Digital Product Passport Software in the France



Measuring product footprints is hard work. Data is often incomplete, assumptions creep in, and getting inputs from across teams and facilities can be a challenge.

At Carbon Trail, our goal is to make lifecycle assessments (LCAs) more reliable, transparent, and easier to manage. This month, we’re excited to announce three new capabilities designed to do just that.

📊 Uncertainty Analysis

When you calculate a product footprint, you now get more than just a single number.

• Each result includes a 95% confidence interval, showing the range your impact is likely to fall within.

• You also see the uncertainty contribution of each process or material. For example, knitting might account for 50% of your uncertainty, while spinning contributes 22%.

This makes it easier to know where to focus your data collection efforts to narrow the range and improve accuracy.

⚖️ Sensitivity Analysis

Sometimes, you’re not fully sure about an input—like product weight or energy use. Instead of guessing, you can now test scenarios.

• Run calculations with different values (e.g., 150 g, 200 g, 250 g).

• Compare results side by side to see how sensitive your footprint is to changes.

This gives you confidence about which assumptions matter most, and which ones won’t significantly affect your results.

📩 Data Requests

Collecting data across teams and facilities is often the hardest part of carbon accounting. We’ve built a workflow to make it easier:

• Create structured requests for data (e.g., energy, transport, fuels).

• Assign responsibilities to specific users and facilities.

• Set priorities and deadlines, and track responses in one place.

• Once approved, the submitted data flows directly into your inventory and emissions are calculated automatically.

This keeps your data collection organized, auditable, and less reliant on messy email chains.

With these updates, Carbon Trail makes it easier to handle uncertainty, test assumptions, and collaborate on data collection—all critical steps toward accurate and actionable LCAs.