The framework, rooted in EcoVadis methodology and powered by its Carbon Data Network, is designed to restore trust in corporate carbon emissions reporting.
NEW YORK & PARIS — June 23, 2026 — EcoVadis, the global standard for resilient, sustainable supply chains, today published the full methodology behind its Carbon Data Reliability Level™ (DRL) framework and is calling on industry stakeholders to adopt it as a shared standard for corporate carbon emissions reporting. Designed to address the critical "trust deficit" essential for Scope 3 calculation, the DRL framework acts as an automated integrity filter that turns raw supplier carbon data into actionable, assurance-aligned intelligence.
As companies accelerate their transition to mandatory Scope 3 disclosure under frameworks like CSRD in Europe, SB 253 in California and emerging requirements across other jurisdictions, the quality of supply chain data has become the defining constraint, not only on accurate reporting, but also – and most importantly – on corporate climate action that can truly follow.
While AI-powered accounting tools are rapidly scaling, they are often ingesting unreliable data, effectively building the next generation of climate strategy on "foundations of sand".
"Scope 3 emissions represent the largest share of most companies’ climate footprint, yet this is the category where data quality is weakest and trust is lowest," said Dexter Galvin, SVP Climate at EcoVadis. "The DRL framework solves this by moving the market from a focus on mere data availability to validated data reliability."
A Three-Gate Architecture for Data Integrity
The DRL framework assesses GHG metrics submitted across the EcoVadis Carbon Data Network, comprising approximately 60,000 reporting organizations. The taxonomy delivers a reliability score through a sequential, cumulative three-gate process:
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Gate 1 (evidence): The integrity filter establishes whether a reported GHG figure can be traced to a valid source document. Metrics without a traceable source default to "low" reliability and are not processed further.
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Gate 2 (rigor): The methodology check assesses the scientific robustness of calculation methodologies, including GHG protocol alignment and third-party verification status.
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Gate 3 (plausibility): The reality check compares reported figures against sector-specific benchmarks drawn from the Carbon Data Network to detect statistically improbable anomalies.
The process yields a clear, four-tier taxonomy: Low, Medium, High or Third-Party Verified/Compliance-Ready Intelligence.
The DRL framework is designed as a compliance enabler, mapping directly to emerging international standards:
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GHG Protocol Scope 3 Phase 1 Revision: DRL data maps to the standard’s data-tier disaggregation and verification labelling requirements.
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CSRD & ESRS E1: The DRL taxonomy identifies high and third-party Verified data as the evidence base required to support "primary" data classification.
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ISSA 5000: The framework produces the documented methodology and evidence chains necessary to support efficient, defensible sustainability assurance engagements
Scaling for the Future
The credibility of the DRL system is rooted in the scale of the EcoVadis Carbon Data Network. Unlike proprietary models, the DRL plausibility gate relies on sector-calibrated benchmarks derived from years of assessment cycles, making it a reference point that platforms and auditors can trust. Through the Carbon Data Network, these reliability levels will be surfaced within a growing network of carbon accounting partner platforms, ensuring that a supplier rated once is then recognized across the entire ecosystem.
"We are moving the market toward a standardized, open reliability baseline," added Dexter. "By making reliability a first-class requirement rather than an optional feature, we empower procurement and finance teams to turn Scope 3 emissions from an unmanaged risk into an opportunity for verifiable impact".
For more information on the DRL methodology, visit : https://ecovadis.com/solutions/ecovadis-carbon-data-reliability-levels/
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