Glossary term
ESG Data Quality
Subject: Sustainability and ESG, ESG Frameworks, Standards and Disclosure
ESG data quality describes how complete, accurate, consistent, comparable and verifiable a company’s environmental, social and governance data is, and so how far investors, regulators and managers can rely on it.
Explanation
ESG figures often come from many sites, suppliers and spreadsheets, with no long history of controls. Quality problems include missing sites, estimates that are not labelled, changing definitions from year to year, and boundaries that differ between reports. Practitioners test data on completeness, accuracy, consistency over time, comparability with peers and traceability back to source. Controls borrowed from financial reporting help: named data owners, written methods, reconciliations, review and sign-off, and an audit trail. Where numbers cannot be measured directly, as with supplier emissions, the estimates and their uncertainty are disclosed. Poor quality is one reason ratings of the same company diverge. Rating agencies, auditors and regulators all begin by asking where a number came from, and weak answers lead to restatements, disputed ratings or enforcement.
Example
A logistics company reports total waste for the year. During assurance, the provider finds two depots left out, one site reporting in tonnes and another in kilograms, and a prior-year figure restated without a note. The company corrects the units, adds the depots, writes a data method note and assigns an owner to each site’s submission.
Not to be confused with
- Data Quality Management
- Data quality management is the general discipline for any data. ESG data quality applies it to sustainability figures, which often rely on estimates and outside sources.