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ESRS S1: Own Workforce·Disclosure Requirement S1-12
Training
Guide pratique pour préparer cette information. Utilisez cette fiche pour identifier les données à préparer, vérifier les affirmations et organiser les preuves. Pour les exigences exactes, reportez-vous toujours à la source officielle European Commission.
Passeport publié
Révision en attente
···
En cours de révision
Révision éditoriale en cours
Élaboré à partir des sources officielles et de preuves issues de rapports publiés. Aucun approbateur n’est encore enregistré : cette page ne porte donc pas de signature.
Utilisez-la avec la source officielle European Commission tant que cette révision est en cours.
Norme
ESRS S1: Own Workforce
Disclosure Requirement S1-12 · 2026-5010-final
Dernière révision
—
Support pédagogique LRA · Non publié ni approuvé par European Commission
Pour préparer cette information
Objet de l’information
This disclosure asks an organisation to explain how it supports the training and development of its own workforce. In practice, the report should show what learning opportunities are available, who can access them, and whether they are designed to help people do their jobs safely and effectively, build skills, and progress in their roles.
The practical focus is on coverage and consistency across the workforce, not just a few showcase programmes. A useful report should make clear whether training is available across different sites, functions and worker groups, how participation is managed, and whether there are gaps between what is offered and what people actually receive.
Ce support pédagogique LRA aide à préparer l’information. Pour les exigences exactes, reportez-vous toujours à la source officielle European Commission.
Avant de commencer
Avant de commencer
Une courte liste de contrôle avant de préparer cette information — cochez chaque point une fois réglé.
Préparation
Informations clés à préparer
| Champ à préparer | Ce qu’il faut recueillir | Indice de preuve | Responsable |
|---|---|---|---|
| Employee review coverage | The share of employees included in the review, with the numerator and denominator clearly defined and the period covered. | HR or performance review records, review completion reports, and the calculation file used to derive the percentage. | HR / People team |
| Training hours total | The full number of training hours delivered in the reporting period, using one consistent basis for all sessions and participants. | Learning management system exports, attendance logs, course records, and the roll-up calculation supporting the total. | Learning and Development |
| Average training per employee | The average training hours per employee, together with the employee count used in the calculation and the period covered. | The total training-hours calculation, the employee population file, and the working paper showing how the average was derived. | Learning and Development / HR |
＋ Afficher les sous-éléments de S1-12 (liste de travail LRA)
Record the share of staff who were reviewed.
Calculate the average for each staff member.
State the overall number of training hours delivered.
Comment le préparer
Set the reporting boundary first: decide which employees are included in this disclosure and keep that scope consistent across the figures and narrative.
Agree the definitions you will use for the three required items: the share of employees covered by the review, the total learning time recorded, and the average learning time per employee.
Gather the underlying records that support each item, such as the employee review list and the training logs needed to calculate the totals and the average.
Calculate and assemble the reported outputs from the source records, making sure the percentage, the total hours, and the per-employee average all tie back to the same scope.
Record any exclusions, adjustments, or changes in method so a reviewer can see why the reported population or numbers differ from earlier periods or internal working papers.
Check the final disclosure against the official source to confirm you have covered every required item and have not missed any supporting detail or changed the intended meaning.
Demander les données
Request the training review data from People Analytics
Traduisez l’information en une question métier interne, puis adaptez-la au vocabulaire de votre organisation.
How many people were reviewed for training, and what training time was recorded for the reporting period?
Please use your organisation’s own terms first (for example, learning review, development check-in, skills review, course time, learning hours), then map them to the disclosure fields. Keep the wording in your internal language and check the official source before sign-off.
Demande faible
Please provide the ESRS S1:S1-12 training metrics for the year, including the percentage of employees reviewed, total training hours, and average hours per employee.
Pourquoi elle échoue : This uses framework language that many operational teams will not use day to day, and it does not tell the owner what source, boundary, counting basis, or internal labels to use. It also leaves room for inconsistent interpretation of who is included and how time is measured.
Meilleure demande
Please send the learning review extract for [period] for [boundary]. We need the count of employees who had a learning or development review, the total learning time recorded, and the average time per employee, using your team’s own labels. Please include the source system, population covered, counting basis, time basis, and any exclusions or duplicates.
Modèle d’e-mail formel
Subject: Request for training review and learning time data for [reporting period] Dear [name/team], Could you please provide the data needed for our sustainability reporting on employee learning for [reporting period]? We need, for the agreed reporting boundary ([boundary]), the following in your own internal terms and source extracts where available: - the number of employees who had a training or learning review during the period; - the total learning or training time recorded for those employees; and - the average learning or training time per employee. Please also include: - the system or file used; - the population covered; - the counting method used for people reviewed; - the basis used for time recorded; - any exclusions, duplicates, or missing records; and - the name of the person who prepared the extract. If helpful, please send this in a simple table. Adapt this to your organisation’s own language, and check the official source before sign-off. Many thanks, [Your name]
Version courte pour Teams / Slack
Hi [name], could you send the training / learning data for [period] for [boundary]? We need: people reviewed, total learning hours/time, and average per employee, plus the source system and any notes on exclusions or duplicates. Please use your team’s own terms in the extract. Thanks.
Exemples sectoriels
Manufacturing
Contexte. A plant uses shift-based toolbox talks, mandatory safety refreshers, and role-specific machine training recorded in a local learning log.
Demande adaptée. Please share the training log for [period] for the plant and support teams. We need the number of employees who had a learning review, total recorded training time, and average time per employee. Please use your site terms, and include the log source, shift coverage, and any sessions that were cancelled or repeated.
Exemple de réponse. The site learning log shows 428 employees reviewed, 1,964 total training hours, and 4.6 hours per employee. Source: site learning tracker. Coverage: plant and maintenance teams. Two cancelled sessions were excluded; duplicate entries were removed.
Professional services
Contexte. A firm tracks mandatory compliance modules, client-skills workshops, and coaching sessions in a central learning platform.
Demande adaptée. Please provide the learning platform extract for [period] across the firm. We need the number of staff who completed a learning review, total learning time, and average time per person. Please include the platform name, business units covered, your completion rules, and any manual adjustments.
Exemple de réponse. The platform extract shows 1,250 staff reviewed, 7,500 total learning hours, and 6.0 hours per person. Source: central learning platform. Coverage: all UK entities. Completion counted once per person per module; one duplicate enrolment was removed.
Rédigez votre information
Des notes qui transforment les données en information publiée
Modèles pédagogiques LRA — adaptez-les à votre organisation et vérifiez la source officielle avant validation.
Note méthodologique
State how you defined the employee population, how you counted those included in the review process, and how you calculated total learning time and the per-person average.
Note de contexte
Explain what the review coverage percentage and training figures indicate about how widely employees were assessed and how much development time was recorded overall and per person.
Déclaration sur les variations
If the figures move materially, note whether the change reflects a wider or narrower review reach, more or fewer training hours, or a shift in the average time per employee.
Entrée de l’index de contenu
S1-12 Training — [location / page] / [notes]Centre de téléchargement
Outils et formulaires de préparation
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Préparation à l’assurance
Pour chaque affirmation, vérifiez les preuves
| Affirmation | Risque | Preuves à vérifier |
|---|---|---|
| We calculated the coverage figure from the training activity we could evidence for the period, using our own employee count as the denominator and the recorded training time as the numerator. | The assurer may test whether the calculation basis is consistent, whether the employee population used is the right one for the period, and whether any training time was omitted, double-counted, or included without support. | Calculation workbook; source training records; employee headcount extract for the reporting period; methodology note showing the numerator and denominator used; reconciliation from raw records to the published figure. |
| We limited the figure to the workforce group we intended to report on and applied the same scope rule throughout the dataset, so the published percentage reflects one consistent population. | The assurer may probe whether the scope was set before calculation, whether exclusions or inclusions were applied consistently, and whether the reported population matches the underlying records. | Scope memo; population definition used for the metric; HR extract showing included and excluded employees; audit trail of any adjustments; sign-off confirming the scope applied before publication. |
| We relied on source records from the reporting period and checked the underlying data for obvious gaps, duplicates, and mismatches before finalising the number. | The assurer may question data completeness, accuracy, and whether the figure was built from reliable source data rather than estimates or partial records. | Training attendance logs; learning system export; performance review tracker; data quality checks; exception log; evidence of follow-up on missing or inconsistent entries. |
| We kept evidence that links the published figure back to the original records, so the calculation can be traced from the final number to the source files. | The assurer may test whether the audit trail is complete enough to support the reported figure and whether the evidence retained is contemporaneous and traceable. | Version-controlled calculation file; source system extracts; supporting documents for any manual entries; change log; approval trail; retention of the files used in the final calculation. |
| Before publication, we reviewed the result for reasonableness against prior periods and internal expectations, and we resolved any unusual movements or data issues we found. | The assurer may probe whether pre-publication checks were substantive, whether anomalies were investigated, and whether the final disclosure could be misleading because of unresolved issues. | Reasonableness review notes; prior-period comparison; variance analysis; issue resolution records; management review or approval evidence; final sign-off confirming no outstanding data concerns. |
Dossier de preuves à préparer
Lacunes fréquentes dans les rapports
Figures are stated without the supporting narrative, or narrative without figures.
Scope is inconsistent between the text and the numbers.
The reporting boundary is left undefined.
Material changes since the previous period are not disclosed.
Estimates and measured values are not distinguished.
Source records for the figures are not identified.
Lacunes fréquentes
Erreurs à éviter lors de la collecte des données
Wrong ownerChasing the learning team alone can miss the people who hold headcount, payroll, or local training records, so the figures come from the wrong source.
Framework language, not business languageAsking for the data using disclosure labels instead of the organisation’s own terms can leave teams unsure which course lists, HR fields, or finance reports to pull.
No clear boundaryIf you do not define which entities, countries, and worker groups are in scope, different teams may count different populations and the totals will not match.
Wrong period basisPulling training activity from a different date range than the reporting year can mix current-year and prior-year records and distort the result.
Mixed counting methodCombining headcount, course completions, and attendance records without one agreed basis can make the percentage reviewed and the hours total inconsistent.
Source labels lostCopying numbers into a summary sheet without keeping the original file names, report titles, or extract dates makes it hard to trace where each figure came from.
Populations mergedPutting mandatory and optional learning, or different employee groups, into one bucket can hide the separate patterns needed for the disclosure.
Missing evidence trailIf the extract date, version, and reviewer sign-off are not kept with the data, no one can show how the final figures were checked before use.
Là où un jugement professionnel est souvent nécessaire
Choose the employee population before calculating the review rateSet out which people sit in the training population for the year, explain any exclusions or inclusions at the margins, and keep the same basis when you compare periods unless a change is clearly described.
Decide how to handle business bought or sold during the yearState whether people who joined or left through acquisitions, disposals or similar changes are counted only for the time they were in the group, and explain any restatement or non-restatement of earlier figures.
Use one practical rule where local job categories do not matchIf country-level role labels or worker groupings differ, map them to a single internal approach for reporting and disclose the rule used so readers can see how the numbers were made comparable.
Be clear on who counts when someone sits near the boundaryExplain how you treat agency workers, contractors, secondees, interns or other near-boundary groups, and disclose any judgement used to include or exclude them from the training population.
State the timing basis for both headcount and training activityMake clear whether the figures reflect an opening point, closing point, or average over the period, and describe how you aligned the people count with the training hours recorded.
Separate measured records from estimates and explain the methodWhere attendance or hours are not fully captured, say which figures come from system records and which are estimated, and describe the basis used to fill gaps or convert partial records into totals.
Explain how you calculate the average per personShow whether the average is based on all people in scope, only those who received training, or another internal denominator, and keep the approach consistent or explain any change.
Round in a way that does not distort the totalsDisclose the rounding rule used for the percentage, the total hours and the average, and make sure the rounded figures still reconcile sensibly to the underlying data.
Aggregate enough to protect personal dataIf small groups could identify individuals, combine categories or suppress detail as needed, and explain the level of aggregation used so the training figures remain usable without exposing personal information.
Exemples
Exemples illustratifs
Synthétiques, rédigés par LRA — ils ne proviennent ni d’un rapport d’entreprise ni du texte d’une norme.
Illustrative (synthetic) example — manufacturing
We reviewed 78% of our workforce during the year, covering 390 of 500 employees. Those reviews took 1,560 training hours in total, which is an average of 3.2 hours per employee reviewed.
Synthetic illustration only. This shows how to present the share of employees reviewed, the total time spent, and the average time per reviewed employee in a single quantitative disclosure.
Illustrative breakdown of employee review activity (people)
| Category | Reviewed employees | Not reviewed |
|---|---|---|
| Headcount | 390 | 110 |
Illustrative (synthetic) example — consumer goods
We covered 62% of our staff in the period, equal to 248 of 400 employees. The related learning time came to 744 hours overall, or 3.0 hours for each employee included in the review.
Synthetic illustration only. This example combines the proportion of staff covered, the total hours delivered, and the average hours per person covered.
Illustrative breakdown of employee review activity (people)
| Category | Reviewed employees | Not reviewed |
|---|---|---|
| Headcount | 248 | 152 |
Rapports d’entreprises
Comment les entreprises publient S1-12 en pratique
Exemples de pratiques de publication complètes et partielles. Ce sont des analyses fondées sur des preuves, non des modèles à recopier.
Acciona, S.A.
Electric Utilities / IPP / Energy Traders · Spain · 2025
Acciona’s 2025 Sustainability Report provides data on employee participation in performance and professional development appraisals, reporting rates of 97% for women and 94% for men, alongside average training hours of 16.9 for women and 25.2 for men (p.231). The report also mentions consolidated training hours in occupational risk prevention, with 519,279 hours in 2025 (p.247), and references ongoing internal training programmes for recruiters (p.213). However, the report does not clearly disclose a specific numeric value for the overall training or appraisal metrics beyond these segmented figures, and some related narrative items remain unclear or not fully detailed (p.231).
Aena S.M.E., S.A.
Air Transportation — Airport Services · Spain · 2025
Aena S.M.E., S.A.'s 2025 sustainability report provides detailed numeric data on employee training, including total training hours by professional category (p.311) and investment in employee training and development programmes by country, with figures for Spain, the United Kingdom, and Brazil (p.304). The report also includes data on employee training related to occupational health and safety across these countries (p.306). However, there is no quotable narrative evidence found in the report to provide context or explanation for these figures.
GEA Group Aktiengesellschaft
Electrical Equipment and Machinery · Germany · 2025
GEA Group Aktiengesellschaft’s 2025 Annual Report provides a numeric value for the total workforce as of December, reporting 19,531 employees on page 155. The report also includes data on average training hours per employee, with figures such as 10.3 hours for males and 9.6 hours for females detailed on page 168. However, no clear narrative explanation or additional qualitative information related to the disclosure was found in the report.
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Scénarios à travailler
A group of 240 staff completed a learning programme during the year, but the HR report only shows the total course hours and does not say how many people were included in the review. The team also has a separate spreadsheet for managers and another for the rest of the workforce.
QHow should you decide whether the headcount figure is ready for disclosure, and what should you do if the split records do not cover everyone in the same way?
Afficher la réponse type →Masquer la réponse ↑
Use one clear figure for the share of employees whose training was reviewed, based on the same population used for the other training figures. If the separate spreadsheets overlap, leave gaps, or exclude part of the workforce, reconcile them first so the percentage reflects the full set you are reporting on, then check the source data before sign-off.
Pourquoi c’est important · Keep the population consistent across the training metrics so the percentage is meaningful and traceable.
A company recorded 1,860 training hours for the year across 310 employees. The draft note shows the total hours, but the average per employee has not been calculated, and one business unit wants to exclude induction sessions because they were short.
QShould the average be based on all recorded training time, and how do you handle the calculation if some sessions are not part of the training total?
Afficher la réponse type →Masquer la réponse ↑
Calculate the average from the same training hours that you include in the total, then divide by the employee count used for the disclosure. If a session is excluded from the total, it should also stay out of the average; do not mix different scopes. Check the working and the source records before sign-off.
Pourquoi c’est important · The average must be derived from the same training scope as the total, otherwise the figures will not align.
A preparer has a report showing 420 staff reviewed for learning needs out of 500 employees, with 2,100 total hours and an average of 5.0 hours per employee. A later payroll update shows that 12 people joined mid-year and were included in the hours, but the review count was not updated.
QDo you keep the draft as it is, or do you revisit the figures before finalising the disclosure?
Afficher la réponse type →Masquer la réponse ↑
Revisit the numbers. If the workforce count changed and those people were part of the training hours, the review percentage and the average need to be checked against the same final population. Update the calculations so the three data points tell one consistent story, then verify the source files before sign-off.
Pourquoi c’est important · When the workforce changes, all training measures should be recalculated against the same final basis.
A business unit can show course attendance logs for 180 employees and a separate learning-platform export with 900 hours. However, the logs do not identify whether the same people appear in both records, and the average per employee has been estimated by dividing hours by the full headcount of 260 without checking.
QCan you rely on the estimate, or do you need more evidence before you publish the training figures?
Afficher la réponse type →Masquer la réponse ↑
You need more evidence. The attendance logs and platform export must be tied together well enough to support the percentage reviewed, the total hours, and the average per employee on the same basis. If the records do not show that link, rebuild the calculation from traceable source data and check the official source before sign-off.
Pourquoi c’est important · Do not publish training metrics from disconnected records; the evidence must support one coherent calculation basis.
Références au référentiel
Exigences ESRS applicables et informations connexes
Références disponibles du référentiel et informations voisines utiles à la préparation de cette exigence.
ESRS
S1-12
au sein de ESRS S1 : Own Workforce
Connexes et exploration
Policies (Own Workforce) → FicheSocial Protection → FicheDisabilities → FicheHealth & Safety → FicheWork-life Balance → Fiche
Parcourir toutes les informations →
Plus dans ESRS S1 → Parcourir le catalogue complet → Accueil de la Bibliothèque des informations → Rechercher dans toutes les informations →
FAQ
Questions auxquelles cette page répond
For S1-12 ESRS Own Workforce, what data do I need to prepare before drafting the disclosure?+−
The page says to prepare three datapoints: employee review coverage, total training hours, and average training per employee. Use those as the starting data set before you draft the narrative.
How do I use the S1-12 step-by-step preparation section in practice?+−
Use it as a working checklist to move from raw data to a draft disclosure. The page is designed to help you set up the scope, gather the datapoints, and then turn them into report-ready wording.
What should I include in the S1-12 evidence pack for assurance readiness?+−
The page includes an evidence pack with five items to support assurance readiness. Build your pack around those items so you can show where the numbers came from and how they were checked.
What are the five assurance claims I need to verify for S1-12?+−
The page says there are five assurance claims to verify, each with a claim, risk and evidence angle. Use that section to test whether your data, calculations and narrative are supported before sign-off.
What are the common reporting gaps or mistakes for S1-12 Own Workforce?+−
The page lists common reporting gaps and mistakes to watch for. Use that list as a pre-submission check so you can spot missing data, weak evidence or inconsistent calculations early.
How do I use the S1-12 workbook download to prepare the disclosure?+−
The Download Centre includes a Prep & Assurance workbook in .xlsx format. Use it to organise the datapoints, track evidence and work through the preparation and assurance checks in one place.
What is the printable S1-12 Library Card PDF for?+−
The printable Library Card is a quick-reference version of the page. It is useful if you want a compact checklist while you are collecting data, reviewing evidence or drafting the disclosure.
How should I turn the S1-12 data into a draft narrative?+−
The page has a draft-output section with visualisation ideas, narrative starters and a content-index line. Use those prompts to convert the datapoints into a short, consistent draft rather than starting from a blank page.
Does the S1-12 page give an example disclosure I can copy structure from?+−
Yes, it includes synthetic illustrative example disclosures, including a quantitative table. Treat them as examples of presentation only and make sure your own figures and wording match your actual data.
Where can I find real company report examples for S1-12 Own Workforce?+−
The page has a 'From company reports' table that links to published reports where the topic is disclosed. Use it to see how others present the topic, but keep your own drafting based on your organisation’s data and evidence.
Autres questions auxquelles cette page peut aider
S1-12 ESRS Own Workforce: what are the minimum datapoints to collect before I start drafting?How do I set ownership for S1-12 Own Workforce data between HR, ESG and finance?What evidence should I keep to support S1-12 employee review coverage and training metrics?How do I check whether my S1-12 training hours and average training per employee are internally consistent?What should I look for in the S1-12 common mistakes section before submission?How do I use the S1-12 narrative starters to write a first draft quickly?What is included in the S1-12 Prep & Assurance workbook download?Can I use the S1-12 illustrative example table as a template for my own disclosure?How do I build an assurance-ready evidence pack for S1-12 Own Workforce?Where does the S1-12 page point me for real published report examples?How do I avoid overclaiming in the S1-12 draft output section?What is the best way to use the S1-12 content-index line in a report draft?
Aller plus loin · S1-12
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Comment cette bibliothèque est construite
312 rapports publiés indexés
63 171 pages avec citations au niveau de la page
272 fiches disclosure conçues par des praticiens
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