It's Martin from Carbonfact. Last month, we've been laser-focused on enhancing our Uncertainty Metric. Uncertainty—what's that, you ask? No worries, let's break it down with a real-world example and discover why it's Carbonfact's game-changing approach to product-LCA.
đź“– For a deeper dive on how we calculate the uncertainty metric - check out my new article.
We empower fashion brands to measure the environmental footprint of ALL their products in just a few weeks. Our secret sauce? Our unique Uncertainty Metric.
A Concrete Example: Imagine you're a fashion brand that produces denim jeans. During customer onboarding, we ingest all available data, like fabric type and manufacturing processes. In less than two weeks, we provide an approximate carbon footprint for your jeans.
Initially, due to assumptions and missing data, the result won't be 100% accurate. That's why we provide an "Uncertainty Range" for each product, material, and supplier. Think of it as a confidence interval: your jeans might have a footprint between 10-15 kg CO2e.
Here's where our Uncertainty Metric shines. It helps you focus on the most impactful data points—like the type of dye used or the energy source of your supplier—that can narrow that 10-15 kg CO2e range to, say, 11-12 kg CO2e. This saves you time and helps prioritize the small bandwidth of your sustainability team.
The Carbonfact platform is the first to use the Uncertainty Metric, a unique feature that tackles the biggest challenge in product Life Cycle Assessments (LCAs) for fashion: data collection. With this metric, we've made it possible for you to get fast, accurate, and affordable LCAs for your entire product range.
đź“– For a deeper dive on how we calculate the uncertainty metric - check out my new article.