Methodology

Comprehensive guide to our data collection, calculation methods, and scoring algorithms for accurate Scope 3 emissions measurement

Organization Data

DitchCarbon aggregates disclosed emissions data, reduction targets, and initiative participation, and generates insights from that data - with no surveys required.

Organization-level records provide the complete picture of an organization from a climate action perspective. Use them to:

  1. 1Pull primary data into Scope 3 calculations
  2. 2Forecast future emissions
  3. 3Segment and benchmark Organizations
  4. 4Determine highest leverage actions to reduce emissions with Scope 3 counterparties

Access and export data within the DitchCarbon web app, via API in your preferred application or ERP.

Organization Record Payload

Data is aggregated and structured into standardized formats, normalizing for units and various reporting styles to GHG Protocol Standards.

Summary of data available in an Organization record:

Data CategoryDescriptionSources
Emissions Disclosures
All GHG Protocol Scopes/CategoriesOrganization disclosures
Assurance Levels
3rd party auditor and assurance level received, by Scope, extracted from each disclosure.Organization disclosures
Organization Emission Factors
Global factors - 3 boundaries available. See Organization Emission Factor section for detailOrganization disclosures: emissions and revenue
Reduction Targets
Disclosed directly by company, or validated by SBTiDisclosing organization or SBTi
Initiative Participation
Participation status: SBTi, CDP, Race to Net Zero, UN Global Compact, RE 100, Climate Action 100, Ecovadis (if publicly disclosed).Initiative databases and disclosing organization.
Reduction Actions
Actions taken by organization to reduce emissionsOrganization disclosures
DitchCarbon Score
Climate action score, 0 to 100. See DitchCarbon Score methodology for detailDitchCarbon algorithm
Score Benchmark
Compares Organization's score to others in its industry. See Score methodology for detailDitchCarbon algorithm
Peer Comparisons
Data from similar OrganizationsOrganization disclosures S&P global database
Recommendations
Highest leverage reduction actions to take, based on Organization's profile, and relevant actions taken by similar organizationsDitchCarbon reduction action database, UN Climate Drive
Industry Emission Factors
6 years industry emission factors, used as fallbacks where organization emission factors unavailableUS EPA, Exiobase, Denstore, UK DEFRA

For more information on fields see our Data Dictionary, or get in touch: enquiries@ditchcarbon.com

Entity Resolution: Matching User Requests to DitchCarbon Organization Records

Users may provide a combination of inputs:

Name (required)
Direct Match IDs (encouraged if available)
DUNS
S&P Global ID
ISIN
LEI
Companies House ID
Tax ID
VAT number
Snowflake ID

Ask if not listed above - others are provided

Website or email (encouraged if no Direct Match ID provided)
HQ region
Industry name

Direct Match IDs enable a direct match to the corresponding entity in DitchCarbon's system. When no Direct Match ID is provided, a fuzzy match to records in DitchCarbon's database is attempted.

Direct Match Available

Direct Match IDs enable immediate matching to corresponding entity in DitchCarbon's system

No Direct Match ID

Fuzzy match attempted against records in DitchCarbon's database

High Confidence Match

Request resolves to the relevant Organization

Low Confidence Match

Request moved to "waiting" status - user can provide more input data

If fuzzy match confidence is high enough, the request will resolve to the relevant Organization. If match confidence is not high enough, the user request is moved to "waiting" status, providing the user with the opportunity to provide more input data to resolve the request.

Organization Data Cascading Down Corporate Trees

DitchCarbon maps user inputs to corporate legal entity trees to ensure complete coverage of climate action across the corporation, while precisely reflecting lines of corporate control.

A user's request may successfully resolve to a subsidiary Organization and corresponding legal entity in DitchCarbon's database.

If the subsidiary Organization has disclosed emissions data, set reduction targets, or signed up to initiatives we track, those data points are provided in the Organization record payload.

If the subsidiary Organization does not have a given category of data, but a parent in its corporate tree does, that data cascades down from the parent Organization to the subsidiary Organization.

To enable auditability, user requests show the requested Organization's legal name, the parent Organization's legal name, and the relationship between the two entities (eg, L2 parent, ultimate parent)

Example:

If a user requests Beats Electronics, the subsidiary Organization (Beats Electronics, LLC) does not have emissions data, targets, or initiative participation, but its parent (Apple, Inc) does Apple Inc's Scope 1-3 upstream emission factor, targets, and initiative participation cascade to the Beats request, and the "ultimate parent" relationship between the two entities is displayed.
Example of organization data cascading down corporate trees

See example request, with subsidiary and parent Organization relationship type displayed:

Example request with subsidiary and parent Organization relationship type displayed

Data Ingestion

Our automated extraction engine and human QA process handles common issues that users of primary emissions data encounter regularly:

  • Differentiation between gross and net emissions disclosures in separate fields
  • Normalization of reported units to kgCO₂e
  • Mapping disclosed categories to GHG Protocol standard categories, flagging unusable data points
  • Human checking of validation warnings triggered by anomalous data

Portability

All data is exportable in structured format via xls/csv.

Original source links are provided, and mirror urls of documents saved on DitchCarbon servers are also provided (to ensure auditability if documents are moved). See sample reduction target export:

Sample reduction target export

Organization-Specific Spend Based Emission Factors

DitchCarbon generates up to three different organization-level emission factors per organization for each year. Emission factors are based on the organization's disclosed global consolidated revenue and global emissions data.

Emission factors are only generated if all minimum data requirements are met. If all minimum requirements are not met, the related emission factor fields will be left blank.

Emission factors are disclosed in kgCO₂e/USD.

Emission FactorMinimum Data RequirementsOther Calculation Logic
Scope 1+2 / revenue- Global Scope 1 and 2 available
- Global consolidated annual revenue data available
If multiple Scope 2 values available, prefer:
1) market-based 2) unspecified "total" 3) location-based
Scope 1+2+3 (upstream) / revenue- Global Scope 1, 2, and all relevant upstream scope 3 categories disclosed
- Global consolidated annual revenue data available
See above, and:
If all relevant Scope 3 upstream categories are disclosed, then calculate
All disclosed upstream scope 3 categories are included in calculation, not just "relevant" categories
Scope 1-3 / revenue- Global Scope 1, 2, and all relevant scope 3 categories disclosed
- Global consolidated annual revenue data available
See above, and:
If all relevant Scope 3 categories are disclosed, then calculate
All disclosed scope 3 categories are included in calculation, not just "relevant" categories

Methodology for Determining Relevant Scope 3 Categories by Industry

Organization records have a primary Industry. Each Organization disclosure is checked against the relevant criteria for a company within its Industry.

For relevance criteria, CDP's Scope 3 Technical Note is used for 16 heavy emitting industries.

For industries that CDP does not cover, their meta-analysis methodology is borrowed to determine relevant categories. This was done by evaluating significant samples of the global emissions reports of publicly listed companies disclosing scope 3 category detail within our database. Only reports disclosed in 2022 or later were considered in the meta-analysis.

Revenue Data: Sourcing and Traceability

Annual revenue data is sourced from S&P Global, which provides revenue sourced from financial disclosures and converted into USD. This accounts for >99% of DitchCarbon's revenue data.

In cases where S&P Global revenue data is not available for large/listed companies, DitchCarbon may acquire revenue data disclosed directly on the organization's website. This accounts for <1% of DitchCarbon's revenue data.

In all cases, original source urls are retained and provided to users for audit purposes.

Organization Emissions Data: Sourcing, Traceability, and Entity Resolution

Emissions data is extracted from Documents disclosed by Organizations.

Documents may be discovered as annual reports disclosed online in PDF or other formats, data disclosed in html on Organization websites, or as reports submitted directly to DitchCarbon.

Original sources are retained, and a copy of each document is saved on DitchCarbon's servers. Users are provided the original source url and a mirror url generated from the DitchCarbon server copy, ensuring data audit trails can be maintained if reporting Organizations move their reports.

Reporting entity legal entity names are extracted from Documents, and matched to the DitchCarbon Organization with the same legal entity name.

Extracted Emissions Data Structure:

Gross CO₂e emissions data points are extracted from Documents and mapped to fields based on the emissions boundaries of the GHG Protocol standard

  • Scope 1, with subcategories (eg mobile combustion)
  • Scope 2 market-based, location-based, unspecified "total", and subcategories (eg purchased heat)
  • Scope 1 and Scope 2 total (disclosed together)
  • Scope 3 categories (15)

Proprietary libraries translate extracted emissions data point units into kgCO₂e and attempt to map to standard GHG Protocol standard emissions boundaries.

Emissions data from Documents are merged into Organization Yearly Performances. To account for companies restating their emissions, datapoints from Documents disclosed in more recent years overwrite data from Documents in less recent years.

For example, if an Organization has two documents - a 2024 annual report with 2022-2024 data, and a 2023 report containing 2021-2023 data - the 2022 and 2023 performances from the 2024 report will overwrite data from the 2023 report.

See Data Dictionary for more detail on specific fields

Entity Resolution: Matching User Requests to DitchCarbon Organization Records

Users may provide a combination of inputs:

Name (required)
Direct Match IDs (encouraged if available)
DUNS
S&P Global ID
ISIN
LEI
Companies House ID
Tax ID
VAT number
Snowflake ID

Ask if not listed above - others are provided

Website or email (encouraged if no Direct Match ID provided)
HQ region
Industry name

Direct Match IDs are a direct match to the corresponding entity in DitchCarbon’s system. When no Direct Match ID is provided, a fuzzy match to records in DitchCarbon’s database is attempted.

If fuzzy match confidence is high enough, the request will resolve to the relevant Organization. If match confidence is not high enough, the user request is moved to “waiting” status, providing the user with the opportunity to provide more input data.

Emission Factor Cascading Down Corporate Trees

If user requests successfully resolve, they match to the Requested Organization record in DitchCarbon's database.

If the Requested Organization has an Organization Emission factor, it will be delivered. If the Requested Organization has not disclosed all Minimum Data Requirements to generate a Scope 1-3 upstream emission factor, but a parent entity has, the emission factor will cascade from the parent entity (ie the Matching Organization) to the Requested Organization.

Emission factors do not cascade up family trees, only down from parent to subsidiary entities.

To enable data auditability, each user request shows the Requested Organization legal name, the Matching Organization legal name, and the relationship between the two entities (eg, L2 parent)

For example:

If a user requests Beats Electronics, the Requested Organization (Beats Electronics, LLC) does not have emissions data or revenue, but its parent (Apple, Inc) does. As the Matching Organization, Apple Inc’s Scope 1-3 upstream emission factor will be used in relevant emissions calculations, and the “ultimate parent” relationship between the two entities will be displayed.

See example export file with cascaded Matching Organizations:

Example export file with cascaded Matching Organizations

Data and Quality Assurance

As an emissions data aggregator (not an emissions data generator), DitchCarbon's role is to accurately represent Documents disclosed by Organizations, and enable users to evaluate that data.

To enable users to easily assess the quality of reports, DitchCarbon extracts assurance statements for each document, for Scopes 1, 2, and 3:

  • Assurance level received (limited, reasonable, unspecified, or none)
  • 3rd party assurer
  • Extracted assurance statement text
  • Additional assurance url, if provided

To ensure accurate capture of emissions data into our system, each Document follows an 18 step process leveraging machine learning and logging each state. Human and machine extraction are used depending on the characteristics of the Document.

A system of rules-based validations triggers human QA review of potential extraction failures.

In some cases, these validation warnings catch obvious mistakes made by the disclosing entities (for example, incorrectly reported units), which are then flagged to users and the reporting entity.

DitchCarbon Score 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 criteria enables better decisions and drives improvement. This is why we disclose the factor categories and relative weights that the DitchCarbon Score takes into account:

Factors Increasing ScoreWeightSource
Reduced absolute emissions: last year
High
Primary data – company disclosures
Reduced emissions intensity (revenue adjusted): last year
High
Primary data – company disclosures
Committed to SBTI: Net Zero
High
SBTI database
Are in a very low or low emitting industry
High
Exiobase, DEFRA, EPA EEIO databases
Reduced absolute emissions: previous 2 years
Medium
Primary data – company disclosures
Reduced emissions intensity (revenue adjusted): previous 2 years
Medium
Primary data – company disclosures
Disclosed Scope 1, 2, and 3 emissions: last year
Medium
Primary data – company disclosures
Reported all industry-relevant Scope 3 categories: last year
Medium
CDP relevance criteria | company disclosures
Committed to SBTIs: Near Term or Long Term
Medium
SBTI database
Is a Climate Pledge signatory
Low
Climate Pledge database
Committed to at least 1 UN Global Compact environmental initiative
Low
UNGC database
Disclosed to CDP: last year
Low
Public disclosures
Disclosed Scope 1, 2, and 3 emissions: previous 2 years
Low
Primary data – company disclosures
Disclosed to CDP: previous 2 years
Low
Public disclosures
Reported all industry-relevant Scope 3 categories: previous 2 years
Low
CDP relevance criteria | company disclosures
Is headquartered in a very low or low emitting country
Low
National grid intensity disclosures
Received assurance on last year's report
Low
Public disclosures

Other factors that will be added to the Score algorithm soon:

  • Other initiatives: Race to Zero, Climate Action 100, RE 100, Ecovadis (if publicly disclosed)
  • CDP Score
  • Comprehensiveness evaluation of net zero or near-term targets published

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:

  1. 1Industry mean score: the average score globally for companies classified in the same industry
  2. 2Percentile benchmark: a Score's percentile rank compared to its industry average.

Industry Average Emission Factors

DitchCarbon provides over 200 industry emission factors for 43 countries and 5 global regions.

Each industry emission factor has an industry, a region, and a year, presented in kgCO₂e/USD. For example, "2022 US steel" or "2024 Egyptian business services".

Each user input is mapped to an industry emission factor, regardless of if more granular data (such as organization specific spend-based emission factors) are available. When more granular data is not available, industry emission factors are used as a fallback for embodied emissions calculations.

Sources and Traceability

Emission factors are generated from EEIO data published by environmental researchers and government agencies at the US EPA, Exiobase, and DenStore.

The specific source used depends on the user's requested Organization, and the Organization's industry and region inputs.

Source urls are always cited in our web app exports and API responses:

Source URLs cited in web app exports and API responses

Industry Emission Factor Selection

Industry emission factor selection requires both industry_name and region selection.

Users may provide unstructured inputs for either industry_name or region as inputs for each Organization requested.

If user inputs are provided, they are mapped to the appropriate classification and used. If the user does not provide either of these fields, data from DitchCarbon's matching Organization record are used as fallbacks.

Mapping user-provided industry_name to DitchCarbon industry:

  • Our system leverages our library of >10,000 confirmed matches to match user inputs to the best industry classification.
  • For inputs our system has not seen before, our proprietary model selects the best match
  • DitchCarbon's QA team may manually adjust matches if appropriate

Mapping user provided region to DitchCarbon region:

  • If the input region is one of 43 covered countries, this is used to select the appropriate industry_emission_factor
    Example: Mexico has an industry emission factor for automotive manufacturing
  • If region is not one of 43 covered countries, fall back to the appropriate region from among 5 global regions
    Example: Morocco is not covered, so falls back to “World Africa”

Transformations for inflation and grid intensity

EEIO datasets are updated irregularly. Where reported values for a given year are not available, we adjust the closest historical year's values for inflation and grid intensity to generate a future year value (always transforming forward in time, not backwards).

Grid intensity adjustments:

  • All database industries are assessed with the method IPCC 2013 GWP 100a V1.03, impact category IPCC GWP 100a
  • The contribution of the grid emissions to each industry's total footprint is calculated using data from the EU27 Input-Output Database
  • The grid portion of the industry emission factor is adjusted for changes in grid intensity over time, as reported by national grids

Inflation adjustments:

  • Adjusted for inflation using data from the US Bureau of Labor Statistics and the Bank of England

Forecasting Module

The forecasting module enables users to forecast their annual embodied emissions out to 2050 based on reduction targets their organizations have or have not set, and to what degree the user believes those targets will be achieved.

Users can configure multiple forecast scenarios, and plot these against their own Scope 3 targets to understand if they are on track to hit their own Scope 3 goals, and which organizations are driving potential gaps:

Multiple forecast scenarios configurationForecast scenarios plotted against Scope 3 targets

Forecasts are calculated at the "Project" level in DitchCarbon's web app. Underpinning each project forecast is individual organization forecasts, which are calculated using extracted reduction targets and user configurations

Reduction Target Sources

Source TypeDescriptionExample source url
SBTiRowStructured targets extracted from SBTiSBTi
DocumentTargets captured from annual reports or website announcementsIBM
IndustryGlobal initiatives for cross-border (global native) sectors: maritime and aviationIMO
Region-IndustryTargets set by specific sectors in specific regions, eg "German automotive"EU for select sectors
RegionNet zero targets set by regionsSingapore regional plan

Targets are structured as follows:

  • Scope: scope 1, scope 2, scope 3 (upstream), scope 3 (all), all scopes
  • Type: absolute, intensity, net zero, or climate-neutral
  • Start and target year
  • Reduction target

Relevant organization targets are selected and applied for each forecast year, by emissions scope, to an Organization's overall forecast in priority level. SBTi validated targets have highest priority, with fallbacks down to Regional targets, if configured to apply in the given scenario.

A selected target's implied cumulative annual average reduction rate is calculated and applied for the relevant forecast years to its relevant emissions scopes.

Target cascading

If a requested organization has set its own targets, those will be used. If not, a parent entity's targets can cascade down the family tree from parent organizations to requested subsidiary organizations. Targets do not cascade upward.

Configuration

Each scenario can be configured across the following attributes:

Forecast scenario configuration attributes

Targets to use:

  • Users may choose to only give credit for organization-specific targets, or apply other targets as fallbacks where organization-specific targets are not available

Target attainment rate:

  • User may discount organization target attainment rate, by source type
  • For example, if organization sets a target to scope 1+2 by 20%, and scope 3 by 10% by 2030, but user configures that they will only make 90% of that reduction progress by the target date

Spend growth rate:

  • How much is user's spend growing with organizations

Revenue growth rate:

  • How much is organization's revenue growing over time

Fixed assumptions:

  • Inflation is assumed at 2% per year for organizations based in OECD headquartered organizations and 5% for non-OECD headquartered organizations

Forecast calculation

As with embodied emissions calculations in the DC platform, organization-specific spend based emission factors are used if organizations have disclosed all relevant upstream categories for their sector, and if revenue data is available.

Organization emission factors can cascade from parent entities to requested child entities if the child entity has not disclosed enough information to generate its own emission factor.

If an organization-specific spend based emission factor is not available, fallbacks to industry average emission factors are used.

Once an appropriate emission factor for the organization is selected, embodied emissions are calculated for future years as follows:

  • Forecast future spend by applying spend growth configuration
  • Generate an average annual reduction rate implied by the applied target and attainment rate configuration
  • Forecast future emission factor by applying inflation assumption and generated average annual reduction rate
  • Calculate forecasted embodied emissions by multiplying future organization emission factor and future user spend

When no target is available given the user's configuration, embodied emissions will grow based on spend, revenue, and inflation inputs.

Portability

Underlying structured target and forecast data is exportable via xls/csv, with original sources and mirror urls provided (in case document locations are moved after capture):

Exportable structured target and forecast data