Sustainability Reporting Must Now Be Machine-Readable
XBRL tagging for financial reporting has been a requirement for years. Now the same standard is coming to sustainability reporting — and this change will fundamentally affect how sustainability teams collect data.
CSRD (Corporate Sustainability Reporting Directive) requires companies to present their sustainability disclosures in a machine-readable format. Article 29d of Directive 2022/2464 mandates that sustainability reporting be presented with XBRL tagging under the European Single Electronic Format (ESEF) framework (European Parliament and Council, 2022).
The purpose behind this requirement is clear: enabling investors, regulators, and data providers to automatically compare sustainability data from thousands of companies through the European Single Access Point (ESAP). Until now, sustainability reports have been published largely as PDF files or web pages — unstructured, closed to automated comparison, each company using its own format. XBRL tagging changes this fundamentally.
Understanding What XBRL Actually Does
XBRL (eXtensible Business Reporting Language) is a markup language that assigns standard tags to data. When a PDF states "Scope 1 emissions: 45,000 tCO2e," this information is meaningful only to the human reader. When the same information is XBRL-tagged, machines can automatically recognize what the number represents (Scope 1 emissions), its unit (tCO2e), reporting period (FY 2025), reporting entity, and ESRS reference (E1-6).
The ESRS digital taxonomy, developed by EFRAG, includes an XBRL tag library covering all ESRS disclosure requirements. This taxonomy follows the structure below (EFRAG, 2024):
- General requirements: Tags under ESRS 1 and ESRS 2 (governance, strategy, risk management, metrics)
- Environmental standards: All disclosure data points from E1 (Climate) through E5 (Resource Use and Circular Economy)
- Social standards: Tags from S1 (Own Workforce) through S4 (Consumers and End-Users)
- Governance standards: G1 (Business Conduct) tags
The total tag count covers thousands of data points. This represents the most granular digital standardization of sustainability reporting to date.
Lessons from Financial XBRL Experience
Listed companies in the EU have been submitting their financial statements in iXBRL (inline XBRL) format under ESEF since 2020. Important lessons emerge from this experience:
The first years were difficult. Many companies encountered tagging errors in their initial ESEF reports — wrong taxonomy references, missing tags, unit mismatches. According to ESMA (European Securities and Markets Authority) reviews, a significant proportion of first-year reports had quality issues (ESMA, 2022).
The automation gap is significant. Companies that handled tagging manually (once a year, at the final stage of reporting) experienced materially higher costs and lower quality than those who integrated tagging into their reporting processes.
The audit process was affected. Assurance providers needed to check the accuracy of XBRL tags as well, expanding audit scope. The same will happen in sustainability reporting.
These experiences show that companies preparing for sustainability XBRL tagging must avoid the "last minute" approach.
Practical Implications for Enterprise Teams
Data Collection Processes Need Redesigning
The most significant impact of XBRL tagging is felt at the data collection stage. Taggable data means structured data. Many companies' current sustainability data collection processes work like this:
- Data is requested from different departments via email or shared spreadsheets
- Data is manually consolidated by the sustainability team
- The report is written in free-text format
- Published as a PDF
In this process, data points are unstructured. For XBRL tagging, each data point must be recorded in a specific format, with a specific unit, and a specific period reference. This requires data collection processes to be redesigned from the ground up.
A practical approach: retroactively mapping the data points in the ESRS taxonomy to your data collection forms. Specifying which ESRS standard and which data point each form collects enables direct mapping at the tagging stage.
Technology Options
Four main approaches exist for XBRL tagging:
| Approach | Description | Suitable For | Cost |
|---|---|---|---|
| Dedicated XBRL software | Tools like Workiva, CoreFiling, ParsePort | Large companies, multi-framework reporters | Medium-High |
| ERP integration | Direct XBRL output from SAP, Oracle systems | Companies with ERP-based sustainability management | High (upfront) |
| Audit firm service | Tagging by Big 4 and mid-tier firms | First years, until capacity is built | Medium |
| Manual tagging | Direct iXBRL coding with taxonomy reference | Not recommended (high error risk) | Low (but rework cost is high) |
For most companies, leveraging audit firm services in the first year and transitioning to dedicated software from the second year is a pragmatic strategy.
Mapping ESRS Taxonomy to Your Data
The ESRS taxonomy developed by EFRAG defines one or more XBRL tags for each ESRS disclosure requirement. For example:
| ESRS Requirement | XBRL Tag Type | Data Format |
|---|---|---|
| E1-6: Scope 1 emissions | Numeric | tCO2e |
| E1-5: Total energy consumption | Numeric | MWh or GJ |
| E1-1: Transition plan existence | Boolean (yes/no) | Boolean |
| E1-4: Emission reduction target | Numeric + text | % reduction + description |
| GOV-1: Sustainability committee | Text | Narrative |
Preparing this mapping table now is the first step toward aligning your data collection and reporting processes with XBRL requirements.
Timeline and Phased Implementation
CSRD's phased implementation applies to XBRL requirements as well:
- Wave 1 companies (large PIEs, 500+ employees): XBRL tagging expected from FY 2024 reports
- Wave 2 companies (all large companies): For FY 2025, though the Commission may grant additional transition time
- Wave 3 (listed SMEs): From FY 2026, with optional deferral until 2028
The final version of the ESRS XBRL taxonomy is expected to be finalized in the second half of 2024. While a "wait-and-see" approach until the taxonomy is finalized may be tempting, starting data structuring work now saves time — because the vast majority of data points (GHG emissions, energy consumption, governance structure) are known before the taxonomy is finalized.
Context for Turkish Companies
Companies reporting under TSRS in Turkey do not yet face an XBRL requirement. However, for Turkish companies in EU supply chains, with EU subsidiaries, or receiving data requests from EU customers, XBRL awareness matters:
- When your EU customers report under CSRD with XBRL, the data format they request from you will align accordingly
- Suppliers who can provide structured data gain a strategic advantage by making their customers' reporting process easier
- KGK's digital reporting requirements under TSRS may emerge in the future
Preparation Action Plan
Short Term (0-6 months)
- Review the ESRS taxonomy draft: Examine EFRAG's published taxonomy documents
- Assess your current data structure: Is your sustainability data collected in a structured format, or scattered across free-text reports?
- Create a data point inventory: Map ESRS requirements to your existing data collection processes
Medium Term (6-12 months)
- Select a technology solution: XBRL software, ERP integration, or audit firm service
- Run a pilot: Test XBRL tagging for a selected ESRS standard (e.g., E1 — Climate)
- Coordinate with your audit firm: Discuss the XBRL dimension of assurance audits
Long Term (12+ months)
- Redesign data collection processes: Create XBRL-compatible structured data collection forms
- Launch training programs: Build XBRL awareness within the sustainability team
- Continuous improvement: Improve tagging quality with each reporting cycle
Key Takeaway: XBRL tagging may seem like the "technical back office" of sustainability reporting. But this requirement directly determines the quality of your data collection processes. Unstructured data at the collection stage creates serious workload and error risk at the tagging stage. The most efficient approach is to design the data collection process in alignment with XBRL requirements from the start.
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