#Knowledge
Climate strategy & accounting
Not Every CO₂e Question Requires the Same Level of Data Detail
When estimates are sufficient – and when more detailed data is needed
When estimates are sufficient – and when more detailed data is needed
Anyone who has worked with emissions data knows the challenge: data is available at different levels of quality, is not always complete, and collecting it can require considerable effort.
At the same time, the question often arises as to how precise the data actually needs to be. Are estimates and average values sufficient, or are detailed activity, product or supplier data required?
The answer depends on the question at hand. For some purposes, approximations may be sufficient, while others require significantly more detailed data.
So which emissions data is actually needed for which decisions?
That is exactly what this article explores. We show which types of data are useful for typical use cases and where greater data granularity can provide real added value.
Emissions data can be based on very different types of underlying information. While estimates, average values or spend-based data often provide an initial overview, activity data as well as product- or supplier-specific information provide a more detailed basis for analysis and decision-making.
In simplified terms, the following levels of data can be distinguished:
As data granularity increases, emissions can be calculated more accurately and measures assessed more precisely. At the same time, however, the effort required to collect the data also increases.
In practice, different levels of data quality are therefore often combined: detailed data where specific decisions need to be made or measures managed, and a more pragmatic approach where initial orientation is sufficient.
The following overview shows several typical use cases.
Practical example
An initial screening shows the relative scale of individual emissions categories and helps determine whether, for example, purchased goods or the use phase of sold products have the greater impact on total emissions.
Question:
Which Scope 3 categories should we examine in more detail?
Level of data detail
Activity data and, where possible, specific supplier or product data
Practical example
Categories with a high share of emissions identified in the hotspot analysis are examined in more detail. For example, suppliers can be asked to provide emissions data, or additional data on employee commuting can be collected through an employee survey.
Question:
What are the emissions of a product?
Level of data detail
PCF based on product-related activity data and, where possible, supplier or product data
Practical example
Some of the data already collected for the CCF can also be used to calculate a Product Carbon Footprint. However, this data must be allocated to the respective product and often supplemented with material quantities or product-specific supplier data.
Question:
How do materials or suppliers differ in terms of their emissions?
Level of data detail
Comparable product or supplier data
Practical example
If a choice is to be made between two materials or suppliers, spend-based data is usually not sufficient. Instead, product-specific emissions data or CCF data is required in order to assess the differences on a sound basis.
Question:
Where should we focus our reduction measures?
Level of data detail
Activity data and, where possible, supplier- or product-specific data. Spend-based data alone is generally not sufficient, as it does not allow conclusions to be drawn about the actual emission drivers.
Practical example
If the hotspot analysis shows that purchased materials account for a significant share of emissions, it can be assessed, for example, whether a higher recycled content or alternative materials could reduce emissions.
Question:
Have our measures actually reduced emissions?
Level of data detail
Consistent activity data over several years
Practical example
If a measure is implemented, such as switching to HVO or reducing energy consumption, the relevant consumption data must be collected in a comparable way over several years. Changes in emission factors should also be taken into account in order to assess the actual emissions reduction correctly.
In practice, this means that companies do not need to collect all emissions data at the highest possible level of detail at the same time. What matters is increasing data granularity specifically where it provides additional value for decisions, measures and management.
This allows effort and resources to be focused on the areas where better data can deliver the greatest benefit.
A typical approach might look like this:
For example, an initial Scope 3 analysis may show that purchased materials account for a significant share of emissions. In this case, it is usually more useful to increase the level of data detail specifically for this category rather than refining all Scope 3 categories to the same extent. Depending on the question, this may involve using activity data, supplier information or product-specific emissions data.
The key is therefore not to aim for the highest possible level of data detail everywhere, but to increase it specifically where it provides additional value for decision-making.
