Focus dell’informativa
In practical terms, the reporting should cover the organisation’s own employees as a whole, not just a few selected sites or senior roles. The emphasis is on the main remuneration principles, how they are applied across the business, and any important differences or features that affect different groups of workers.
Questo materiale didattico LRA supporta la preparazione dell’informativa. Per i requisiti esatti, fai sempre riferimento alla fonte ufficiale European Commission.
Prepara
Cosa raccogliere prima di redigere
Spunta ogni campo man mano che arrivano le evidenze. I responsabili sono i team che di solito custodiscono i file sorgente.
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Pay gap figure
Reward / HR analyticsCapture the reported percentage difference in pay between the relevant groups, using the organisation’s chosen basis and period consistently.
Evidenze Payroll extracts, pay-gap calculation workbook, and the underlying employee grouping logic used for the reporting period.
Attenzione a The percentage is calculated on a different pay basis or period than the payroll source, so the reported figure does not reconcile to the underlying pay data.
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Pay ratio figure
Reward / HR analyticsCapture the reported ratio comparing pay between the relevant pay levels or groups, using one consistent method and reporting period.
Evidenze Payroll data, ratio calculation file, and the definition used to select the two pay points or groups.
Attenzione a The ratio mixes different pay definitions or periods, so the numerator and denominator do not reconcile to the same source population.
Prima di iniziare
- Have you fixed which pay comparison you are using for the gap figure, and who sits inside each side of that comparison?
- Have you decided which pay ratio you will show, and which two pay amounts it compares?
- Are the figures taken from the same reporting period and pay basis across both measures?
- Can each number be traced back to a source record or payroll extract you can explain?
- Have you agreed the working definitions for pay, so the same items are counted on both sides?
Come prepararla
Richiedi i dati
Request the pay gap and pay ratio data from Reward / Pay Analytics
Traduci l’informativa in una domanda di business interna, poi adattala al linguaggio della tua organizzazione.
What pay gap and pay ratio figures should we use for the reporting period, and what source data and method sit behind them?
Use your organisation’s own pay and reward language first, then map it to the reporting disclosure. For example, ask for your pay gap and pay ratio outputs, the underlying pay files, and the method used to calculate them. Keep the request in the terms your team already uses, and check the source material before sign-off.
Richiesta debole
Please provide the ESRS S1:S1-15 remuneration data and evidence for the disclosure.
Perché non funziona: This uses framework language that many internal owners will not recognise, and it does not say which figures, source files, or calculation details are needed. It is too vague to help the owner pull the right data quickly or to let the reviewer trace the numbers back to the source.
Richiesta migliore
Please send the latest pay gap and pay ratio outputs for [period], together with the source export, calculation basis, scope, and any notes on adjustments or assumptions. Use your team’s usual pay and reward terms, and confirm which version is approved for reporting.
Modello di e-mail formale
Subject: Request for pay gap and pay ratio data for [reporting period] Hello [name/team], We are preparing the sustainability reporting pack and need your help with the pay gap and pay ratio figures for [reporting period]. Please send: - the final figures you would use for [reporting period] - the source file(s) or export(s) used to produce them - the calculation basis and any assumptions or adjustments - the population and boundary included - the internal category labels used in the analysis - any notes needed to explain the output clearly If there are multiple versions, please confirm which one is the latest approved version and who reviewed it. Please share the material by [date]. If anything is unclear, I’m happy to adapt this to your team’s usual terms. Thanks, [Your name]
Versione breve per Teams / Slack
Hi [name] — could you send the latest pay gap and pay ratio figures for [period], plus the source file and any notes on how they were calculated? Please include the boundary, population, and the internal labels used. Thanks.
Esempi di settore
Manufacturing
Contesto. A plant-based group with hourly and salaried staff, multiple sites, and a central reward team.
Richiesta adattata. Hi [name] — for [period], could you share the pay gap and pay ratio figures for the group, plus the payroll export, the calculation basis, and any site or worker-group exclusions? Please include the internal labels you use for hourly, salaried, and bonus-eligible staff.
Esempio di risposta. Attached: 1) approved pay gap workbook, 2) payroll extract from [system], 3) notes showing the group boundary, included staff, and calculation basis, 4) version history and reviewer sign-off.
Financial services
Contesto. A regulated business with multiple legal entities and a central compensation team.
Richiesta adattata. Hello [name/team], please provide the latest pay gap and pay ratio pack for [period] across the entities in scope, including the compensation file, the method used, and any entity-level notes. Please use the internal grade and population labels your team already works with.
Esempio di risposta. Returned: entity list in scope, compensation analysis workbook, source HR/pay export, methodology note, and confirmation of the approved version for reporting.
Redigi la tua informativa
Note che trasformano i dati in un’informativa
Modelli formativi LRA: adattali alla tua organizzazione e verifica la fonte ufficiale prima dell’approvazione.
Nota metodologica
State how the two figures were calculated, including the pay basis used, the employee population included, and any exclusions or adjustments applied before the numbers were finalised.
Nota di contesto
Explain what the percentage gap and the pay multiple indicate about the relationship between higher- and lower-paid workers, and note whether the figures point to a wider or narrower spread in pay.
Dichiarazione sulle variazioni
If either figure has changed materially, link the movement to the underlying workforce or pay-setting factors that drove it, such as changes in headcount mix, pay awards, or the composition of the group included in the calculation.
Voce dell’indice dei contenuti
S1-15 Remuneration — [location / page] / [notes]Centro download
Strumenti e moduli per la preparazione
Scarica gli strumenti di preparazione per S1-15 per 24 ore con accesso gratuito tramite email verificata. I link ai rapporti originali restano pubblici.
Verifica
Per ogni affermazione, verifica le evidenze
We prepared the coverage figure using our own payroll and HR records, then checked that the population included the relevant staff group for the reporting period and that any exclusions were deliberate and documented.
Rischio Assurer will probe whether the headcount basis was complete, whether anyone was left out without a clear reason, and whether the period and population used for the calculation were consistent with the published figure.
Evidenze da verificare ['Payroll extract and HR master data used for the calculation', 'Population reconciliation showing included and excluded employees', 'Documented scope note explaining any exclusions or boundary choices', 'Version-controlled calculation file with period-end cut-off']
For the pay-gap figure, we used gross hourly pay data for men and women and built the calculation from the ordinary salary element plus other pay items available across the workforce, with the method set out in our working papers.
Rischio Assurer will test whether the pay inputs were defined consistently, whether the same pay components were used across the dataset, and whether the method was applied in a way that could distort the result.
Evidenze da verificare ['Calculation methodology note', 'Source payroll data showing gross hourly pay inputs', 'List of pay components included in the model', 'Sample recalculation or spreadsheet audit trail']
We disclosed the gap figure together with the contextual split by employee group and/or country where that helped explain the result, and we kept the underlying breakdowns that support the published numbers.
Rischio Assurer will check whether the contextual breakdowns match the reported figure, whether the grouping logic was applied consistently, and whether the supporting detail can be traced back to source data.
Evidenze da verificare ['Segmented calculation outputs by employee group and/or country', 'Source data mapping to each segment', 'Narrative explaining why the contextual split was used', 'Reconciliation from segment totals to the published figure']
We calculated the annual pay ratio using the full employee population in scope, the base salary element, and the cash, benefits-in-kind and long-term incentive items covered by our pay policy, then checked the result against the source records before sign-off.
Rischio Assurer will probe whether the pay elements were selected correctly, whether the employee population was complete, and whether the ratio was recalculated accurately from the underlying records.
Evidenze da verificare ['Remuneration policy extracts showing included pay elements', 'Employee population listing used in the ratio', 'Source payroll and reward data for each component', 'Independent recalculation or review sign-off']
We published the ratio between the top earner and the middle employee after confirming the ranking method, the treatment of the top earner, and the exclusion of that individual from the median population.
Rischio Assurer will test whether the ranking and median approach were applied correctly, whether the highest-paid person was handled consistently, and whether the disclosed ratio can be reproduced from the source data.
Evidenze da verificare ['Ranking and median calculation worksheet', 'Employee pay dataset used for the ratio', 'Explanation of how the top earner was identified and excluded from the median set', 'Reperformance check or internal review evidence']
Before publication, we documented the approach used to compile both pay metrics, including the data sources, the calculation steps, and the main judgement calls made in the process.
Rischio Assurer will probe whether the methodology was sufficiently clear to reproduce the figures, whether key assumptions were disclosed, and whether the process was applied consistently across both metrics.
Evidenze da verificare ['Methodology paper covering both metrics', 'Data lineage from source systems to final disclosure', 'List of assumptions, judgements and exclusions', 'Approval record showing review before publication']
Pacchetto di evidenze da preparare
Lacune ricorrenti nella rendicontazione
- 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.
Dove le bozze sbagliano
Errori da evitare e dove serve una valutazione
La colonna sinistra mostra gli errori di chi raccoglie i dati; la destra, dove dovrete prendere e spiegare una valutazione.
Errori da evitare
- Wrong ownerThe team asks the wrong pay or HR contact, so the figures come from someone who does not hold the source records.
- Framework language firstPeople ask for the data using disclosure jargon instead of the organisation’s own payroll terms, which slows down the handover and creates confusion.
- Scope not pinned downThe request does not state which worker groups, entities, or locations are in scope, so different teams pull different populations.
- Wrong period basisThe data is gathered for the wrong reporting window or cut-off date, so the numbers do not match the period being reported.
- Mixed counting methodOne team uses headcount while another uses full-time equivalent or another basis, so the pay gap and pay ratio are built from unlike measures.
- Source labels lostThe original payroll or HR file names and field labels are stripped out during collection, making it hard to trace each figure back to its source.
- Separate groups mergedPeople combine groups that should stay apart, such as different worker categories or pay populations, and the result no longer reflects the underlying records.
- Evidence trail missingThe pack is assembled without the supporting file details, version history, or sign-off record, so no one can show how the numbers were checked.
Serve una valutazione
- Choose one pay-gap basis and keep it consistentDecide whether the gap is built from base pay, total cash, or another internal pay measure, then explain the basis used and keep it stable unless you clearly explain a change.
- Set the comparison group at the same point in timeUse one clear cut-off date for the workforce and the comparator group, and disclose that date so readers can see who was in scope for the calculation.
- Handle joiners, leavers, and people with partial-year service consistentlyState whether people who were hired, left, or worked only part of the year are included, excluded, or time-adjusted, and apply the same rule across the calculation.
- Define the worker population where local labels differIf job titles or employment categories vary by country, map them to one internal grouping rule and explain the mapping so similar roles are treated the same way.
- Decide how to treat acquisitions and disposals in the reporting boundaryExplain whether newly acquired or sold entities are included from the transaction date or from the full reporting period, and note any boundary change that affects comparability.
- Choose between actual payroll data and estimates where records are incompleteIf some pay elements are missing, say which figures are measured and which are estimated, describe the method used, and flag the parts of the result that are less precise.
- Round in a way that does not distort the resultUse one rounding rule for the percentages and the ratio, apply it consistently, and make sure the rounded figures still reflect the underlying calculation.
- Protect personal data by grouping small populationsWhere the workforce slice is too small to show safely, aggregate it into a broader group, explain the privacy-driven suppression or grouping approach, and keep the method consistent.
Esempi
Come si legge nella pagina
Sintetici, scritti da LRA: non provengono dal report di un’azienda né dal testo di uno standard.
we show a simple pay comparison for our workforce, split by women and men, using average pay and a like-for-like pay comparison. The figures below are illustrative and internally consistent.
Illustrative pay comparison for our workforce (people / %)
| Category | Women | Men |
|---|---|---|
| Average pay | 48 | 52 |
| Headcount | 240 | 260 |
Illustrative disclosure showing a workforce pay gap percentage and a pay comparison ratio for a manufacturing reporter.
we present a second, different workforce pay comparison for our group, again split by women and men. The numbers are illustrative and internally consistent.
Illustrative pay comparison for our group (people / %)
| Category | Women | Men |
|---|---|---|
| Average pay | 57 | 43 |
| Headcount | 180 | 120 |
Illustrative disclosure showing a workforce pay gap percentage and a pay comparison ratio for a financial services reporter.
Scala di qualità
- Base
Our median pay gap is 12% and our pay ratio is 18:1.
- Migliore
Our median pay gap is 12% and our pay ratio is 18:1, based on this year’s pay data for our workforce and the chief executive.
- Ottimo
Our median pay gap is 12% and our pay ratio is 18:1 for this reporting year, using the same pay basis across our workforce and chief executive, and the gap narrowed because bonus payments were lower at the top end.
Verifica la tua comprensione
Scenari da affrontare
A preparer has the latest payroll extract for the year-end workforce and a separate file for the chief executive’s total pay. The team can calculate the gap between average worker pay and the leader’s pay, but they have not yet checked whether the same basis is used for both figures.
A company has a large bonus accrual for senior staff, while most other employees receive only fixed salary and a small allowance. The preparer is unsure whether to compare total pay or only base salary when preparing the remuneration disclosure.
The finance team has calculated a pay ratio of 18:1 using the chief executive’s annual pay and the median employee’s annual pay. A reviewer asks whether the ratio alone is enough, or whether the underlying pay-gap information also needs to be prepared.
A group prepares its sustainability report centrally, but payroll data sit in several country systems. One subsidiary has not yet confirmed its year-end figures, and the group team is considering using an estimate so the report can be issued on time.
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Controlla il tuo testo
Incolla uno o due paragrafi. Il frammento viene usato solo per questa verifica e non viene salvato nella conversazione.
Il confronto usa gli esempi di questa scheda, non la loro prevalenza nel corpus dei report.
Indicazione, non assurance
Riferimenti al framework
Requisiti ESRS pertinenti e informative correlate
ESRS
S1-15
all’interno di ESRS S1: Own Workforce
Guides that settle this question
Correlati ed esplora
Altro in ESRS S1 →Sfoglia il catalogo completo →Cerca in tutte le informative →
FAQ
Domande a cui risponde questa pagina
The page says the two datapoints to prepare are the pay gap figure and the pay ratio figure. Use the plain-language explainer and the step-by-step preparation section to confirm what you need before drafting the disclosure.
Use it as a practical checklist to move from understanding the disclosure to gathering the right inputs and shaping a draft. The page is designed to help you prepare the disclosure rather than to act as an official source.
The page includes an evidence pack with five items to support assurance readiness. Use those items alongside the six assurance claims to verify so you can show how the figures were built and checked.
The page lists six assurance claims in a claim/risk/evidence format. Use them to test whether your data, method and supporting documents are strong enough for review before you finalise the disclosure.
The page includes a list of common reporting gaps and mistakes to help you avoid weak or incomplete reporting. Use that section as a pre-submission check against your draft, data and evidence pack.
They are there to show what a draft disclosure can look like, including a quantitative table. Treat them as examples only and use them to shape your own wording, layout and data presentation.
The Download Centre includes a Prep & Assurance workbook in .xlsx format. Use it while preparing the disclosure and building your assurance evidence so you can track inputs, checks and draft outputs in one place.
The Download Centre includes a printable Library Card in PDF format. It is a practical companion for working through the page content and keeping the key preparation and assurance points to hand.
The page has a draft-output section with visualisation ideas, narrative starters and a content-index line. Use those elements to turn your prepared figures and evidence into a clear first draft.
Yes. The page includes a table linking to real published reports at the pages where the topic is disclosed, which can help you see how others present similar information in practice.
Altre domande in cui questa pagina può aiutare