Most companies already have enough data to start. You can start with basic product data such as materials, weights, and formats. Pickler is designed to work with incomplete datasets, so you don’t need everything upfront.
The minimum data depends on the product setup, but useful starting data usually includes a product identifier, product name, material composition, product weight and the main material inputs. Additional data such as processing location, transport, packaging layers and end-of-life assumptions can improve representativeness.
Pickler is designed so teams can start with essential inputs and improve the dataset over time. Where some fields are missing, documented defaults or secondary data can help make calculations scalable, while primary data can be added later to improve quality.
A team may start with product names, weights and main materials from an ERP or spreadsheet, then enrich the dataset later with supplier information, transport routes and end-of-life assumptions.
Pickler helps structure product data into calculation-ready inputs and shows where better primary data can improve the quality of footprint results.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
Easily manage products in bulk through API or spreadsheets.
