How to: Data Sourcing

Sourcing data is one of the biggest challenges when it comes to a company's carbon footprint.

Updated over a week ago

Sourcing data is one of the biggest challenges when it comes to a company's carbon footprint. It is important to consider when deciding the scope of your carbon footprint, and when deciding how to report activity data in the Log emission categories. Moreover, collecting data is challenging because the company needs to coordinate with its suppliers and customers as well as with internal departments of the company.

Why is it important to collect data with sufficient quality?

  • Ensure that the inventory appropriately reflects GHG emissions

  • Support company’s goals

  • Support decision making needs of users

Prioritizing data sourcing: screening method

The first step in data sourcing is to select the activity categories that should be of a high or low priority in order to focus data collection efforts on the former. Here are some criteria to base the screening process on:

Generally, significant activity categories should receive the most precise data sourcing treatment.

Data sourcing options

Cozero Logs offer activity data entry options. In general, a hierarchy of data entry options are offered. These are below, and listed from high to low data accuracy.

  • Primary data – Primary data is the most accurate because it’s the raw data that is directly measured or collected from the use of your product, a process, a facility, or a supplier. For instance: Amount of fuel consumed in a company vehicle.

  • Secondary data – Secondary data is not directly collected or measured but rather sourced from third-party databases. For instance: industry-average data (e.g. published database, statistics) or proxy data. Secondary data are generally less accurate than primary data as they are estimations or averages of data but they are useful when primary data is unavailable or of poor quality. For instance: Estimated distance traveled based on industry-average data.

  • Spend data – Spend data is data related to the expenditures on goods and services purchased from external suppliers and then multiplied by the corresponding emission factors (e.g. kg CO2e per €). These emission factors are based on environmentally extended input-output (EEIO) models. Spend data is generally the least accurate since EEIO data is clustered into large product categories and limited geographic regions.

Users should choose the method that is the most appropriate to the data available to them, to their business goals and the significance of the emissions of the category.

Getting started

The majority of your emissions could well lie within Scope 3, which could make these emissions simultaneously the most challenging and the most important.

Principles for getting started on data sourcing include:

  • Select the activity data that is readily available. Often, users start by sourcing spend-based data, and then build granularity over time.

  • Choose a manageable and representative sample of Locations to report emissions against.

  • Limit the number of suppliers you get emissions data from.

  • Select categories that are relevant for your business, and where data is available.

Build in detail

Once you are up and running you can add detail and quality over time, for instance by sourcing primary data from suppliers.

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