Why Structured Data is the Key to Unlocking ESG Insights: A Guide for Regulators

Today more than ever, regulators are taking transformative strides in shaping corporate behavior and ensuring transparency in environmental, social, and governance (ESG) reporting. As the world seeks solutions to pressing challenges such as climate change, social inequality, and corporate governance failures, regulatory frameworks must keep pace to ensure data-driven decision-making and accountability. 

One of the most significant challenges in ESG reporting lies in interpreting and utilizing unstructured data, which is often presented in narrative formats, scattered across documents, and inconsistent in scope. This lack of standardization makes it nearly impossible to efficiently monitor compliance, assess risks, or compare corporate performance. 

Structured data, enabled by technologies like XBRL (eXtensible Business Reporting Language), offers regulators a transformative solution. Marc Houllier, CTO of Corporatings, highlighted the power of structured data at Data Amplified, demonstrating how the European Sustainability Reporting Standards (ESRS) are leveraging it to revolutionize ESG disclosures. This blog explores how structured data can help regulators meet their goals of transparency, comparability, and actionable insights. 

Structured data refers to information that is organized in a predefined manner, often within rows and columns, such as a database or spreadsheet. Each data point is tagged with a specific identifier (or taxonomy), making it easier to sort, filter, and analyze. In the context of ESG reporting, structured data can include information such as carbon emissions, renewable energy usage, waste management practices, gender diversity figures, and financial commitments to sustainability targets. 

XBRL is a key enabler of structured data. It is an open standard for digital business reporting that tags individual pieces of financial and non-financial data, such as those found in ESG reports, with standardized labels. These tags ensure that the data can be processed, validated, and compared with ease across different organizations, sectors, and timeframes. 

For regulators tasked with enforcing sustainability mandates, unstructured ESG data presents three significant challenges:

1. Inconsistency Across Reports: ESG data in its unstructured form is often buried within narrative sections of corporate reports. This makes it nearly impossible to standardize or compare disclosures, particularly across industries or jurisdictions. 
2. Difficulty in Identifying Non-Compliance: With no standard tagging or formatting, critical information may be omitted or hidden in long-text narratives. Detecting omissions or discrepancies requires manual analysis, which is time-intensive and prone to human error. 
3. Inadequate Support for Decision-Making: Regulatory bodies need robust, actionable data to assess trends, enforce compliance, and design future policies. Unstructured ESG data provides limited usability, slowing down regulatory processes and hindering informed decision-making.

• • Enhanced Monitoring and Compliance Oversight
    Structured data empowers regulators to efficiently monitor corporate compliance with ESG mandates. For example, under the ESRS framework, companies are required to disclose sustainability metrics in a structured format using XBRL. These disclosures allow regulators to:
  • Instantly validate reported data against mandated thresholds or targets.
  • Detect non-compliance or incomplete disclosures through automated systems.
  • Monitor trends over time to identify risks or areas requiring intervention.

This proactive approach eliminates the reliance on manual audits and streamlines compliance processes.

• • Standardization Across Jurisdictions and Sectors
    One of the most significant barriers to effective ESG oversight is the lack of standardized reporting across companies and industries. Structured data ensures uniformity in reporting by using a common taxonomy that defines how data should be tagged and presented.

For instance, in the European Union, the ESRS taxonomy allows regulators to compare emissions data from a car manufacturer in Germany with a tech company in France, enabling sector-specific and cross-sector analyses.

• • Improved Data Usability and Comparability
    Structured data supports advanced analytics, enabling regulators to derive insights that would be impossible with unstructured formats. For example, regulators can:
  • Benchmark corporate performance within sectors to identify outliers or laggards.
  • Compare year-over-year data to assess progress on climate goals.
  • Evaluate the impact of specific regulatory interventions on corporate behavior.

This capability is essential for designing data-driven policies and fostering accountability among businesses.

• • Real-Time Insights Through Automation
    Structured data enables real-time analysis by integrating seamlessly with regulatory databases and dashboards. For example, regulators can:
  • Automate the collection and processing of ESG data from companies.
  • Generate instant reports on compliance rates or sectoral performance.
  • Use predictive analytics to identify potential risks or areas of concern.

This real-time insight not only improves regulatory efficiency but also enhances transparency, which is crucial for maintaining public trust.

• Facilitating Global Harmonization
  Global ESG frameworks, such as the Task Force on Climate-related Financial Disclosures (TCFD) and the International Sustainability Standards Board (ISSB), emphasize the need for consistent and comparable data. Structured data aligns with these frameworks, making it easier for regulators to harmonize reporting requirements across jurisdictions and avoid redundancies.

XBRL, as a tool for structured reporting, provides several features that make it indispensable for regulators: 

• Tagging Capabilities: XBRL allows companies to tag individual data points, such as renewable energy usage or greenhouse gas emissions, ensuring clarity and accuracy. 

• Validation Mechanisms: XBRL-enabled systems can automatically validate disclosures against predefined taxonomies, reducing errors and inconsistencies. 

• Scalability: Whether monitoring a single company or an entire sector, XBRL scales to accommodate the needs of regulators. 

Marc Houllier’s insights at Data Amplified highlighted how XBRL’s capabilities align perfectly with the ESRS framework, providing regulators with the tools needed to enforce compliance and promote transparency effectively. 

• Structured data is no longer optional—it is essential for unlocking the full potential of ESG insights. For regulators, it offers a powerful solution to the challenges of unstructured reporting, enabling better compliance oversight, enhanced data usability, and informed decision-making. As global sustainability goals become increasingly urgent, regulators must lead the charge in adopting and promoting structured data frameworks. By mandating the use of technologies like XBRL and supporting international harmonization efforts, regulators can ensure that ESG reporting delivers on its promise of transparency, accountability, and comparability. 

  The future of sustainability reporting lies in structured data. For regulators, embracing this innovation is not just a technological advancement but a critical step toward achieving a more sustainable and equitable world.