Why Your Carbon Number Doesn't Match Your Supplier's — And Why That Can Cost You Real Money
If you've ever calculated a product's carbon footprint, sent it to a partner, and gotten back a different number for what should be the same thing, you've already met the least glamorous but most consequential problem in carbon accounting: not all emission factors are created equal.
This isn't a rounding error. At a recent Climate Week Zurich panel hosted by ecoinvent — Beyond the Pledge: Embedding Sustainability into Business DNA — Anke Hampel, Global Head of Sustainability at ABB, shared a story that should make every finance and sustainability leader pay attention.
A $1 Million Lesson in Data Consistency
ABB had built a QR-code based product transparency system, giving customers access to circularity assessments, recycled content data, take-back options, and environmental product declarations (EPDs) for individual products. It was a genuine differentiator — competitors later copied the concept.
Then one of ABB's largest distributor customers decided to publish its own sustainability ratings for the products it sold — an Amazon-style, one-to-five "green star" system, built into the retailer's own website. The problem: the retailer sourced its underlying emissions data from a different environmental database than the one ABB used internally.
The result, according to Hampel: differences of up to 30% in calculated emissions for the exact same product , purely as a function of which database and methodology was used. ABB's products ended up scoring worse than competitors' — not because they performed worse, but because the comparison wasn't apples to apples.
It took a sustained effort to demonstrate the discrepancy and get the retailer to adjust or pull the ratings. By ABB's own account, the episode cost the company roughly $1 million in lost turnover before it was resolved.
Why This Keeps Happening
Carbon accounting has multiple valid but methodologically different ways to answer the same question: "how much CO2e did this product generate?"
When academic researchers compared product carbon footprints between major LCA databases like ecoinvent and EXIOBASE, they found that roughly half of the matched products deviated by a factor of 2 or more . Similarly, comparing generic global averages to specific supplier data can reveal emission factor variances of up to 98% for identical inputs .
A few of the biggest sources of variance:
- Different underlying life cycle inventory (LCI) databases. Databases differ in system boundaries, regional grid mix assumptions, allocation methods (mass-based vs. economic vs. system expansion), and how frequently they're updated.
- Average vs. activity-based data. Many "quick" carbon estimates rely on spend-based or industry-average emission factors (e.g., "$1,000 of steel = X kg CO2e"), which can be off by wide margins for any specific supplier, process, or facility. Activity-based data — grounded in actual quantities, materials, energy sources, and processes — is more accurate but requires real supplier-level input.
- EPD scope and boundary differences. Even Environmental Product Declarations, often treated as a gold standard, can differ in the life cycle stages they cover (cradle-to-gate vs. cradle-to-grave), the product category rules (PCR) applied, and how end-of-life is modelled.
- Update cadence. Emission factors change as grids decarbonize and processes improve. A number that was accurate two years ago may already be materially wrong.
None of this makes any single database "wrong." It means that without a consistent, transparent, defensible methodology, two honest actors can produce two different — and both defensible — numbers for the same product. And as ABB learned, that inconsistency doesn't stay academic. It shows up in retailer rankings, tender scorecards, investor questions, and customer-facing comparisons.
What The Industry Is Doing About It
To solve this data crisis, industry groups and regulators are moving aggressively to standardise how product carbon footprints (PCFs) are calculated and shared.
A major turning point is the launch of the PACT Methodology Version 3.0 by the WBCSD in April 2025 , which establishes a harmonised framework for cradle-to-gate PCF calculations and mandates recalculation if production changes cause a variance of 10% or more. This methodology pairs with the PACT Technical Specifications (updated to v3.0.3 in late 2025) to enable automated, interoperable PCF data exchange across disparate software systems.
Regulatory pressures are also forcing alignment. For instance, the EU Battery Regulation enforces mandatory carbon footprint declarations for specific battery categories starting in 2026 , requiring strict adherence to standardised calculation rules. The business risks of ignoring these standards are escalating; companies relying on generic or inconsistent emission factors are increasingly seeing these discrepancies classified as major nonconformities during ISO 14064-1 greenhouse gas audits .
Why Activity-Based, EPD-Grounded Data Matters
This is precisely the gap that activity-based carbon accounting — grounded in verified, standardised documentation like EPDs — is designed to close.
Rather than applying a generic industry-average factor to a line item on an invoice ("steel purchase = generic steel factor"), activity-based accounting ties emissions to the actual activity: the specific supplier, the specific material specification, the specific process and energy source behind it. Where EPDs exist, they anchor the calculation in third-party-verified, standardised data rather than a black-box internal estimate.
The result is a carbon figure that:
- Reflects what was actually purchased , not a category-level proxy.
- Can be defended and reproduced when a customer, auditor, or regulator asks "how did you get this number?"
- Stays consistent across the value chain , reducing the risk of the exact mismatch ABB experienced.
What This Means for How You Manage Supplier Data
If your organisation is converting invoices or bills of materials into carbon data, three practical takeaways follow directly from ABB's experience:
- Document your methodology and cite your source data. If a customer, auditor, or retailer ever compares your numbers against another source, you need to be able to explain the difference in minutes, not months.
- Push for supplier-specific and activity-based data wherever it's available , especially for your highest-spend or highest-carbon-intensity categories. Generic averages are a reasonable starting point, but they're a liability once a number becomes customer-facing or contract-relevant.
- Treat carbon data with the same rigour as financial data. ABB's episode wasn't caused by bad intentions on anyone's part — it was caused by treating emissions data as a soft, secondary number rather than something that gets checked, audited, and relied upon commercially.
The Bigger Pattern
This story is a specific illustration of something several panelists at the ecoinvent event in Zurich echoed: sustainability data is no longer confined to annual reports. It's now embedded in retailer rankings, tender requirements, and customer-facing product comparisons — which means data quality and consistency isn't a "nice to have" for the sustainability team. It's a commercial risk that sits squarely with procurement, sales, and finance too.
At Simple., this is exactly the problem we built our platform to solve: converting your actual supplier invoices and bills of materials into carbon data anchored in activity-based, EPD-grounded methodology — so the number you report is the number that holds up, wherever it ends up being compared.