3 Common Reasons Carbon Reports Face Issues During Third-Party Verification

A carbon report can look complete on the surface and still raise questions when a verifier asks where the numbers came from. Third-party verification is not simply a formality. It involves assessing whether the reported information is supported by appropriate data, methodologies, assumptions, and documentation.

For teams preparing a Product Carbon Footprint (PCF) for external review, identifying potential weaknesses before verification can reduce rework and help make the process more efficient. Common issues can arise from gaps in supporting data, unclear methodologies or assumptions, and insufficient documentation or traceability.

Below are three common reasons a carbon report can encounter problems during third-party verification, why these issues occur, and what a more verification-ready approach looks like.

The need for reliable and transparent carbon data is increasingly relevant across business relationships. Some customers request product-level emissions information from suppliers, while procurement processes may incorporate environmental criteria into supplier evaluations. Investors and other stakeholders may also expect companies to provide credible emissions information.

In this environment, a report that cannot adequately support its reported figures can lead to additional questions, corrective work, or delays in completing the review. Building traceability, consistency, and supporting documentation into the reporting process from the beginning can help reduce these issues.

Third-party verification is an independent assessment of whether reported greenhouse gas information is supported by appropriate data, calculations, methodologies, and documentation, and whether it meets the applicable criteria or standard. For a Product Carbon Footprint (PCF), this can include assessing whether the quantification and reporting approach is consistent with the applicable requirements, such as ISO 14067.

A verifier does not just check the final numbers. They may examine the trail behind those numbers: where the activity data came from, which emission factors were applied, whether the methodology was applied consistently, what assumptions were made, and whether the available documentation supports the material information reported. GHG Protocol guidance emphasizes transparency, documentation, data quality, and an audit trail as important foundations for verification.

Verification may also involve assessing reported information against a materiality threshold, depending on the applicable verification program and assurance requirements. A material discrepancy can involve an error or omission that significantly affects the reported information or could influence decisions made by its users. GHG Protocol does not prescribe one universal materiality threshold; the appropriate threshold depends on the reporting program and objectives.

A report does not necessarily need every data point to be error-free. The focus is on whether material discrepancies exist and whether the reported information meets the applicable verification criteria. Traceability, consistency, transparency, and supporting documentation therefore matter alongside the final carbon number.

That distinction is where seemingly complete carbon reports can reveal weaknesses.

Activity data is a key input behind emissions calculations: how much material was used, how far it traveled, how much energy a process consumed, and so on. When this data is incomplete or collected inconsistently, the resulting emissions calculations can also become less reliable, making it more difficult for a verifier to establish whether the reported result is adequately supported. GHG Protocol guidance treats completeness, reliability, and representativeness as important aspects of data quality.

PCF data may be assembled from multiple sources and may cover different periods, which can create consistency and data-quality challenges. A product team pulls a Bill of Materials from one system. A supplier sends partial figures in an email. A production line's energy use is estimated rather than metered. By the time all of this is combined into a single report, some materials may be represented by precise, supplier-specific figures while others are represented by estimates, with no clear record of which data sources or assumptions were used.

A verifier reviewing this kind of report may have difficulty determining whether a data gap was deliberately excluded, inadvertently omitted, or addressed using an assumption if the treatment is not documented. These situations may require different treatment under the applicable methodology, but the basis for that treatment should be documented and justified. GHG Protocol guidance emphasizes documenting assumptions, methodologies, activity data, emission factors, data quality, and changes to data or methodology.

Consider a company reporting the footprint of a metal enclosure. The aluminum housing is supported by a recent supplier declaration with measured energy data. The steel fasteners are represented by an estimate based on last year's purchase volume, with no unit-level detail. The powder coating is based on an undocumented figure carried over from a previous project. Each figure might appear reasonable in isolation, but when a verifier asks why three materials in the same product were supported by different data sources and methods, the company needs to be able to explain and document those differences. Otherwise, the verifier may request additional evidence or clarification.

The second common issue is using emission factors or calculation approaches that cannot be clearly justified or traced to an appropriate source. This can include applying an emission factor without recording its source or version, using different types of emission factors for similar materials without documenting the rationale, or changing a calculation method during an assessment without documenting the change.

A related problem is inconsistency in the product system boundary. Under ISO 14067, a Product Carbon Footprint can be assessed as a CFP covering the product system or as a partial CFP covering defined life-cycle stages. The selected scope and boundary need to be clearly defined and consistently applied within the assessment. If different components are calculated using different life-cycle coverage and those differences are not appropriately accounted for or documented, it can become difficult to establish whether the combined product-level result is consistent.

This does not mean every emission factor needs to come from the same database or that every calculation method needs to be complex. Different appropriate data sources may be used when their selection is justified and documented. What matters is that the choices are appropriate for the assessment, traceable, and consistent with the defined methodology.

A practical example: a team assessing a piece of electronics equipment might use datasets with different life-cycle coverage for different components. Each dataset may be appropriate for its own defined scope, but combining them into a single product-level figure without appropriately accounting for their different life-cycle coverage can create an inconsistent result. A verifier may then request clarification or additional evidence to determine how the different boundaries were treated.

The third issue is often avoidable with stronger documentation practices: the underlying calculation may be reasonable, but the documentation needed to support the reported result is missing, incomplete, or scattered across systems that were never set up to be reviewed together.

Verification typically requires sufficient documented evidence to support the material information reported. This can include invoices, supplier declarations, activity data records, emission factor references, calculation worksheets, and other supporting records. When that evidence is scattered across disconnected spreadsheets, email threads, or individual files, reconstructing the supporting trail during verification can create significant additional review work.

This gap can be particularly challenging in Scope 3 reporting, which often depends on information supplied by external parties. If supplier data is collected informally through emails or one-off spreadsheet submissions in varying formats, there may be no consistent record of when it was received, what information was provided, or whether it was checked before being used in the final report. A figure may be accurate, but if sufficient supporting evidence cannot be produced for the verifier to evaluate it, the verifier may be unable to obtain sufficient appropriate evidence to support that reported figure.

Consider a report where twenty suppliers each submitted emissions data differently: some as PDF declarations, some as completed spreadsheets, and some as numbers typed into emails. Months later, when a verifier asks for supporting evidence for a specific reported figure, the team may have to search inboxes and shared drives to track it down, if it can be found at all. The underlying number may be accurate, but without sufficient supporting evidence, the verifier may request additional documentation or clarification before reaching a conclusion on that information.

The three issues discussed above can often be linked to challenges in how carbon data is collected, calculated, and documented. When information is spread across spreadsheets, emails, supplier files, and manual calculations, maintaining consistency and traceability can become more difficult.

Carbalyze is designed to help bring key parts of the PCF calculation process into a more structured workflow, from product data and emission-factor mapping through to carbon calculations and reporting.

Caly, Carbalyze's AI assistant, can work with a company's Bill of Materials as an input for PCF calculations, helping bring material-level information into a structured calculation workflow. Caly can then help map materials to relevant emission factors using available emission-factor data, including supplier-specific information where available. This can reduce some of the manual effort involved in organizing product data and selecting factors for individual materials.

Carbalyze also supports supplier data collection for Scope 3 calculations, giving teams a more structured way to gather supplier information within the carbon reporting workflow.

The workflow connects product data, emission-factor mapping, carbon calculations, and reporting, helping teams review how the reported result was developed. This can make it easier for teams to understand how the reported carbon result was developed and to organize the information needed for review.

Carbalyze helps teams build a more structured foundation for PCF preparation, connecting product data, emission-factor mapping, calculations, and reporting in one workflow. This can make it easier to review the data and methodology behind a carbon result and prepare the information needed for external review.

With a more connected workflow, teams can spend less time managing scattered data and manual calculations and more time reviewing the quality and consistency of their carbon results.

The three issues discussed in this article point to one important principle: verification depends on more than the final carbon number. The underlying data, methodology, assumptions, and supporting evidence all need to be sufficiently documented and traceable for the reported result to be evaluated.

Preparing for verification therefore starts well before a report reaches a verifier. It begins with collecting reliable activity data, documenting emission-factor and methodology choices, recording assumptions, and organizing supporting information throughout the calculation process. Addressing these areas early can help reduce clarification requests and rework during the review.

These challenges can also overlap. Inconsistent product data can make emission-factor selection harder to document, while fragmented records can make it more difficult to explain how a final PCF was calculated. A structured workflow helps connect these steps instead of requiring teams to reconstruct the calculation history later.

The goal is simple: make the data and decisions behind the carbon number clear, traceable, and easier to review from the beginning.