Data collection is a crucial step in calculating the emissions embedded in your products for Product Carbon Footprint (PCF) assessments. This guide explains the process of gathering and entering the required data, ensuring accurate emissions calculations and improved Scope 3.1 reporting.
Why is Data Collection Important?
The data you collect directly impacts the accuracy of your product-level carbon footprint. Each product’s emissions depend on several factors, including raw materials, energy usage, and production outputs. Comprehensive and precise data collection ensures:
Accuracy: Provides reliable results for your product's carbon footprints.
Transparency: Enables clear reporting to customers, regulators, and stakeholders.
Consistency: Ensures results can be compared across suppliers, products, and methodologies.
Steps to Collect Data
1. Identify required data: Review the categories above and gather Bill of Materials (BOM), electricity, and fuel data consumption
2. Gather information from sources:
BOM:
Most manufacturers manage their BOMs in ERP systems like SAP, Oracle, Microsoft Dynamics, NetSuite.These systems can generate BOM exports (usually in Excel/CSV format).
A purchasing BOM or manufacturing BOM can be provided by procurement teams, as they manage supplier material lists and quantities.
In some industries (electronics, automotive, textiles), suppliers provide BOM files directly when delivering a product, including material breakdowns.
Electricity and Combustion:
For PCF, consumption allocation is mass-based. This means that energy and fuel use are distributed across products in proportion to their production output.
You will need, for the selected reporting period (e.g., 2023):
Total factory product output (eg. in tonnes).
Total electricity or fuel consumption (eg. in MWh or GJ).
Total product output specific to the assessment (the share of the factory’s output linked to the product being assessed).
3. Enter data into the tool: Navigate to your PCF assessment and input the values into the corresponding fields.
4. Save progress: Save as you go to avoid data loss.
5. Validate data: Cross-check totals and units (e.g., product outputs vs. energy usage) before running calculations.
Best Practices for PCF Data Collection
Collaborate with suppliers: Request accurate data on raw materials and embedded emissions. Our tool offers a specific product SPCF that allows to give to your supplier access so they can input primary data and improve calculations accuracy [maybe link for a sale call, it could be an Upsell driver]
Use standardized sources: Rely on consistent databases or utility records to avoid discrepancies.
Review regularly: Revisit and update data each reporting period to maintain accuracy.