Starting a scope 3 calculation can feel a bit like being handed a blank spreadsheet and told to fill in the entire supply chain. Where do you even begin? The good news is that you don’t need perfect data to get started — you need the right data. Understanding what to collect, where to find it, and what to do when it’s missing is what separates a calculation that stalls from one that actually moves forward.
This guide walks through the core data requirements for a scope 3 calculation, organized in a way that makes the process feel far less overwhelming. Whether you’re preparing for CSRD reporting, working toward an SBTi target, or simply trying to understand your full carbon footprint, getting your data foundation right is the most important first step.
The two types of data every scope 3 calculation relies on
At its core, every scope 3 calculation comes down to two types of data: activity data and emission factors. These two inputs work together to produce an emissions figure for each category you’re measuring.
Activity data is a measure of the business activity that generates emissions. This might be the amount of money spent with a supplier, the weight of goods purchased, the distance traveled by freight, or the number of employees commuting to work. It’s the “how much” of your operations. Emission factors are then applied to that activity data to convert it into a carbon equivalent. These factors represent the average greenhouse gas emissions associated with a given unit of activity, and they come from established databases such as those published by the GHG Protocol or national environmental agencies.
The reason this distinction matters is that the quality of your activity data largely determines the quality of your results. Emission factors are generally available from public sources, but activity data has to come from your own operations, finance systems, and supply chain. That’s where the real work begins.
Mapping your scope 3 categories to the right data sources
The GHG Protocol defines 15 scope 3 categories, split between upstream (categories 1 to 8) and downstream (categories 9 to 15). Not all of them will be relevant to your organization, but the ones that are will each require a specific type of activity data — and that data lives in different places.
Before collecting anything, it’s worth mapping out which categories apply to your business model. A manufacturing company will have very different material categories than a professional services firm. Once you know which categories are in scope, you can match each one to the data source most likely to hold the information you need. Some common pairings include:
- Category 1 (Purchased goods and services): This typically requires spend data from your finance or procurement system, or physical quantity data if you have it. It’s usually the largest category for most companies and the most data-intensive.
- Category 4 (Upstream transportation and distribution): You’ll need freight data such as distances, transport modes, and shipment weights, often held by logistics teams or third-party freight providers.
- Category 6 (Business travel): Travel booking systems or expense reports are your primary source here, covering flights, rail, and hotel stays.
- Category 7 (Employee commuting): This usually requires a survey of employees, since commuting data isn’t typically captured in any existing system.
- Category 11 (Use of sold products): For companies selling energy-consuming products, you’ll need data on how customers use those products over their lifetime.
Mapping categories to data sources before you start collecting saves a lot of back-and-forth. It also helps you identify early on which categories are going to be straightforward and which ones are going to need more creative approaches. That brings us to where you’ll actually find most of this data.
Where to find scope 3 data inside your organization
A surprising amount of the data you need already exists somewhere in your organization. The challenge is that it’s scattered across departments that don’t typically think about it in emissions terms.
Finance and procurement are usually your richest starting points. Spend data categorized by supplier or cost center can feed directly into spend-based emission calculations for purchased goods and services. Purchase orders, invoices, and supplier lists all become useful inputs. The accounts payable team may not know why you’re asking, but they almost certainly have what you need.
Operations and logistics teams hold data on transportation, warehousing, and product flows. If your company manages its own distribution, freight logs and fuel consumption records are valuable. If you outsource logistics, your third-party providers may be able to share transport data on request.
HR systems can help with employee headcount, office locations, and sometimes travel policies, all of which feed into commuting and business travel estimates. Travel management companies, if your organization uses one, often have reporting tools that make extracting this data relatively straightforward.
It’s also worth looping in your IT and facilities teams. Energy consumption data for offices and data centers may already be tracked for cost purposes, and that information can support calculations for leased assets and related categories. The point is that scope 3 data collection is rarely a solo task — it requires pulling together information from across the business.
When supplier data is needed — and what to do without it
For category 1 (purchased goods and services), the most accurate approach is to use primary data directly from your suppliers: their actual product-level emissions or environmental product declarations. In practice, though, most organizations can’t get this data from the majority of their suppliers, at least not right away.
When primary supplier data isn’t available, spend-based methods using environmentally extended input-output (EEIO) databases are the standard fallback. These databases assign average emission factors to spending categories, allowing you to estimate emissions based on how much you spent rather than what was physically produced. It’s less precise, but it’s widely accepted as a valid approach for initial calculations and for suppliers where engagement hasn’t yet happened.
If you’re prioritizing which suppliers to engage for primary data, focus on your highest-spend categories first. These will have the greatest impact on your overall scope 3 figure, so improving data quality there gives you the most meaningful accuracy gains. For lower-spend or lower-impact suppliers, spend-based estimates are often sufficient for the purpose of your calculation.
Common data gaps and how to handle them
Even with the best internal data collection effort, gaps are almost inevitable in a first scope 3 calculation. Some categories genuinely don’t have clean data sources, and some parts of the supply chain are simply hard to reach. Knowing how to handle these gaps is part of doing the calculation well.
The most common gaps tend to fall into a few patterns:
- Missing supplier data: When suppliers can’t or won’t share emissions data, spend-based or average-data methods fill the gap. Document your assumptions clearly so the methodology is transparent.
- Incomplete internal records: Finance systems don’t always categorize spend in ways that map neatly to GHG categories. In these cases, sampling a portion of transactions and extrapolating is a recognized approach.
- Employee commuting data: Since this isn’t captured in any system, a survey is the standard method. If a full survey isn’t possible, industry averages based on office location and employee count can serve as a reasonable proxy.
- Downstream categories: Data on how customers use or dispose of your products is notoriously difficult to collect. Product lifetime assumptions and average use patterns drawn from industry research are commonly used here.
What ties all of these approaches together is the importance of documentation. A scope 3 calculation with some estimates and proxies is still a valid calculation, as long as you’re clear about where those estimates came from and why you made the choices you did. Transparency about uncertainty is far better than false precision. As your data collection matures over time, you can revisit these gaps and replace estimates with more accurate inputs.
Ready to get your scope 3 calculation off the ground?
Getting the data right is genuinely the hardest part of a scope 3 calculation, and it’s also the part where having the right expertise makes the biggest difference. A scope 3 emissions specialist brings not just technical knowledge but also practical experience navigating the exact data challenges you’re facing — from procurement systems to supplier engagement to defensible methodology choices.
That’s where Dazzle comes in. We match organizations with pre-screened sustainability freelancers who specialize in exactly this kind of work. Whether you need someone to lead your full scope 3 calculation or help you work through a specific data challenge, we can connect you with the right expert within 48 hours. No long procurement processes, no agency overhead — just flexible access to the specialist knowledge you need, when you need it. Reach out to our team, and let’s find the right fit for your project.
