Introduction

In this 3rd module of the PCF Essentials course, we'll be discussing best practices for collecting data to build your first PCF: Module outcomes: Learn about the type of data you will need to collect to build PCFs Learn how to prioritize data collection needs and fill gaps in data completeness Learn how to prepare for, send data requests, organize received data and assess the completeness of a data set

What are good sources of data for PCFs?

There are a range of sources that might be useful when identifying appropriate data sources. These can include:

• Enterprise resource planning system (ERP) – this is likely to contain information about materials used in products and potentially other statistics on sold volumes, energy consumption, waste generation​

• Other internal inventory management systems​

• Meter readings and fuel consumption logbooks​

• Direct measurements from manufacturing processes​

• Data provided directly by suppliers ​

• Transport and logistics logbooks

• What is a step-wise approach to collecting data?

  Accurate data collection is essential for completing a product carbon footprint. This step often poses significant challenges. This module offers guidance on addressing these challenges effectively.

  The steps can be broken down into:

  1. Preparation work – identify appropriate contact points and build structured response templates to aid data requests​

  2. Send formalized requests – ensure communication of the importance of data accuracy, completeness, and timeliness. Establish a system to monitor responses.​

  3. Organize received data – organize data so that it can easily be referred to for PCF calculation​

  4. Assess completeness – are there any ongoing data gaps that would significantly impact the PCF score?

• What are the key things to consider when collecting activity data?​

  Activity data is a key input for the calculation of greenhouse gas emissions and refers to the data associated with the activities that generate GHG emissions. This might be energy consumption, distance travelled, or quantities of materials purchased. Collecting activity data is often the most significant challenge for compiling PCFs and so establishing robust activity data collection procedures can help streamline PCF generation across many products.
  

  1. Consistency – is the data consistent with other datasets you have available in terms of scope, interannual variations, and implied activity size. ​

  2. Completeness –does the data capture all the required information?​

  3. Representativeness – does the data truly represent your activities and product across your chosen reference period of study?

Cheat Sheet PDF

You can download a PDF version of this module below:

• PCF Essentials 3 - Data collection.pdf800 KB
• Category level data collection checklist.pdf900 KB
• SKU data collection checklist.pdf900 KB