As regulations take hold, ESG is firmly moving into the compliance realm and organizations need to ensure they are ready, particularly with regard to the underlying data used to inform ESG reporting.
ESG data challenges
The biggest risk identified by the Deloitte poll was data collection and integrity. This is hardly surprising. ESG is complex, multi-dimensional and constantly evolving, which makes data management an enormous task. ESG data encompasses a wide range of metrics, including carbon emissions, water usage, waste management, labor practices, board diversity and executive compensation. Each of these metrics requires distinct types of data, ranging from self-reported data to third-party assessments.
Several metrics are hard to quantify due to their complex and nuanced nature. For example, measuring the social impact of a company’s activities, such as its contribution to community development, employee well-being and local empowerment, can be difficult. Metrics related to employee engagement and job satisfaction involve capturing subjective experiences and emotions, making them challenging to quantify accurately.
Even reporting scientific metrics like greenhouse gas emissions (GHG) can be arduous. To get a complete picture of an organization’s carbon footprint, three types of emissions need to be measured: those produced by the organization’s own facilities and vehicles; those associated with purchased electricity; and all other upstream and downstream emissions, including those generated by suppliers and distributors.
The diverse requirements for emissions tracking and reporting mean ESG data is typically sourced from various upstream channels, both internal and external. Because the data comes in diverse formats that require custom curation, validation and storage, aggregation challenges are unavoidable.
On top of that, different, and sometimes conflicting, sustainability reporting standards can complicate data collection efforts. This is particularly true when a company has operations across several regions and needs to report under more than one standard.
Preparing data for ESG reporting
First and foremost, a data infrastructure must have the ability to integrate all data sources, no matter where data is coming from or in what format. This is easier said than done, as most large organizations use multiple operating platforms and have siloed data across various third parties. Accessing data from all sources and seeing it in a centralized location is a challenge that data integration addresses and is essential for ESG reporting.
This also means not only reviewing the GHG emissions from a business’ own facilities but aggregating the data from their suppliers, shippers and other third parties for a holistic view. Beyond that, having a single view into data throughout an entire organization can support leaders in making decisions that provide benefits to the business as a whole, including operational efficiencies, reduced costs, increased innovation and improved brand reputation, all of which contribute to sustainable growth over time.
As ESG reporting becomes a foundational requirement of business operations, it is also vital to consider the governance and controls needed. This could include building additional processes and technology-based controls directly into the ESG reporting process to further substantiate accuracy in data collection, report build-out or review.
Given the numerous sources of information, organizations have to implement quality control measures to identify and rectify inconsistencies, outliers and errors in the data. In traditional data infrastructure systems, cleaning data can be a tedious process. However, there are tools that automate the data validation process.
Sustainability data needs to be treated and governed with a similar level of rigor as other strategic data, like financials, sales and customer data. The challenges of ESG reporting are only going to grow to meet the demanding requirements of new regulations in Europe and in the U.S. The stakes are high for companies, as noncompliance with sustainability regulations can become a board liability and present reputational risk. The goal is to get started now and build an appropriate ESG reporting and disclosure foundation for your organization.