CSRD Wave 1: First Cycle Lessons

What Wave 1 companies found hardest

The first CSRD reporting cycle revealed consistent patterns of difficulty across Wave 1 filers — providing invaluable guidance for Wave 2 companies now in preparation.

Scope 3 data quality: Category 1 (purchased goods) and Category 15 (investments for financial sector) were universally the most difficult Scope 3 categories. Most Wave 1 companies disclosed spend-based estimates with PCAF data quality scores of 4 or 5 — acknowledging high uncertainty. Supplier-specific data programmes are still in early stages. Wave 2 companies have an additional 2 years to build supplier engagement — use them.

Double materiality assessment documentation: Wave 1 assurers consistently flagged inadequate documentation of the materiality assessment process — specifically the stakeholder engagement inputs and the scoring methodology. The assessment outcome was often defensible but the process documentation was insufficient to support assurance conclusions. Wave 2 companies should build documentation-first materiality processes.

Non-employee worker data: ESRS S1-8 (non-employee worker headcount) was almost universally a gap — most HRIS systems do not systematically track contractors, agency workers, and self-employed persons. Wave 2 companies have 2 years to build contractor registries.

Biodiversity and water (ESRS E4, E3): Even for companies that assessed these topics as material, the site-level data infrastructure — IBAT screening, water metering by site, biodiversity impact assessments — was frequently underdeveloped. Wave 2 companies in sectors with E4/E3 materiality should start site screening immediately.

XBRL tagging — the unexpected challenge

XBRL tagging of the sustainability report was widely underestimated as a compliance effort in Wave 1 preparation. Companies that planned to 'add tagging at the end' found it consumed 4–8 weeks of intensive effort for a full ESRS report.

The tagging workload: A complete ESRS report for a large company has 800–1,200 tagged datapoints. Each datapoint must be matched to the correct EFRAG ESRS XBRL element, formatted correctly, and validated before ESAP filing. Manual tagging using XBRL authoring tools is error-prone at this scale — automated tagging from structured ESG data platforms is significantly more reliable.

Quality issues in first-year tagging: Early ESAP filings from Wave 1 companies showed significant tagging errors — incorrect element selection, missing mandatory tags, inconsistent unit formatting. ESAP validation rules rejected some filings entirely, requiring resubmission.

Assurance of XBRL: Limited assurance covers the XBRL tags as part of the sustainability report. Assurers flagged XBRL errors as findings — in some cases requiring restatement of the digital filing after assurance completion.

Wave 2 lessons: Implement ESG data platform with automated XBRL output from the start of your data collection programme — not as a final-stage addition. Budget 6–8 weeks for XBRL implementation and testing before first filing. Engage your assurer on XBRL quality early — do not leave XBRL validation to the final assurance review.

Assurance market realities from Wave 1

The limited assurance market for Wave 1 CSRD reports revealed supply and quality challenges that Wave 2 companies must plan around.

Capacity constraints: The assurance market was significantly tighter than anticipated — Wave 1 companies that engaged assurance providers less than 12 months before filing faced delays, premium pricing, and in some cases inability to complete assurance in time. Wave 2 companies should engage their assurance provider immediately — not wait until 2027.

Assurer readiness variability: Not all assurance providers had adequate ESRS expertise for Wave 1 engagements. Some companies received assurance opinions that later attracted regulatory questions due to methodology weaknesses. For Wave 2, seek providers with demonstrated Wave 1 CSRD assurance experience — ask for specific Wave 1 client references.

The documentation finding: The most common assurance finding across Wave 1 was inadequate documentation — data exists but the trail from source to reported figure was unclear. This is addressable: build source data retention into your data collection system from day one. Every reported figure should have a documented calculation workbook with source reference.

Scope 3 assurance: Assurers applied higher uncertainty tolerances for Scope 3 — particularly spend-based Category 1. Most Wave 1 reports received limited assurance conclusions on Scope 3 with explicit caveats about data quality. This is expected and acceptable for first-year reporting — the trajectory matters more than first-year precision.

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