Sustainability Data: How Data Spaces Simplify ESG Reporting

AI Open Space

Sustainability Data: How Data Spaces Simplify ESG Reporting

Every sustainability reporting cycle follows the same routine in many companies: an email sent to dozens of suppliers asking them to complete a questionnaire about their emissions, energy consumption or labour practices; weeks of waiting; incomplete answers or conflicting information from suppliers in the same sector; and, ultimately, estimates used to fill the gaps left by real data that has not arrived in time. The result may tick the required boxes, but it does not accurately reflect what is happening across the value chain.

The underlying problem is not a lack of willingness, but a lack of infrastructure. The sustainability data required by European regulations does not sit within a single company. It is spread across suppliers, subcontractors, distributors and customers, each with their own systems and formats and, often, no clear incentive to invest time in generating information that another company needs for its own report.

For sustainability, ESG and finance managers at companies required to report under the Corporate Sustainability Reporting Directive (CSRD), this is not a problem that can be solved simply by sending better questionnaires. It requires rethinking how sustainability data flows between the organisations that make up a value chain. This is where data spaces are beginning to make a real difference.

Why sustainability data is different from other corporate data

A company's financial data is generated and managed within its own accounting systems. Sustainability data, by contrast, is distributed by nature. Scope 3 emissions — those generated across a company's value chain, including procurement, transport, the use of sold products and their end-of-life treatment — cannot be calculated without information from third parties.

This makes ESG reporting an exercise in coordination between organisations, rather than simply an internal accounting task. And coordination through manual questionnaires has structural limitations:

  • Each customer requesting ESG data from the same supplier tends to use a different format, increasing the supplier's workload without improving the quality of the information.
  • Data submitted through questionnaires is not always verifiable, forcing the reporting company to accept a level of uncertainty that the CSRD is specifically intended to reduce.
  • Data updates are slow: an annual questionnaire does not reflect operational changes that take place throughout the year.

The result is a sustainability report that meets the required format, but whose actual traceability and verifiability fall short of the standards pursued by European regulations.

What the CSRD actually requires regarding data sources

The Corporate Sustainability Reporting Directive, which implements the European Union's reporting framework aligned with the European Green Deal, gradually expands the number of companies required to report on their environmental, social and governance impacts, risks and opportunities. The information required includes greenhouse gas emissions divided into Scopes 1, 2 and 3, with the latter covering indirect emissions across the value chain.

The regulation does not simply require companies to report a figure. They must be able to explain how the data was obtained, how reliable it is and which methodology was applied when estimates were necessary. This means that data traceability — knowing where it comes from, when it was generated and under what conditions — is just as important as the numerical value itself.

This is where the current questionnaire-based model reveals its limitations: an Excel file sent by email does not provide verifiable traceability. By contrast, data shared through a data space can be accompanied by metadata about its origin, generation date and transfer conditions, while the exchange itself can also be recorded.

How a data space changes the flow of ESG information

A modern data space does not remove the need for suppliers to generate sustainability data. Instead, it transforms how that data flows between the organisations in a value chain.

From one-off questionnaires to continuous data flows

Rather than having each customer send an annual questionnaire to its suppliers, suppliers can publish their sustainability data — energy consumption, direct emissions and waste management indicators — in the data space's federated catalogue, using a shared vocabulary. Customers that need this information to calculate their Scope 3 emissions can access it through the transfer module instead of waiting for the next round of questionnaires.

This does more than save time: it allows information to be updated as frequently as the supplier decides, rather than remaining frozen at the moment an annual form was completed.

Traceability through a clearing house

Every sustainability data transfer carried out through the data space is recorded by the clearing house, the trusted third party that certifies agreements and transfers that have actually taken place. This provides the reporting company with verifiable evidence that the data used in its report genuinely comes from the declared source, strengthening the reliability required by the CSRD in the eyes of auditors and external verifiers.

A common vocabulary for ESG indicators

One of the main sources of friction in current ESG reporting is that every company requests data according to its own criteria: different units, different reporting periods and different definitions of what counts as "waste managed" or "renewable energy consumed". A data space incorporating shared vocabularies and data models for sustainability indicators helps reduce this fragmentation. A supplier publishing its data according to the common model makes that information usable by any customer within the data space, without having to adapt its response to each individual questionnaire.

Control over who can access which data

Sharing sustainability data does not mean giving up control over it. The data space's policy engine allows each supplier to define who can access its information, under what conditions and for what purpose. This means suppliers can contribute to their customers' ESG reporting without exposing sensitive data to unauthorised third parties or losing track of who has accessed what.

An example from a Castilla y León value chain

Consider a food processing company in Castilla y León that is required to report under the CSRD and needs Scope 3 emissions data from its agricultural raw material suppliers and logistics distributors. At present, this information is collected through annual questionnaires that produce inconsistent responses: some suppliers provide measured data, others submit estimates based on sector averages, and several simply fail to respond in time for the reporting deadline.

By joining a regional data space, both the company and its main suppliers publish their energy consumption and emissions indicators using a common data model. The food processing company accesses this information through the transfer module whenever it needs it for its Scope 3 calculations, with the clearing house record providing evidence that the data genuinely comes from each declared supplier. The annual questionnaire is no longer the only way to obtain information; instead, it becomes a complementary tool for collecting data that is not yet available in the data space.

The next step for your sustainability reporting

Regulatory pressure on sustainability reporting is not going away. Companies that rely exclusively on manual questionnaires will continue to face increasing costs in terms of both time and the quality of the data they ultimately publish. Adopting a data space infrastructure to exchange ESG information with suppliers and customers is a way to anticipate this pressure rather than struggle with it during every reporting cycle.

If your company needs to organise the flow of sustainability data across its value chain and improve traceability for CSRD reporting, look for a technology partner with experience in data spaces who can support you through the process and help assess how this approach fits your specific needs.