Product impact data often starts in spreadsheets, ERP exports, supplier files or incomplete internal lists. Before footprint calculations can scale, this data needs to be structured into consistent product records with clear materials, weights, assumptions and identifiers.

Pickler helps make product data usable by translating it into fields needed for product-level impact calculations. This does not remove the need for good primary data, but it gives teams a clearer structure for improving data quality over time.

A product list with inconsistent material names and missing transport data can be mapped into a clearer format, so products become easier to calculate, compare and update.

Pickler provides a structured product data model, spreadsheet workflows and calculation fields that help teams move from messy files to repeatable footprint outputs.