1) When calculating emissions: details matter
Increasingly corporations are required by law to report their emissions to regulators. In practice, this means they need to use credible calculation logic – most commonly by following the Greenhouse Gas Protocol standards – and provide auditable data sources to back up calculation results.
As one example, the EU’s CSRD regulation, which affects many corporations reporting starting in 2025, requires companies to receive limited and then reasonable assurance from 3rd party auditors for their emissions reports (source).
The pressure to produce audit-grade reports has only increased. Corporations who reduce their reported emissions over time increasingly receive financial benefits in various forms.
Some examples of the financial impact of reducing emissions:
- Avoiding painful fines:
- The ECB has threatened daily fines up to 5% of annual revenue for banks who are not compliant with regulations to report emissions from their loan portfolios (source)
- Reducing the cost of carbon taxes:
- The EU’s cap and trade ETS scheme expanded in 2024, and now covers emissions from maritime shipping (source)
- This is already incentivizing large regulated enterprises to find lower carbon solutions to reduce their tax bill – for example, Nestle is now working with Maersk to reduce it’s shipping emissions using alternative fuels (source)
- The UK and California have similar cap-and-trade policies in place
- The EU’s cap and trade ETS scheme expanded in 2024, and now covers emissions from maritime shipping (source)
- Retaining and winning enterprise buyers:
- Enterprises like Salesforce.com have committed to reducing their emissions by signing up to the Science Based Targets Initiative, and now increasingly require suppliers to contractually commit to doing the same. Such internal policies can have a cascading effect within entire supplier ecosystems (source)
2) The good news is that increasing accuracy enables reductions.
The GHG Protocol sets out three levels of data granularity, and provides guidance that companies use the most granular data available and accurate for their situation:
- Primary data at the product/service level reported by a supplier
- Primary data reported at the company-level
- Secondary average emission factors
Most carbon accounting software use EEIO emission factors compiled by environmental researchers out of the box. While this is an acceptable method by the GHG Protocol standard, and a reasonable starting point in a decarbonization journey, in practice many of these EFs are several years old and unhelpfully broad. This means they are less accurate and often overestimate emissions compared to more current and granular emissions data.
In addition to being less accurate, companies that use these emission factors to estimate their scope 3 emissions don’t get credit when their Scope 3 counterparties reduce their emissions. This means the only way to reduce your Scope 3 procurement emissions in the short term is to reduce your procurement spend – not exactly actionable advice!
On the other hand, if product or company-level emissions data are available, companies can increase their reporting accuracy while getting credit for reduction actions taken by their Scope 3 counterparties.
3) Why don’t all companies use primary data?
If using more granular primary data instead of average emission factors increases the accuracy of a report and can help reduce a company’s reported emissions, why doesn’t every company do it?
Companies increasingly publish primary emissions data, but these reports are complicated to acquire and use. This is because most managers don’t know how to translate unstandardized emissions reports into useful data and actions, and suppliers hate responding to surveys.
4) How DitchCarbon simplifies the Scope 3 Challenge
We start by taking the pain out of acquiring company-reported carbon data, by aggregating data from many fragmented sources, and normalizing it to Greenhouse Gas Protocol standards.
We then provide tools that automate Scope 3 measurement and simplify carbon reduction decisions for both sustainability professionals and supply chain operations employees.
Depending on your use case and available input data, DitchCarbon can provide manufacturer-reported data and solutions at the product or company-level, as well as industry average EEIO emission factors when more granular data are not available, to complete coverage.
In practice, this means our products are:
- Auditable: with original data sources provided
- Accurate: aligned with the GHG Protocol
- Comprehensive: automatically delivering the broadest coverage while using the most granular primary data when available and appropriate for your use case
We handle common issues with Scope 3 data so you don’t have to, and our team is available to help you pick the best tool for your use case.
5) Detailing our methodology
The DitchCarbon Score enables professionals and non-sustainability experts alike to evaluate whether Organizations are taking action to reduce their emissions, and if they compare favorably with their peers.
All data points used are provided in our Organization API response. Use our score out of the box to enable carbon-aware decisions within your operations, or leverage our data and methodology to generate your own internal score.
The Score leverages proprietary algorithms to analyze dozens of data points specific to an Organization and calculates their score between 0 and 100.
We believe that transparent decision-making criteria enables you to make better decisions, and helps your Scope 3 counterparties to improve. This is why we disclose the factor categories and relative weights that the DitchCarbon Score takes into account.
What impacts the score
Factors Increasing Organization Score | Weight | Source | Apple 2024 Example: |
---|---|---|---|
Reduced absolute emissions: last year | High | Primary data – company disclsoures | Yes |
Reduced emissions intensity (revenue adjusted): last year | High | Primary data – company disclsoures | Yes |
Committed to SBTI: Net Zero | High | SBTI database | No |
Are in a very low or low emitting industry | High | Exiobase, DEFRA, EPA EEIO databases | Yes |
Reduced absolute emissions: previous 2 years | Medium | Primary data – company disclsoures | No |
Reduced emissions intensity (revenue adjusted): previous 2 years | Medium | Primary data – company disclsoures | No |
Disclosed Scope 1, 2, and 3 emissions: last year | Medium | Primary data – company disclsoures | Yes |
Reported all industry-relevant Scope 3 categories: last year | Medium | CDP relevance criteria | company disclosures | Yes |
Committed to SBTIs: Near Term or Long Term | Medium | SBTI database | Yes |
Is a Climate Pledge signatory | Low | Climate Pledge database | No |
Committed to at least 1 UN Global Compact environmental initiative | Low | UNGC database | No |
Disclosed to CDP: last year | Low | Public disclosures | Yes |
Disclosed Scope 1, 2, and 3 emissions: previous 2 years | Low | Primary data – company disclsoures | Yes |
Disclosed to CDP: previous 2 years | Low | Public disclosures | Yes |
Reported all industry-relevant Scope 3 categories: previous 2 years | Low | CDP relevance criteria | company disclosures | Yes |
Is headquartered in a very low or low emitting country | Low | National grid intensity disclosures | Yes |
Score | 69 |
Working through the Apple example:
Apple’s score for 2024 is 69. They are in a moderate emitting industry, and have made progress by disclosing all relevant emissions categories consistently, signing up to STBI near term targets, and reducing their emissions in 2023. The most impactful steps they can take to continue to increase their Score are reducing emissions and emissions intensity consistently for the next few years, and setting an SBTI Net Zero target.
How to understand if a company’s score is good, decent, or bad: use peer group benchmarks.
We provide 2 benchmarks at the score level:
- Industry mean score: the average score globally for companies classified in the same industry
- Percentile benchmark: a Score ‘s percentile rank compared to its peers.
Going back to the Apple example:
- The mean score globally for companies similar to Apple is 47
- Apple’s score of 69 is in the top 10% of its peer group globally
DitchCarbon’s Organization-level data gives you the full picture on an organization from an emissions perspective. Use it for pulling primary data into your Scope 3 calculations, benchmarking, and action planning to reduce emissions with Scope 3 counterparties.
Access and export data within your preferred application or ERP via API, or in the DitchCarbon web app.
Inputs accepted for entity resolution:
- Organization Name
- Industry
- Headquarter Country/Region
- Website domain
- Stock ticker
We provide organization-reported primary data when they’ve been disclosed, and always provide average industry-level emission factors for use as fallbacks and comparisons:
Region Rank ranks the organization’s primary region by its grid’s carbon intensity compared to other grids globally. Regions are ranked in quintiles from very low to very high.
Industry Rank ranks the organization’s industry-average emissions intensity compared to other industries. Industries are ranked in quintiles, from very low to very high.
Organization-reported primary data are captured and normalized to the GHG Protocol standards leveraging:
- Artificial intelligence in the data extraction phase
- Machine validations of extracted data comparing to our previously validated database
- Human review of potential anomalies
Our data extraction engine automatically handles common issues that enterprises encounter when trying to use primary data that cause emissions reports to fail audits. Example issues we often correct:
Reported emissions figures not aligned with GHG Protocol reporting standards
Reductions from carbon offsets should be reported separately from total emissions numbers according to the GHG Protocol. In practice, companies sometimes report a Net Emissions figure as their Total Emissions without documenting the difference. DitchCarbon presents the cleaned GHG-aligned total in our web app, and provides it along with the original company-reported data via API or CSV export. This helps you avoid issues when using company-disclosed data.
Unclear units
Reported units are captured and normalized to kgCO2e. In cases where units are not clear due to poor reporting structure, units are inferred by comparing to benchmark industry emission factors in our existing dataset.
Incorrect category naming
Companies sometimes report emissions categories that are not aligned with the GHG Protocol, including combining Scope 3 categories together. DitchCarbon’s artificial intelligence automatically normalizes reported categories to GHG Protocol standard categories while filtering unusable data points.
Correcting emissions factors for proper use cases
We simplify Scope 3 measurement and benchmarking by providing 3 company-level emission factors and one industry-level emission factor out of the box, and guidance on the correct use case for each one. For example, using an emissions factor with upstream Scope 3 emissions included is appropriate for a procurement spend emissions calculator, but an asset manager evaluating automotive manufacturers should also consider downstream Scope 3 emissions to take vehicle efficiency into account.
We generate up to three different organization-level emission factors per organization for each year. Emission factors are based on the organization’s disclosed global revenue and emissions data.
Emission factors are only generated if sufficient data has been disclosed to perform the necessary calculation accurately:
Emissions category relevance is assessed using CDP’s Relevance Guidance covering 16 heavy emitting sectors.
For other sectors, we use CDP’s definition of relevance as exceeding 2% of total emissions, and determine relevant categories by evaluating emissions reports in our database issued by publicly listed companies that disclose Scope 3 category data. We consider reports for the year 2022 or later.
Different users will find different organization-specific emission factors to be best suited for their use cases. We provide the following based on past experience working with users and practitioners to select the most useful emission factors for a given situation.
Scope 1+2 emission factor use cases:
- Benchmarking organizations in sectors with high scope 1+2 emissions allocations
- Reducing survey requirements in Scope 3 hybrid cradle-to-gate calculations
- Tracking organization internal emissions intensity changes over time
Scope 1+2+3 (upstream) emission factor use cases:
- Benchmarking organizations in sectors with relevant scope 3 upstream allocations
- Further reducing survey requirements for Scope 3 hybrid cradle-to-gate calculations
- Tracking organization supply chain emissions intensity changes over time
Scope 1+2+3 emission factor use cases:
- Benchmarking organizations with high scope 3 downstream emissions allocations
- Tracking organization’s entire value chain emissions intensity changes over time
Industry average spend-based emission factors are often used in the first step of the emissions reduction journey to quickly identify areas of focus, and later to fill in gaps where primary data are not available.
DitchCarbon provides 200 industry emission factors for 43 countries and 5 global regions.
Emission factors are generated from EEIO data published by environmental researchers and government agencies at DEFRA, the US EPA, and Exiobase. The specific source used depends on the emission factor requested, and sources are always cited in our web app and API responses.
Because these datasets are updated irregularly, and depend on currency valuations and other factors, they need to be adjusted for changes over time in inflation and grid intensity to be useful.
Country-level industry emission factors are:
- Adjusted for Inflation and exchange-rate using data from the Bank of England
- Adjusted for changes in grid intensity overtime. Government-reported national grid intensities are used, and each industry is adjusted based on the share of that industry’s emissions that are generated from the electrical grid, using data from the EU27 Input-Output Database
Regional average emission factors are:
- Provided where country-level emission factors are not available. These are calculated using a GDP-weighted average, using data from the World Bank
- Used in cases where Exiobase country-level data is anomalously high
For purchases of fuels and electricity, unit-based emissions factors are used to ensure accuracy and auditability.
For categories of electricity:
- Country-level emissions/kwh are used, and converted into spend-based emission factors using annual national average price/kwh data
For categories of fossil fuels, such as coal, kerosene, fuel oil, and natural gas:
- Spend-based emission factors are used to calculate Scope 3 emissions from extraction and distribution
- Unit-based emission factors are used to calculate Scope 1 emissions. These are converted into spend-based emission factors using annual national average price/unit data
The Product API helps you determine emissions from product purchases using manufacturer-reported data where available. Access via DitchCarbon’s API inside your preferred application.
Leading procurement tech firms are using it within their guided buying applications to enable their enterprise customers’ buyers to understand the emissions of products before purchase, and generate auditable emissions data alongside purchase orders to streamline end-of-year carbon accounting.
In line with the GHG Protocol standard, the Product API provides data at three levels of granularity, automatically using the most granular data available based on what manufacturers have disclosed:
- Manufacturer-reported product-level data
- Manufacturer-reported organization-level calculation, using a Scope 1+2+3 (upstream) emission factor
- Category average spend-based calculation
For product-level disclosures, we provide both the original manufacturer-reported carbon footprint and a modified value that uses DitchCarbon’s model to consider aspects that have changed since the manufacturer’s declaration (e.g. grid intensity) to provide a more accurate estimate.
When category-average spend-based calculations are made, DitchCarbon uses EEIO data on the economic value of purchased goods and services and applies an emission factor per currency unit. Emission factors are adjusted from original sources for inflation and exchange rates where applicable.
DitchCarbon’s API provides the data method that was used for a calculation, along with the original source emissions disclosure, ensuring auditability.
6) Organization level data
- Inputs
- Company name
- HQ country
- Website
- Industry
- Stock Ticker
- Spend (if using web app)
- Outputs
- Organization-level emission factor
- DitchCarbon score
- Current and historical disclosures
- SBTI, CDP, and UNGC status
- Reduction Action Co-Pilot
- Peer comparisons
- Industry benchmark
- Sources for all data points
7) Product level data
- Inputs
- Product name
- Product manufacturer
- Location of use
- Quantity
- Price (used as fallback)
- Outputs
- Product carbon footprint (if disclosed)
- Breakdown of stages of use
- Method of calculation used
- Organization-level spend or category-level spend (if not disclosed)
- Sources of all data points