From Commute Optimization to CSRD-Ready Reporting: A Workflow

If you want one workflow for commute planning, budget checks, and CSRD Scope 3 Category 7 reporting, this is the core idea: You use one shared commute model from start to finish.

That means you can:

• build a baseline from data you already have, such as PLZ, sites, attendance, and shifts
• test measures like shuttles, ÖPNV support, carpooling, parking rules, and shift timing changes
• compare options with the same metrics, such as load factor, cost per boarded rider, and kg CO2e
• turn the same output into a reporting view by site, employee group, mode, data source, and assumptions
• rerun the process each cycle so finance, HR, mobility, and reporting teams work from the same numbers

The point is simple: You do not need one model for planning and another for disclosure. You can use the same structure for both.

A few facts stand out:

• Scope 3 Category 7 covers employee commuting
• for many employers, commute data sits in separate systems
• site differences matter, especially with shift work, parking limits, and long travel distances
• if assumptions are not stored, the final figure is hard to trace back during review

Here is the workflow at a glance:

Step	What to do	Main output
1	Build a commute baseline from existing data	Current travel by mode, distance band, and site
2	Test mobility measures before budget approval	Expected uptake, cost, and emissions effect
3	Map outputs to CSRD Scope 3 Category 7 fields	Reporting view with source data and assumptions
4	Repeat on a set cycle across sites	Updated figures for each reporting period

In short: You start with the baseline, test changes before you spend money, and use the same model for reporting later.

1. Build a CSRD-aligned commute baseline from minimal data

Start with the data you already have

You do not need a full employee survey to build a credible commute baseline. Start with the data already sitting in your systems: home postal codes (PLZ), site locations, attendance patterns, and shift structures.

For employers with more than one site, the main problem is usually scattered data. One team has HR data, another has site data, and attendance may live somewhere else entirely. triply's consolidate step pulls these inputs into one commute view.

Turn raw inputs into a mode and distance baseline

Once those inputs are brought together, triply can model likely travel patterns. The result is a breakdown by transport mode, by distance band, and by site.

That means the baseline reflects actual geography and shift patterns without relying on survey responses. For shift-based sites, triply also accounts for timing and attendance, so the baseline lines up with how people travel in practice.

Document assumptions for auditability

For CSRD-ready reporting, document the data sources, missing-data logic, emission factors, and any modelled assumptions used to fill gaps. This matters because Scope 3 Category 7 figures need to be traceable, not just estimated.

triply stores those assumptions with the baseline, so sustainability teams and auditors can trace any Scope 3 Category 7 figure back to its source inputs.

That baseline then becomes the input for measure simulation in the next step.

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2. Simulate mobility measures before you commit budget

Once your baseline is in place, the next step is simple: test which measures are most likely to change commuting behaviour before you spend money.

Model the measures that fit large industrial sites

Large industrial sites usually deal with a few hard constraints at the same time: shift work, limited parking, and employees living across a broad area. So it makes sense to model measures that match those conditions, not generic office-based ideas.

triply models shuttle routes for shift-based demand, public transport support such as subsidies or employer-funded tickets, carpooling programmes, parking changes, and flexible scheduling adjustments that spread shift start times. Each measure is tested against the actual commute baseline, so the simulation reflects your site’s geography and workforce.

Compare each measure using the same decision metrics

Use one set of metrics across all measures so you can compare options on like-for-like terms.

Measure type	Expected uptake	Load factor	Cost per boarded rider	Scope 3 Category 7 emissions impact
Shuttle route	Modelled by site geography and shift patterns	Seats filled versus capacity	€ per boarded rider	kg CO2e or tonnes CO2e vs baseline
Public transport support	Modelled by commute baseline and access to existing public transport	N/A	€ per boarded rider	kg CO2e or tonnes CO2e vs baseline
Carpooling programme	Modelled by shift overlap and home locations	Load factor	Admin and incentive cost	kg CO2e or tonnes CO2e vs baseline
Parking changes	Modelled by site context and commute baseline	N/A	N/A	kg CO2e or tonnes CO2e vs baseline
Flexible scheduling	Modelled by shift structure	N/A	Operational cost	kg CO2e or tonnes CO2e vs baseline

This table is illustrative. Actual figures depend on your site data and modelled assumptions.

Using the same metrics across each option gives you a cleaner shortlist for implementation and reporting.

Use scenarios to avoid wasted spend

Scenario planning helps you test options like stop configurations, ticket support, or shift changes before anything gets approved. Each scenario runs against the same baseline, so the comparison stays clean and the assumptions are documented.

That makes sign-off much easier. You’re not relying on rough guesses or back-of-the-envelope estimates. You’re working from outputs that can be traced back to the same source model.

Keep the chosen scenario, assumptions, and uptake logic in that same model so the reporting step can pull from the exact same source.

3. Convert the commute model into CSRD-Ready Scope 3 Category 7 reporting

Use the scenario output from step 2 as the reporting input for CSRD Scope 3 Category 7 disclosure under ESRS E1 (Climate Change).

Map commute data to reporting requirements

Include all employees inside your organisational boundary, including remote workers, and split the data by site when commuting patterns change from one location to another.

The output from steps 1 and 2 already includes the fields needed for disclosure: site, employee group, transport mode, calculation method, data sources, assumptions, baseline emissions, and modelled impact. Because the scenario uses the same baseline, each figure can be traced back to its source input. That clear line back to the source is what makes the output easier to defend in an audit.

Report baseline and modelled impact in one structure

The table below shows the fields included in the output. Actual figures will depend on your site data and the assumptions used in the model.

Reporting field	What it captures
Site	The specific location the data covers
Employee group	Segmented by site or contract type where commuting patterns differ
Transport mode	The commuting mode used
Calculation method	The methodology used to build the baseline
Data sources	The source inputs used in the model
Assumptions	The assumptions applied in the calculation
Baseline emissions	Current commuting emissions for the reporting period
Modelled impact	The projected impact of the selected measure, compared with the baseline

The same structure also feeds the recurring site-by-site reporting cycle in step 4.

This article is general information, not legal or tax advice. Your finance, sustainability, or legal team should review any disclosure before it is submitted.

4. Run this as a repeatable workflow across sites and reporting cycles

Once your reporting setup is in place, don't let it go stale. Put it on a fixed cadence so the same baseline and scenario logic flows through every reporting cycle.

Set a simple operating cadence

Refresh employee and attendance data, rerun the commute model, simulate active or planned measures again, and update the Scope 3 Category 7 output. After new data lands, automate each refresh so the model stays current ^[1].

Store every updated output in one shared location so HR, finance, and sustainability are all working from the same version ^[1]. If assumptions or site conditions change, document that change and rerun the model right away instead of waiting for the next cycle.

Give each team a clear role

The workflow is much easier to keep steady when each team owns one clear part of the process.

Function	Primary contribution
Operations	Validates shift patterns, site constraints, and attendance data
HR	Supplies headcount, PLZ, and contract types
Mobility	Tests measure feasibility and updates scenario inputs
Sustainability	Owns reporting logic and the Scope 3 Category 7 output
Finance	Reviews cost assumptions and signs off on investment figures

For auditability, tag each data point as extracted or inferred so each figure stays traceable ^[1]. That kind of shared ownership helps the workflow stay steady from one cycle to the next.

Conclusion: One model, one workflow, one defensible reporting output

Once you’ve built the baseline, tested scenarios, reported the results, and run refresh cycles, the main point is pretty simple: one commute model can do two jobs. It helps you make better investment decisions, and it gives you CSRD-ready Scope 3 Category 7 output.

Start with the baseline. Then test measures against it, document assumptions clearly, and refresh the model on a fixed schedule so the output stays current across sites and reporting cycles. Each step flows into the next, which means the same model can support both decision-making and disclosure.

triply brings these steps together in one place. One shared model means fewer handoffs between teams, clearer assumptions, and a reporting structure you can defend.

Book a triply demo with your site data. You’ll leave with a baseline view, modelled scenarios, and a reporting structure you can defend.

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