QUALITY MATTERS: TRANSFORMING ESG DATA FOR BETTER DECISION-MAKING

The We Mean Business Coalition identifies critical failures in the ESG data ecosystem, noting that historical emissions data is often inadequate for meaningful analysis due to blatant errors and inconsistent reporting. The report categorizes these issues into company-level reporting failures, data provider extraction errors, and structural gaps such as the lack of central repositories and misalignment between GHG and financial reporting boundaries. To resolve these, the authors advocate for the global adoption of ISSB standards, mandatory XBRL tagging, and the alignment of GHG operational boundaries with financial reporting standards.

• Historical ESG data is frequently unreliable, with a significant rate of blatant errors in older datasets. For WMBC-companies, obvious data issues were present in 7% of 2019 emissions data, compared to only 0.25% in 2021 and 2022.
• Company reporting is often skewed toward large, publicly listed entities in developed regions, leading to the underrepresentation of SMEs, privately owned companies, and companies in emerging markets.
• Data providers introduce significant delays and errors; ESG data is often outdated by 1.5 years or more, and manual extraction methods frequently result in unit mistakes, typos, and missing data points.
• There is a critical misalignment between GHG reporting boundaries and financial reporting boundaries, which hinders logical integrated analyses of emissions against revenue or cash flow.
• The report identifies several common company misunderstandings of reporting requirements, such as reporting only CO2 instead of CO2 equivalents (CO2e), failing to segregate GHG emissions across the three scopes, and equating energy consumption with electricity.
• The adoption of mandatory XBRL (eXtensible Business Reporting Language) tagging and the creation of central repositories, such as the EU's European Single Access Point (ESAP) and the Net Zero Data Public Utility (NZDPU), are proposed as primary solutions to reduce data lag and extraction errors.

APA

Jagd, J. T., & Fischbach, S. (n.d.). QUALITY MATTERS: TRANSFORMING ESG DATA FOR BETTER DECISION-MAKING. We Mean Business Coalition. https://www.wemeanbusinesscoalition.org/wp-content/uploads/2025/02/WMBC_Quality_Matters_report.pdf

Chicago

Jagd, Jane Thostrup, and Sebastian Fischbach. QUALITY MATTERS: TRANSFORMING ESG DATA FOR BETTER DECISION-MAKING. We Mean Business Coalition, n.d. https://www.wemeanbusinesscoalition.org/wp-content/uploads/2025/02/WMBC_Quality_Matters_report.pdf.

Wikipedia

{{cite report |last1=Jagd |first1=Jane Thostrup |last2=Fischbach |first2=Sebastian |title=QUALITY MATTERS: TRANSFORMING ESG DATA FOR BETTER DECISION-MAKING |publisher=We Mean Business Coalition |url=https://www.wemeanbusinesscoalition.org/wp-content/uploads/2025/02/WMBC_Quality_Matters_report.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{jagdndquality, author = {Jagd, Jane Thostrup and Fischbach, Sebastian}, title = {{QUALITY MATTERS: TRANSFORMING ESG DATA FOR BETTER DECISION-MAKING}}, institution = {We Mean Business Coalition}, url = {https://www.wemeanbusinesscoalition.org/wp-content/uploads/2025/02/WMBC_Quality_Matters_report.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }