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Users face significant challenges with data ingestion for Product Carbon Footprint (PCF) calculations, which is a major bottleneck. Bill of Materials (BOM) data arrives in diverse formats, including structured spreadsheets and unstructured PDFs, and often originates from multiple ERP systems. There is a need for software to efficiently process and integrate these varied data sources to enable scalable PCF calculations for a large number of SKUs.
The bottleneck for Product Carbon Footprints (PCFs) isn't the calculation, it's the data ingestion. A single manually calculated PCF can cost thousands and takes weeks to complete, which means for a company with 3,000 SKUs, the traditional approach simply isn't an option. I work with sustainability teams navigating exactly this challenge, and the same pain point comes up every time: getting the data in cleanly. BOMs arrive as structured spreadsheets, unstructured PDFs, and everything in between. The good news is that this is a solvable problem, and solving it turns PCF data from a compliance burden into a genuine commercial differentiator. I put together a write up about it at Normative.io on what scaling product carbon footprints actually requires – link in my comments. 👇