Disclosure focus
The practical focus is on coverage and consistency across the organisation, not just on a few well-paid or flagship sites. Readers should be able to see whether the assessment applies across countries, business units and worker groups, and whether any differences in pay practices are linked to location, role or employment type.
This LRA educational guidance supports disclosure preparation. For the exact requirements, always refer to the official European Commission source.
Prepare
What to collect before drafting
Tick each field as the evidence lands. Owners are the teams that usually hold the source files.
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Adequate wage flag
Reward / HR analyticsRecord whether the organisation has checked if pay meets the chosen adequacy benchmark for the reporting population and period, and whether the result is yes or no.
Evidence Pay review output, wage benchmark calculation, HR or payroll summary, and the documented basis for the yes/no conclusion.
Watch for The yes/no flag is set without reconciling to the pay dataset used for the benchmark test, so the conclusion reflects the wrong population or period.
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Wage benchmark basis
Reward / sustainability reportingCapture the specific benchmark or reference point used to judge pay adequacy, including the named source and how it was applied.
Evidence Benchmark policy note, external reference document, internal methodology paper, or board-approved pay standard used for the assessment.
Watch for The benchmark basis is described using a different definition from the one applied in the calculation, so the reported reference point does not match the test performed.
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Affected countries
HR operations / financeList the countries where the pay adequacy check was carried out and where the result is relevant for reporting.
Evidence Country-level payroll extracts, entity mapping, and the consolidated reporting workbook showing which locations were included.
Watch for A country is omitted or added because the reporting perimeter does not reconcile to the legal-entity or payroll location list.
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Below-threshold share
HR analytics / payrollState the percentage of employees whose pay falls below the selected adequacy threshold for the reporting scope and period.
Evidence Headcount by pay band, threshold calculation, and the working paper showing the numerator and denominator used for the percentage.
Watch for The percentage is calculated with the wrong denominator, or the below-threshold group is defined differently from the threshold test, so the share does not reconcile to the underlying pay analysis.
Before you start
- Have you decided which parts of the workforce are included in this check, and which countries you will cover?
- Have you settled the pay benchmark you will use for the comparison, and is it the same basis across the countries in scope?
- Have you confirmed the cut-off date or reporting period for the figures, so the comparison is taken from one consistent point in time?
- Can you trace the headcount and pay data back to a source you can explain, rather than relying on an estimate?
- Have you agreed how you will identify anyone paid below the chosen benchmark, and how you will calculate the share of workers affected?
How to prepare it
Request the data
Request the pay-benchmark data and below-threshold headcount
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
Are our people paid at or above the pay floor we use, and if not, where and for whom does the gap sit?
Use your organisation’s own pay and reward language first, then map it to the reporting fields below. For example, if you talk about salary bands, pay floors, living-pay checks or local market benchmarks internally, use those terms in the request and only translate them into the reporting labels when you prepare the return. Check the source material before sign-off.
Weak request
Please provide the ESRS S1-9 adequate wages data, including whether we meet the benchmark, the benchmark used, countries affected, and the percentage of employees below threshold.
Why it fails: It uses framework language that many internal owners will not recognise, and it does not tell them which internal report, population, or counting basis to use. That makes the return harder to prepare and easier to misread.
Better request
Please send the latest pay-floor review extract for [period], showing the benchmark used, the countries or sites included, the headcount and share of people below that benchmark, and the report or system the figures came from. Use our internal pay and reward terms in the return, and add any scope or assumption notes.
Formal email template
Subject: Request for pay-benchmark data for [reporting period] Hi [name/team], Could you please share the latest extract for the pay review covering [reporting period]? We need the following, using our internal pay and reward terms where possible: - the benchmark used for the review; - the countries or locations included; - the number and share of employees paid below that benchmark; - the population and counting basis used; - the source system or report used to produce the figures. Please include any notes on scope, exclusions, or assumptions, and confirm who reviewed the numbers before they were sent. A possible LRA training template is attached below for reference only. Please adapt this to your organisation and check the source material before sign-off. Thanks, [preparer name]
Short Teams / Slack version
Hi [name] — could you send the pay review extract for [period]? Please include the benchmark used, the countries covered, and the number/share of people below that benchmark, plus the source report and any scope notes. Use our internal pay/reward terms in the return where possible. Please adapt this to your organisation and check the source material before sign-off. Thanks
Industry examples
Retail / Distribution
Context. A business with stores, depots and a head office wants one return across different pay structures.
Adapted request. Please share the pay-floor review for [period] across stores, depots and head office. Include the local benchmark used in each country, the number and share of colleagues below that floor, and the payroll or reward report used to build the figures. Please separate store, depot and office populations using our usual workforce labels.
Example response. Country: UK; Workforce group: Store colleagues; Benchmark: local living-pay check; Employees in scope: 4,820; Employees below benchmark: 96; Share below benchmark: 2.0%; Basis: headcount; Source: payroll extract v3; Notes: excludes seasonal staff.
Manufacturing
Context. A plant-based employer needs the data split by site and worker group.
Adapted request. Please provide the wage-floor review for [period] by site. Use our site and shift-worker labels, and include the benchmark used, the number and share of employees below it, and the system extract used for the analysis. Flag any sites where the pay floor differs by country or collective arrangement.
Example response. Country: Spain; Site: Valencia plant; Workforce group: Production operators; Benchmark: statutory minimum; Employees in scope: 1,140; Employees below benchmark: 0; Share below benchmark: 0.0%; Basis: headcount; Source: payroll and site roster; Notes: no exceptions identified.
Draft your disclosure
Notes that turn data into a disclosure
LRA training templates — adapt them to your organisation, and check the official source before sign-off.
Method note
Explain which pay benchmark was used, how the organisation defined the adequacy test, which countries were included, and how the below-threshold share was calculated.
Context note
Set out what the figures mean in practice by linking the chosen benchmark to the countries affected and the proportion of employees whose pay falls below it.
Fluctuation statement
If the figures changed, note whether that reflects a different benchmark, a change in the countries covered, or a shift in the share of employees below the threshold.
Content index entry
S1-9 Adequate Wages — [location / page] / [notes]Download Centre
Preparation tools & forms
Download preparation tools for S1-9 with free verified email access for 24 hours. Source-report links remain public.
Check
For each claim, check the evidence
We used a wage comparison basis that we believe is fit for purpose across the countries in scope, and we checked that the benchmark set we relied on meets the minimum screening criteria we applied for both EU and non-EU locations.
Risk The benchmark may be incomplete, outdated, or not suitable for one or more countries, which could make the comparison unreliable.
Evidence to check Benchmark methodology note; source documents for each benchmark; country-to-benchmark mapping; date of last update; internal review showing the criteria applied and why each benchmark was accepted.
For the calculation, we started from the lowest pay received by employees in the relevant population, left out interns and apprentices, added only the fixed pay elements that are guaranteed, and used the comparison level that matches the country or sub-national area concerned.
Risk The calculation basis may be inconsistent across locations or may include/exclude the wrong pay elements, leading to an overstated or understated result.
Evidence to check Payroll extracts; calculation workbook; definition of included pay elements; population filters showing interns and apprentices excluded; country or regional mapping logic; reviewer sign-off on the calculation approach.
We have identified which wage benchmark applies in each place and can show how each benchmark was assigned to the countries covered by the figure.
Risk A benchmark may have been applied to the wrong country, or the mapping may be too broad or too narrow for the disclosed locations.
Evidence to check Benchmark-to-country mapping table; rationale for each assignment; list of countries and any sub-national areas used; management review notes; version-controlled mapping file.
Where our review found employees below the wage threshold, we recorded the relevant countries and calculated the share of employees affected for each one.
Risk The affected-country list or percentages may be incomplete, based on the wrong denominator, or not traceable to source data.
Evidence to check Exception analysis by country; headcount denominator used for each percentage; payroll and HR data extracts; calculation checks; evidence of review of outliers and edge cases.
Based on the checks we completed before publication, we concluded that not every employee is paid at the level we regard as adequate.
Risk The statement may be unsupported if the underlying analysis is partial, if the population is misstated, or if the conclusion is not consistent with the evidence held.
Evidence to check Final assurance pack; reconciliation between payroll and reported population; sign-off memo; exception log; evidence of pre-publication review and approval; supporting schedules for the conclusion stated.
Evidence pack to prepare
Common reporting gaps
- The information is presented without a date or as-at point.
- The scope or boundary of the statement is left undefined.
- Key terms are used inconsistently across the report.
- Material changes since the previous period are not disclosed.
- Assertions are made without supporting detail or a source record.
- Boilerplate is used that does not actually answer what is asked.
Where drafts go wrong
Mistakes to avoid and where judgement is needed
The left column is what preparers get wrong while collecting; the right column is where you will have to make and explain a judgement.
Mistakes to avoid
- Wrong owner askedThe team goes to the wrong business owner, so the answer comes from someone who does not hold the payroll or local pay data.
- Framework terms used instead of local languagePeople ask for the information in ESRS-style wording, and the organisation cannot map that request to its own pay, HR or country reporting terms.
- Scope not pinned downThe data pull starts before the team has fixed which workforce groups, entities or countries are in scope, so the figures end up covering the wrong population.
- Wrong period basisThe team mixes a snapshot from one date with figures built over a different reporting window, so the numbers do not line up.
- Counting bases mixedHeadcount, full-time equivalent and payroll records are blended together, which makes the percentage below the threshold impossible to trust.
- Source labels lostThe original country names, benchmark names or file labels are stripped out during collection, so nobody can trace where each figure came from.
- Separate groups mergedEmployees who should be tracked separately by country or pay basis are rolled into one file, which hides differences that matter for the disclosure.
- Evidence trail incompleteThe team saves the numbers but not the supporting notes, extracts or approval record, so the source and sign-off cannot be checked later.
Judgement needed
- Choosing the pay yardstick where local practice differsPick one benchmark for each country on a consistent basis, explain why that measure best fits the local context, and keep the same approach unless a change is clearly justified and described.
- Handling countries with more than one plausible benchmarkIf several local reference points could be used, state which one you selected, why it was preferred over the alternatives, and whether the same choice was applied across all affected locations.
- Deciding who counts in the headcountSet out the employee population included in the calculation, explain any exclusions or borderline cases such as recent joiners, leavers, part-time staff or workers on leave, and keep the scope aligned with the way the figures were built.
- Treating business changes during the yearIf acquisitions, disposals or restructurings changed the workforce base, explain whether the figures reflect the opening group, the closing group or a blended view, and describe any restatement or carve-out used.
- Using estimates where payroll data is incompleteWhere exact pay data is not available for part of the workforce, say which figures were estimated, how the estimate was built, and how much of the result is based on measured versus approximated data.
- Setting the cut-off date for the calculationChoose a clear reporting date or period-end basis for the assessment, explain any timing differences between payroll records and the workforce snapshot, and apply the same cut-off consistently.
- Dealing with different pay definitions across countriesIf local rules or contracts define pay components differently, explain how you normalised the data so the comparison is like-for-like, and note any items included in one country but not another.
- Rounding and presentation of the percentage below thresholdState the rounding rule used for the share of employees below the benchmark, apply it consistently across countries and the group total, and make sure the rounded figure still matches the underlying calculation.
- Protecting privacy when the workforce is smallWhen a country or site has too few people for a safe breakdown, aggregate the data to avoid identifying individuals, explain the level at which you combined it, and note any resulting limits on detail.
Examples
How it reads on the page
Synthetic, written by LRA — not from a company report, not text from any standard.
We assessed whether our pay floor in each country meets the relevant living-wage benchmark, and the result is yes for this reporting period.
- We used the Anker reference as the comparison point.
- The countries where this check was relevant were Bangladesh, Vietnam, and Romania.
- Across those locations, 1,200 of 15,000 employees were paid below the benchmark, which is 8%.
This is a made-up example for training only. It shows how to describe the pay-floor check, the benchmark chosen, the countries in scope, and the share of employees below that level without naming any real organisation.
Our review found that our pay arrangements do not yet meet the chosen living-wage reference in every country covered by the assessment.
- We compared pay against the MIT living wage estimate.
- The countries included were Mexico, Poland, and South Africa.
- In those locations, 540 of 9,000 employees were below the benchmark, equal to 6%.
This is a fictional training example. It demonstrates a plain-language way to state the outcome of the wage check, identify the benchmark, list the affected countries, and report the proportion of workers below the threshold.
Quality ladder
- Basic
We paid adequate wages: yes.
- Better
We paid adequate wages in two countries, using the local living-wage benchmark, and 8% of employees were below that threshold.
- Best
We paid adequate wages across our operations in two countries during 2025, measured against the local living-wage benchmark, and 8% of employees were below it; the share fell from 12% last year because we raised pay in one site and completed a catch-up review in the other.
Check your understanding
Scenarios to work through
A group has payroll data for three countries. In one country, a local benchmark is used to test pay levels, and a small set of staff are still below that benchmark after allowances are counted.
A company operates in two countries and uses different local reference points to assess whether pay is at an acceptable level. One country clears the test, while the other does not, but the team is unsure whether to report only the shortfall country.
HR has a pay review showing that all employees in a single country are above the chosen wage benchmark. The team wonders whether the percentage field can be left blank because there are no workers below the line.
A preparer has two possible reference points for the same country: a statutory minimum and an internal living-cost estimate. The team used the internal estimate for the review, but a manager wants the lower statutory figure shown because it makes the result look better.
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Advice, not assurance
Framework references
Relevant ESRS requirements and related disclosures
ESRS
S1-9
within ESRS S1: Own Workforce
Guides that settle this question
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FAQ
Questions this page answers
Start with the plain-language explainer, then work through the step-by-step preparation section and the listed datapoints. The page also gives draft-output ideas, so you can turn the collected information into a narrative and a simple content-index line.
The page says to prepare four datapoints: an adequate wage flag, the wage benchmark basis, the affected countries, and the below-threshold share. Use those as the starting point for your data request and check that the figures are internally consistent.
Use the page’s preparation section to decide which workforce data are in scope and then test the scope against the datapoints listed on the page. The affected countries and below-threshold share help you see where the disclosure needs to be broken down.
The page is designed for ESG, HR and data owners, so ownership should sit with the team that can source the workforce data and explain the methodology. The assurance section and evidence pack are useful for agreeing who will provide support and who will sign off the draft.
The page includes an evidence pack with five items for assurance readiness, alongside five assurance claims to verify. Use both together so you can show the claim, the risk it addresses and the supporting evidence in one place.
The page lists common reporting gaps and mistakes, so it is meant to help you spot missing scope, weak methodology and unsupported figures before publication. A good check is whether each datapoint can be traced back to the evidence pack and the workbook.
The Download Centre includes a Prep & Assurance workbook in .xlsx format, which is intended to help you organise the preparation and assurance steps. Use it to capture the datapoints, evidence and review notes before turning them into a draft.
The Download Centre also includes a printable Library Card in .pdf format. It is a practical companion for keeping the key points, datapoints and assurance checks to hand while you prepare the disclosure.
Yes, but only as an illustrative starting point. The page says the example is synthetic, so use it to see how the data table and narrative might look, then replace it with your own figures and wording.
The draft-output section gives visualisation ideas, narrative starters and a content-index line to help you shape the final text. Use those prompts after you have checked the datapoints and evidence pack so the draft is consistent with the underlying data.
More questions this page can help with