The Importance of ESG Reporting Data Quality

ESG reporting is becoming increasingly important as investors, consumers, and other stakeholders place greater emphasis on a company’s social and environmental impact. As a result, the collection of high-quality, reliable data is the most crucial aspect of ESG reporting, as poor data quality can lead to a misrepresentation of a company’s performance and can negatively impact investment decisions. Gathering this high-quality ESG data also presents a challenge for firms due to the lack of standardization in the data and reporting framework landscape and the lack of consistency in the definitions of ESG itself. Navigating these challenges from the start in order to mitigate the risks associated with inaccurately reported data down the line is the most important first step in a company’s sustainability journey.

Raw data sourcing and acquisition processes for environmental and climate-related data portions of ESG are particularly important due to the quantitative nature of this data. Environmental data points are the most actionable, auditable, and comparable across firms for policymakers and investors. When it comes to climate-related data, insurers and wealth and asset management companies generally regard the lack of available relevant data as the single greatest challenge preventing them from adequately addressing climate risk. Understanding companies’ true performance on ESG issues through quality data inputs is important for investors seeking to mitigate risk, identify drivers of long-term performance, or invest according to their preferences. Questionable data wouldn’t be acceptable with financial metrics; nor should firms have to accept inaccurate, unaudited, out-of-date, incomplete and biased data in the ESG realm as a snapshot of company performance.

Benefits of high-quality ESG data

High-quality data can assist with decision-making, as it provides a clear and accurate picture of a company’s performance in areas related to the environment, society, and governance. Internally, regularly monitored environmental data may reveal inefficiencies when it comes to facility-level energy use and areas for improvement on sustainability metrics that can lead to cost savings. Additionally, high-quality ESG data can enhance transparency and accountability, which can improve a company’s reputation and brand image. Successful investing is heavily reliant on high-quality data inputs, something that holds particularly true in ESG investing. The abundance of incomplete or inaccurate data and greenwashing in the reporting space ensures that firms taking the time to provide accurate metrics will be seen as high-value investments and industry leaders.

The costs & challenges associated with poor ESG data

Costs from poor data quality can accumulate in financial and operational processes from wasted resource time on manual data entry methods and from missed revenue opportunities associated with investor interest or energy efficiency losses. Poor ESG metrics can make it difficult to attract valuable investment as the liabilities may be viewed as too high.
Misrepresentation of a company’s performance and inconsistent data outputs can lead to reduced credibility and trust in the company or accusations of greenwashing that may lead to legal trouble.
ESG data is often collected in a backwards-looking manner given the extended timelines of corporate reporting. Assessments of ESG performance rate the organization on where it was at a point in time incentivizing firms to use a one-and-done approach to data collection. With environmental data especially, this eliminates the tangible value of collecting actionable data in the first place, which is using ongoing & operationalized sustainability data capture to improve efficiency and meet sustainability goals such as net zero in the long run.
Firms that do not have comprehensive and traceable environmental data may be unable to independently verify data for compliance purposes and may have issues in transferring data across platforms for reporting.

Who is using ESG data and requiring the data to meet certain standards?

An ecosystem of specialists who interpret ESG primary data continues to develop. It includes data collectors, reporting framework entities that systematically collect corporate disclosures and attempt to independently verify the data, and data providers that collect ESG data in order to score or rate corporates on their ESG performance. Examples of these data providers include Sustainalytics, MSCI, and S&P Global.
Insurance companies will increasingly use ESG data associated with climate risk mitigation to help policyholders avoid problems or to secure insurance coverage
In asset and wealth management, where demand for ESG investment products continues to soar, more sophisticated ESG data enables firms to offer new funds, portfolio management services, and support for DIY investors
Private equity and venture capital firms providing the funding for early-stage and growing businesses increasingly regard sustainable returns as a key driver of value so better data is crucial.
Banks may be concerned about lending to or advising organizations with poor ESG practices, and inaccurate climate-related data in particular.

Tips for ensuring data quality in ESG reporting

For ESG reporting to be fully effective, the data collection and quality controls must be built-in and use the same rigor as financial data. Closing the ESG data gap will require more granular data sources, and new tools and methodologies to deliver actionable insights at scale. Here are a few hallmarks of quality ESG data to consider when deciding on data collection methodologies:

100% visibility from reports to granular, meter-level data sources – meaning all financial and operational data must be clearly visible and easily accessible to allow for audits and verification. Obtaining independent third-party assurance to provide an unbiased and objective view of results is also recommended.
Having a means with which to compare and visualize performance on key sustainability metrics across a portfolio.
Real-time monitoring of environmental data over time instead of at one point in order to address progress on ESG targets or goals and identify inefficiencies.
AI and cloud-based solutions may offer a means to collect and aggregate ESG data more effectively, automating tasks such as filtering and analytics to reduce the risk of errors and improve efficiency.
Standardized reporting frameworks and guidelines can help to ensure that data is comparable and consistent, and firms should look to recent progress in the global effort to consolidate reporting frameworks going into 2023.
Using platforms that provide a single source of truth when it comes to the collection and analysis of sustainability and energy data to minimize difficulties in managing multiple data sources

About WatchWire

WatchWire is a sustainability and energy management software-as-a-service (EMSaaS) provider. Across the globe, WatchWire helps commercial and corporate real estate portfolios, Fortune 500 industrial/manufacturing and big-box retail, government, healthcare, and educational facilities reduce emissions, meet their sustainability and net zero goals, and reduce energy expenses while simplifying sustainability and carbon reporting.

Additionally, through advanced, automated data auditing, the WatchWire platform can catch billing errors, saving users money and helping them actualize a superior ROI.