Why you need data integrity for ESG reporting?
Is your company making commitments to environmental, social, and governance (ESG) efforts? How are you quantifying those results, and can you make sure you have the most accurate and current data?
The latter question holds the issue for many – while it’s easy to add, messaging and imagery on your website, products, and beyond, things become more difficult when reporting and compliance for those efforts come into the picture.
Across industries, data for ESG initiatives share at least one major thing in common: gathering and analyzing the data for compliance and reporting is a massive, costly undertaking – one that goes beyond manual capabilities. That’s because ESG data can be both qualitative and quantitative; structured and unstructured; diverse and dispersed.
You need a flexible framework to efficiently identify, understand, and link the underlying data elements required for accurate, consistent, and contextualized ESG reporting.
In summary: your ESG data needs data integrity. Let’s examine that more.
The growing demand for ESG data
Formal government regulations are certainly on the rise, but to this point, the demand for transparent ESG practices has been driven by the public – from customers, investors, and employees who want to engage with companies that drive meaningful initiatives around what they care about: topics like diversity and inclusion, ethical business practices, environmental issues like climate change, and data privacy.
With this demand, ESG has evolved into a business imperative. But it’s important to note that the awareness of “greenwashing” has also been on the rise. Greenwashing refers to companies making claims about their ESG practices that aren’t supported by the facts.
Consumers and investors are becoming savvier about spotting greenwashing, so it’s never been more important to have the data to back those claims up. For example, are you making good on your promise to reduce the use of plastic in your products and processes?
Great – but what does that look like by the numbers? Have you cut down plastics by 25%? 50%? What’s your end goal? How do you prove it?
Being transparent and having this type of information readily available is what builds confidence and trust in your brand and makes reporting and compliance processes more streamlined. The stakes are high and there isn’t a tolerance for error. Here are just a few more examples that illustrate why high-quality data matters:
- Investment managers and asset owners demand full disclosure of ESG risks that could impact the long term value of their holdings
- Financial and stock exchange regulators are concerned about preventing market instability caused by fraudulent or misleading ESG claims and disclosures
- ESG raters, rankers, and reporters can suffer damage to their reputations if they publish investment analyses based on false or incomplete corporate risk disclosures
With all of this in mind, what do you need to actually achieve data integrity and ensure better results from your reporting?
The Data Integrity capabilities you need for ESG reporting
Now that we’ve covered why you need to have clear, accurate, and readily accessible data to show the progress of your ESG efforts, let’s walk through a snapshot of what that means for your data management capabilities.
Once key ESG issues and metrics are established, IT and data management executives need to align and lead their teams through a careful and thorough evaluation of the related data requirements. To gain data integrity, you need IT systems and processes that allow you to achieve several crucially important data management competencies, effectively and flexibly. These include:
- Data Integration capabilities for capturing and organizing ESG data from diverse sources and making it available in real-time.
- Data Enrichment for combining and aligning your fundamental ESG data with additional datasets to add context and meaning, such as geographic, demographic, or economic data.
- Data Governance for positive control over data storage, access, use, exchange between systems, etc., while maintaining privacy, security, and compliance with essential government regulations.
- Data Quality & Observability standards and controls to ensure all data, including ESG data, is always accurate, complete, and consistent, wherever it’s stored and used throughout the organization. Observability makes it possible to be proactive in catching anomalies in your data, so you can fix the issue faster and prevent costly downstream issues.
Through these capabilities, you gain more cost-effective data quality processes, time-saving automation of manual efforts, and overall greater confidence in data trust. Only then can you be sure that your data-driven ESG reporting is making the impact you need it to.
For an even deeper dive into how data integrity helps your organization realize the full business potential of ESG through better data and reporting, read the eBook: “Unlocking Real Business Value from ESG” and learn how Data Integrity helps companies realize the full business potential of ESG through better data and reporting.