Most spend-based tools
A·S·F · in every report
What happens to a $400 refund on a $2,500 fuel purchase?
Refund is absolutized (counted as emissions) or silently dropped. Your number ends up 15–25% too high and cannot reconcile to the P&L.
Netted within category before the factor is applied, per GHG Protocol §7.3.2. The Data Quality Summary reports how many rows were netted and in which categories. Reconciles to the GL by construction.
Electricity in California vs. Ohio: same number?
National-average factor applied everywhere. A California-based SaaS company gets a Wyoming-coal footprint. Underwriters notice.
A per-state factor, resolved from your billing address and anchored on that state's own commercial electricity price. California is 0.70 kg/$; Ohio is 4.55. A dollar of Ohio electricity carries 6.5× the emissions of a dollar in California.
A German supplier's CSV with EU-formatted numbers?
Silent parse failure. Produces a zero-emissions report or drops every row. You find out when the supplier questionnaire bounces.
Intake auto-detects comma/period decimal conventions, localized headers, and parens-negative notation. Engine stamp confirms the parse path.
How confident is the classification on row 2,847?
Confidence is not surfaced. The buyer cannot distinguish a high-confidence vendor match from a guess, and the auditor cannot either.
Per-row confidence score on the Disclosure-Aligned tier. Low-confidence rows surfaced in the Data Quality Summary for manual review.
Where does this number come from, exactly?
Factor source is buried in a methodology page that cites “EPA, Exiobase, DEFRA, and proprietary” with no way to reproduce any specific number.
Every row carries its factor, the matching rule that chose it, and the authority behind it: NAICS code, EPA document, date, engine version. The methodology drawer on this page is the same as the PDF's.