How does automated software handle Scope 3 data gaps?

Published 6 November 2026

How does automated Scope 3 software handle data gaps in supply chains?

DitchCarbon fills every line with the most accurate method available and records which one it used: a product carbon footprint first, then activity or service data the supplier has disclosed, then generic activity data on a published factor such as ecoinvent, then the supplier's own inventory applied to your spend, and an industry average only when all else fails. You get a complete baseline now, with every remaining Scope 3 data gap labelled.

DitchCarbon calls this a hybrid calculation, and it starts from verified emissions data for over 2 million organisations, built on primary emissions data wherever it exists. That includes published GHG inventories and product carbon footprints, CDP responses, EcoVadis scorecards, SBTi targets and data that suppliers declare on their own profiles. Because so much is already published, much of the gap closes before anyone is asked: a recent deployment reached 70% coverage of emissions with primary data within 2 weeks.

The same order applies to every line, so a supply chain of thousands of organisations is handled the way a list of a hundred is, with no manual triage.

In what order does the software fill a gap?

DitchCarbon starts with the most accurate method and reaches an industry average last. It works down five methods for every line and stops at the first one it has data for.

Rung 4 is the one most teams do not know is already available. The supplier's reported inventory is primary data under the GHG Protocol, the allocation to your spend is ours, and it costs you nothing beyond the purchase data you already hold.

For the full argument on moving lines up the order, see how to move from spend-based to supplier-specific data. One supplier can sit on several rungs at once: a product footprint for the item you buy most, its own reported inventory on the rest of your spend with it. DitchCarbon records the rung on every line, so the split across the five methods is a stated percentage of your baseline.

What happens when an organisation on your list has published nothing?

DitchCarbon looks further before it falls back.

1. Match the right organisation. DitchCarbon matches each line by entity resolution against DUNS, LEI, ISIN or VAT identifiers, or a company name alone where that is all the purchase data holds. A match on a name alone is still a match, so the data you already have is enough to start.
2. Roll up to the parent where needed. Procurement data usually names the operating entity. Where an operating entity has no data of its own, DitchCarbon rolls it up to its parent, so the parent's disclosures and commitments apply; where the operating entity has published its own figures, those are used.
3. Use what suppliers have already shared. Activity and product data that suppliers have provided through DitchCarbon for other clients, and agreed to share, is available to the next client from the start. Sharing is always the supplier's choice, and a disclosure made privately for one client stays with that client.
4. Regionalise the last rung. Where nothing has been disclosed and nothing can be obtained, the industry factor is regionalised automatically, so a truck manufacturer in the USA gets a different factor from one in China. Where a company has disclosed its own regional factors, those are used.

Where you need more than that for a line that matters, the request goes out prepopulated with what DitchCarbon already holds on the organisation and asks only for what you need: a site's energy use, the activity data behind what you buy, or a product carbon footprint for a named item. The supplier adds that detail to its own profile, which is a smaller job than a blank questionnaire. A recent deployment gained additional primary data from 30% of over 40,000 recipients. More on that route in low supplier response rates on Scope 3 and how to collect supplier emissions data.

Where does AI help close the gaps?

AI does the reading and matching that would otherwise take a team months, so the order of methods can run on every line of a large supply chain. In DitchCarbon, AI handles three jobs:

• Reads what organisations have published. Sustainability reports, GHG inventories, product carbon footprints and other disclosures are read and the figures, scopes and assurance levels extracted into each organisation's profile, with the source document attached.
• Matches your purchase data to the right organisations. Each line is matched by DUNS, LEI, ISIN or VAT identifiers, or a company name alone where that is all the purchase data holds.
• Links operating entities to their parent. Where the entity on the invoice has no data of its own, it is rolled up to its parent, so the parent's disclosures and commitments apply to every line they cover.

A team of 15 analysts checks what the AI reads, and data capture is annually assured by UL Solutions. The emissions figure on each line then comes from the method it lands on, so every number traces back to a source document or a named emission factor, and AI never invents an emissions figure. The result is time back for lean teams, with numbers you can defend within 2 weeks.

How can you tell which Scope 3 figures are estimates?

Every figure in DitchCarbon shows which method produced it, and the share of a baseline still on an industry factor is shown as a number. You can filter the baseline by method, see exactly which lines rest on a sector average, and watch that share fall. Ask any vendor to show that share on your own list.

That number is also what the GHG Protocol asks you to report. The Scope 3 Standard (chapter 11) requires a description of the types and sources of data used, and the percentage of emissions calculated using data obtained from suppliers or other value chain partners. With the method recorded on every line, that disclosure comes straight out of the baseline.

Behind the method sits the evidence an auditor follows. Every figure carries its source and change history, and the source documents are shown with their level of third-party assurance. DitchCarbon data has been used in emissions reports that were subsequently assured by ten different third-party assurance providers, including Big Four firms, and Fortune 100 companies use it in their annual reports. The Portal calculator is verified to ISO 14064-3, limited assurance, by UL Solutions, renewed annually, which makes DitchCarbon the only specialist Scope 3 tool with third-party assurance of its calculation methodology, and the verification report is downloadable from the trust centre.

How do Scope 3 data gaps shrink over time?

They shrink as organisations publish and as the suppliers where action moves the footprint most add detail. DitchCarbon makes both happen without a new project each year, from two directions.

• Continuous refresh. As an organisation publishes a new inventory, a product footprint or a target, its profile updates with documented sources, and every line that uses it moves up the order on its own.
• Targeted requests. Requests go to the organisations carrying the most emissions with the least disclosed, sorted by the four-step maturity ladder, so the effort lands where a better figure changes the total. Each reply (a report, a site's energy figures, activity data, a product carbon footprint) is read into the same record and moves that line up a rung. The method is the same for 100 suppliers as for 10,000.

That matches the GHG Protocol's guidance (Scope 3 Standard, section 7.6): improve data quality over time, starting with activities that combine relatively low data quality with relatively high emissions. A line that moves from an industry average to the supplier's own figure changes the number, so DitchCarbon keeps the change history on every figure, which lets you separate a method change from a real reduction under your base year recalculation policy.

Suppliers already cutting emissions show up as they publish, so you can follow their progress against their own targets and let them carry on. The requests go to the ones you need something from.

What does the GHG Protocol say about filling Scope 3 data gaps?

It allows secondary data and proxies to fill gaps, as long as you choose them carefully, say how good they are, and replace them with better data over time. The Scope 3 Standard (chapter 7) sets out four points:

1. Secondary data can fill a gap (section 7.5). Prefer databases that are internationally recognised, provided by national governments or peer reviewed.
2. Choose by data quality indicators. Pick the secondary data most representative of the activity in technology, time and geography, and the most complete and reliable.
3. Proxy data is allowed where nothing of sufficient quality exists: data from a similar activity, extrapolated or scaled to fit (section 7.5).
4. Improve it and describe it. Early inventories may rest on lower quality data; companies should replace it as better data becomes available and must describe the data quality of what they report (section 7.6).

For the longer history of the hybrid approach, see solving Scope 3 data gaps with a hybrid approach. DitchCarbon's generic rungs (3 and 5) use a large library of published emission factors, including ecoinvent, CEDA, EPA, DEFRA and EXIOBASE, with the industry factor regionalised to where the organisation operates. The calculation is assessed as compliant with the GHG Protocol Scope 3 Standard and ISO 14064-1:2018, and the method column records data quality line by line, so DitchCarbon's baseline carries the data quality description the Standard asks for.

Being asked for this data yourself?

If a customer or investor has asked you for emissions data, what you have already published is where they start. Claim your company profile, free, to see what they see and add the detail they need once, for every customer who asks.