Which datapoints auditors test for ESRS E1 Scope 3 Category 7 commuting and how to make commuting emissions audit-ready.
If your company reports Scope 3 Category 7, auditors usually want more than one emissions total. They want a clear boundary, source data they can trace, and a written method that shows how commuting emissions were worked out.
As of 28 July 2026, ESRS reporting is lighter after the 3 July 2026 changes cut mandatory datapoints by more than 60%. But for employee commuting, the core audit checks stay much the same. If you run plant sites with shift work, site lists, and employee PLZ data, you still need figures that link back to site activity.
Here’s the short version:
In plain terms: if you cannot show where the number came from, the number is at risk in review.
For many German manufacturing and automotive sites, that means building the Category 7 model from site locations, PLZ data, and shift records instead of relying on rough estimates alone.
This article explains what still needs to be documented, what auditors tend to test, and what data setup helps your commuting figures stand up in an audit.
ESRS E1 is the CSRD’s mandatory climate standard. Employee commuting falls under Scope 3 Category 7.
For plant sites, this can become material fast. Shift work, fixed start times, and staff moving across more than one site tend to cluster travel patterns at the site level. That creates a simple reporting issue: auditors usually want site-level activity data, not just one rolled-up emissions figure for the whole company.
With the 2026 ESRS simplification, the number of datapoints and the narrative workload went down. But one thing did not change: companies still need an auditable Scope 3 Category 7 total and a documented methodology that shows how that total was calculated.
So the next step isn’t whether reporting still matters. It’s which datapoints still need to back up that total.
Section 1 covered why commuting still belongs in scope. This section gets into the numbers and records auditors will ask for.
Once commuting is in scope, they usually look for three things: a clear boundary, activity data they can trace back to source files, and a written calculation method.
Start by defining what sits inside the model. That could mean each plant, each legal entity, or the full site network. Whatever you choose, write it down clearly.
You also need to document which employee groups are covered and whether you calculate on a headcount or FTE basis. Then stick to that basis across all sites. If one site uses headcount and another uses FTE, the model gets messy fast.
Keep commuting separate from business travel so you don’t double-count emissions. They belong to different Scope 3 categories. You should also state whether teleworking is part of the commuting model. If it isn’t, exclude it the same way across the board.
Once the boundary is set, the next thing an auditor will ask is simple: what data is this based on?
For multi-shift sites, annual headcount on its own usually isn’t enough. Auditors often want the data source that shows when people are actually on-site.
The main inputs they expect are:
The method needs to show how site-level commuting patterns are turned into Scope 3 Category 7 emissions.
Document these points:
These details matter because auditors will trace reported emissions back to each source file and then test the assumptions behind the calculation.
| Datapoint group | Key items to document |
|---|---|
| Scope and boundary | Sites in scope, employee groups, headcount or FTE basis, commuting versus business travel separation, teleworking inclusion or exclusion |
| Activity data | Postcode-based distance, mode split, on-site frequency, source system for each input |
| Methodology | Formula, emission factors, distance logic, proxy rules, versioned assumption log |
This is general information only, not legal or tax advice.
Auditors will often accept estimates. But there’s a catch: the method has to be clear, and the evidence trail has to hold up from start to finish.
Trouble starts when site boundaries shift from one location to another, assumptions live only in someone’s head, or the reported number can’t be traced back to the source files. A figure can look fine on the surface and still fail review if the path behind it is messy.
Once the datapoints are in place, auditors check whether you used them the same way across the board. They look at whether one Category 7 rule was applied across all relevant sites and employee groups, and whether every exclusion has a written reason behind it.
If you left out a plant, you need to say why in writing. If you included it, the same inclusion logic should also apply to similar sites. A missing file, by itself, is not a reason auditors will accept.
After the scope is set, auditors work backward from the reported total. They trace the total to the model, then from the model to the source files behind each input.
That chain matters. If one link is missing, broken, or inconsistent, the figure fails traceability, even if it seems reasonable at first glance.
Most audit findings in Category 7 tend to fall into three patterns:
The main audit risk is pretty simple: if your commuting model can't be traced from start to finish, it can fall apart under review. triply deals with that at the model level, before you even open a reporting template.
To close the audit gaps above, triply starts with site-level inputs that auditors can trace back to source data. It builds a commuting baseline from site locations, employee postal codes (PLZ, the German postcode system), and shift patterns.
That means you don't need a full workforce survey. That's a big deal when HR data sits in different plants and shift schedules vary by site. Instead of waiting for patchy survey responses, triply models actual commuting flows from structural data and gives you one rule for inclusion across all sites.
Once the baseline is in place, you get the Category 7 inputs your audit file needs. triply provides the Category 7 datapoints and the calculation trail auditors usually ask for, covering:
Each output ties back to the underlying site, PLZ, and shift inputs. So when someone asks where the total came from, you can show the source data, the assumptions, and the method behind it.
The same baseline also works as a planning tool. You can use it to test shuttles, public transport subsidies, carpooling, or schedule changes before putting money behind them. In plain terms, it lets you check what might move the needle before you commit budget.
That also gives you a clean base for the next reporting round.
Once your baseline is in place, the next job is simple: close the audit gaps that still tend to trip teams up. In most cases, that means boundary, traceability, and assumptions.
Use this checklist for the next reporting round:
After the checklist is done, you can use the same baseline for both reporting and planning.
Before the next reporting cycle, keep these three points in view:
Ready to see what your Category 7 baseline looks like? Book a demo with triply to review your Category 7 baseline against your site data.
This is general information only, not legal or tax advice.
