How Data Quality Impacts Emissions Accuracy

The accuracy of your carbon footprint hinges on the quality of the activity data you provide. High-quality data allows for more precise emissions calculations, supports better decision-making, and strengthens the credibility of your sustainability reporting.

But what exactly makes data 'high quality' in the context of carbon accounting? And how do different types of data affect the results calculated by the Plan A Sustainability Platform?

This article introduces the key concepts behind emissions data quality, including materiality, primary data vs. national averages, calculation method accuracy, and the difference between data gaps and non-applicable data. Understanding these foundations will help you focus your efforts where they matter most and improve the overall accuracy of your carbon footprint.

In carbon accounting, materiality refers to identifying the business activities and their associated emissions categories which will have the largest impact on your overall carbon footprint. In this regard, a business activity’s ‘materiality’ can be understood as its significance to your emissions impact. If a certain business activity contributes only a small or negligible amount to the company’s wider emissions balance, it can be considered not material.

Even within emission categories, there can be differences in the materiality of certain business activities. For instance, for Purchased Goods and Services, your top suppliers (by spend amount) are likely to contribute far more to your emissions than the bottom 50% of your suppliers.

As such, it is important to ascertain which business activities are significant in your organisation and prioritise these when trying to improve your data quality.

Conducting a materiality assessment is recommended. This will promote efficiency in data collection by allowing you to focus on critical business activities and not waste time on immaterial business activities.

Primary data is specific to your business and its operations - put simply, it is data that you collect about your organisation’s business activities rather than national average data.

During the data collection process, the goal should be to collect as much primary data as possible, as this will ensure that the Corporate Carbon Footprint calculated by the Plan A Sustainability Platform best reflects your business.

However, it is not always possible to collect primary data, and in these cases, 'National averages' can be used as a fallback option. Using national averages allows you to approximate your carbon footprint in a given category based on your Organisational Data and national average conversion factors for particular business activities (i.e. the 'amount' of each activity).

The aim should be to use National averages as a last resort, especially for categories with significant materiality. As such, these should ideally be used as placeholders, with the intention of either updating your data once primary data is available or, at the minimum, removing barriers to collecting primary data for future data collection rounds.

For more information on collecting primary data, the Plan A Help Centre has guides on data collection for each emissions category.

For most categories, Plan A offers multiple calculation methods to accommodate different levels of data availability and formats. Each method varies in accuracy, with the most precise always marked as ‘recommended.’ In general, the more specific and detailed the input data, the more accurate the resulting calculation. For example, in Scope 3, Category 1: Purchased Goods and Services, using the Fashion: Average data method provides a more accurate estimate of emissions from fashion purchases than the broader Spend-based method.

To improve the accuracy of your emissions data, it is usually worth trying to collect the data required to use the ‘recommended’ calculation methods. Two key factors in making the decision to pursue currently unavailable data are:

We recommend weighing the two against each other and pursuing the new data when the effort required to source it is balanced against the business activity’s materiality.

Data gaps refer to any data points that have not been collected or uploaded to the Plan A Sustainability Platform, whereas non-applicable data refers to data points that are not applicable to your organisation, usually either because they are not material to your organisation's boundaries or because the business activity is simply not one conducted by your organisation.

Keeping track of data gaps and non-applicable data is important and will require you to organise your data collection and approach it as methodically as possible. Breaking data collection down into smaller chunks can help keep upload tasks manageable and easy to track. For example, delegating categories to team members can ensure that categories aren't missed. Similarly, keeping your data templates organised is key. To stay organised, make sure to keep an internal filing system for uploaded documents.

The Plan A Sustainability Platform is designed to make high-quality emissions data collection and management easier, even across complex organisations. It offers tailored guidance through step-by-step data collection instructions for each emissions category in our Help Centre, visual Overview dashboards that flag missing or incomplete data, and built-in tools to track upload history, such as the Activity log.

With flexible calculation methods and clear recommendations on how to improve accuracy, the platform supports you in moving from estimates and averages towards more precise, primary data. You can also invite team members to contribute directly, helping distribute the workload and improve collaboration across departments.