GRI 404: Training and Education·Disclosure GRI 404-1
Average hours of training per year per employee
Guía práctica para preparar esta divulgación. Use esta ficha para identificar la información a preparar, verificar afirmaciones y organizar la evidencia de soporte. Para los requisitos exactos, consulte siempre la fuente oficial de GRI.
Pasaporte publicado
Revisión pendienteNorma
GRI 404: Training and Education
Disclosure GRI 404-1 · 2016
Última revisión
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Material formativo de LRA · No emitido ni avalado por GRI
Foco de la divulgación
This disclosure asks an organisation to report the average amount of training each employee receives over a year. In practice, it is about showing how much learning and development time is being provided, rather than listing every course or training event. The figure should be presented in a way that lets readers understand the overall level of training support across the workforce.
The practical focus is on how broadly training is covered across the organisation. A useful question is whether the average reflects all employees and all relevant parts of the business, or only selected sites, functions, or programmes. The reporting should make clear the scope used so readers can judge whether the number represents training across operations or only a more limited set of activities.
Este material formativo de LRA apoya la preparación de la divulgación. Para los requisitos exactos, consulte siempre la fuente oficial de GRI.
Antes de empezar
Antes de empezar
Una breve lista de comprobación antes de preparar esta divulgación: marque cada punto a medida que lo resuelva.
Preparación
Información clave que preparar
| Campo de preparación | Qué recopilar | Pista de evidencia | Responsable |
|---|---|---|---|
| Gender split | Capture the gender categories used for the workforce disclosure, using the same definitions and labels as the underlying people data. | HRIS workforce extract, diversity reporting definitions, and any self-identification guidance used to classify staff. | HR / People Analytics |
| Worker category | Capture the employee groupings used for reporting, with each person assigned to the correct workforce category under the organisation’s own classification rules. | HRIS employee master data, workforce segmentation rules, and payroll or contract records used to assign categories. | HR / People Operations |
| Training hours average | Capture the average number of training hours completed by employees during the reporting period, based on the same employee set and time window used in the training records. | Learning management system reports, training attendance logs, and the calculation workbook showing the average and the employee count used. | L&D / HR Analytics |
Cómo prepararlo
Solicitar los datos
Request the training-hours data from People Analytics
Traduzca la divulgación a una pregunta de negocio interna y adáptela después al lenguaje propio de su organización.
What training time did each employee group record during the reporting period, split by gender and employee category?
Use your organisation’s own labels first, then map them to the reporting categories. For example, if you use job family, grade, population, or workforce segment internally, ask for those terms and translate them later into the disclosure wording. Keep the request in the language the data owner already uses.
Solicitud débil
Please provide the GRI 404-1 data showing the evidence needed for GRI 404:GRI 404-1, split by gender and employee category.
Por qué falla: It uses framework language rather than the organisation’s own terms, and it does not tell the owner which system, population, grouping labels, or calculation basis to use. That makes the response harder to prepare and harder to check.
Solicitud mejor
Please send the training-hours extract for [period] from [system], using your usual workforce group labels. Include gender, employee category, total training hours, average hours per employee, the population covered, the calculation method, and any exclusions or assumptions. We will map your labels later. This is a possible LRA training template only; please adapt it to your organisation and check the official source before sign-off.
Plantilla de correo formal
Subject: Request for training-hours data for sustainability reporting Hi [Name], Could you please share the training-hours extract for [reporting period] from [source system], using the workforce groups you normally report internally? We need the data broken down by: - gender - employee category / workforce segment - total training hours recorded in the period - average hours per employee for each group Please also include: - the population covered - the definition of training used in the extract - the calculation method - the extract date and source system - any exclusions, assumptions, or data quality notes If your team uses different internal labels, please send those as-is and we will map them later. This is a possible LRA training template only; please adapt it to your organisation and check the official source before sign-off. Thanks, [Your name]
Versión corta para Teams / Slack
Hi [Name] — could you send the training-hours extract for [period] from [system], split by your usual workforce groups plus gender? Please include the method, population covered, exclusions, and extract date. We’ll map your internal labels later. This is a possible LRA training template only; please adapt it to your organisation and check the official source before sign-off.
Ejemplos sectoriales
Retail
Contexto. A store-based workforce with full-time, part-time, and seasonal staff recorded in an LMS and HR system.
Solicitud adaptada. Please send the learning-hours extract for [period] from [LMS/HR system], split by your usual staff groups such as store, warehouse, and head office, plus gender. Include total learning hours, average hours per person, the population covered, and any exclusions such as agency staff or one-off induction sessions. This is a possible LRA training template only; please adapt it to your organisation and check the official source before sign-off.
Ejemplo de respuesta. Returned table shows: gender; staff group; headcount; total learning hours; average hours per person. Notes state that agency staff were excluded and that induction was included for new starters only.
Manufacturing
Contexto. A site-based workforce with production, maintenance, and office teams, where training is tracked through a learning platform and local spreadsheets.
Solicitud adaptada. Please provide the training-time extract for [period] from [system], using the site’s normal workforce categories such as production, maintenance, and support teams. Split by gender and include total hours, average hours per employee, the calculation method, and any items not counted, such as toolbox talks or external conferences. This is a possible LRA training template only; please adapt it to your organisation and check the official source before sign-off.
Ejemplo de respuesta. Returned table shows: gender; workforce category; headcount; total training hours; average hours per employee. Notes explain that toolbox talks were excluded and that only completed courses in the learning platform were counted.
Redacte su divulgación
Notas que convierten los datos en una divulgación
Plantillas formativas de LRA: adáptelas a su organización y consulte la fuente oficial antes de la aprobación.
Nota metodológica
Define the employee groups and gender categories used, and state that the figures show the average training time per person during the reporting period.
Nota de contexto
These figures show how much learning time different parts of the workforce received on average, helping readers see whether development time is spread evenly or concentrated in particular groups.
Declaración sobre las variaciones
If the averages moved materially from the prior period, explain whether this was driven by changes in headcount mix, training availability, programme design, or other operational factors.
Entrada del índice de contenidos
GRI 404-1 Average hours of training per year per employee — [location / page] / [notes]Centro de descargas
Herramientas y formularios de preparación
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Preparación para el aseguramiento
Para cada afirmación, compruebe la evidencia
| Afirmación | Riesgos | Evidencia que comprobar |
|---|---|---|
| We built the coverage figure from the employee records we held for the reporting year, and we split the workforce by sex and by job group using our internal HR coding. | The assurer may test whether the grouping logic was applied consistently, whether any staff were left out, and whether the categories used in the published figure match the source records. | HR headcount extract for the reporting period; workforce coding guide or data dictionary showing sex and job-group fields; reconciliation from source records to the published figure; sample employee files or system screenshots confirming the assigned codes. |
| For the disclosed workforce breakdown, we used the same cut-off date and the same employee population across all tables, and we excluded only people outside the defined reporting boundary. | The assurer may probe boundary decisions, duplicate counting, treatment of leavers and joiners, and whether the same population was used consistently across the disclosure. | Reporting boundary memo; population definition used for the disclosure; dated headcount report; joiner/leaver logs; reconciliation showing how the final population was derived; evidence of any exclusions and the reason for them. |
| We calculated the training-hours figure from attendance logs and learning-system records, then checked the total and the average before publication. | The assurer may question whether the underlying hours were complete and accurate, whether the average was calculated correctly, and whether the published number was rounded or adjusted without support. | Training attendance records; learning-management-system export; calculation workbook showing total hours and average; rounding policy or calculation note; review sign-off from the preparer and checker; exception log for missing or corrected records. |
| Where records were incomplete, we used documented estimates or replacements only after review, and we kept a clear audit trail from the original source to the final figure. | The assurer may test whether estimates were justified, whether substitutions were applied consistently, and whether the audit trail is strong enough to support the published result. | Data-quality issue log; estimate methodology or replacement rule; approval evidence for any manual adjustments; version history of the calculation file; source-to-report traceability schedule. |
| Before release, we ran a final consistency check against prior-period data, internal management reports, and the narrative in the report so the published figure agreed with the supporting schedules. | The assurer may look for unexplained movements, mismatches between tables and narrative, and weak review controls before sign-off. | Pre-publication review checklist; variance analysis versus prior period and management reporting; final proof of the report; sign-off emails or approval form; evidence of any corrections made after review. |
Paquete de evidencia que preparar
Carencias habituales en los informes
Carencias habituales
Errores que evitar al recopilar los datos
Dónde suele hacer falta juicio profesional
Ejemplos
Ejemplos ilustrativos
Sintéticos, redactados por LRA: no proceden del informe de ninguna empresa ni del texto de ninguna norma.
During the year, we tracked learning time by gender and by staff group, and we report the average number of training hours per person for each slice.
- Women: managers 18 hours, specialists 14 hours, support staff 10 hours.
- Men: managers 16 hours, specialists 12 hours, support staff 9 hours.
This example shows how a reporter can break learning time down by gender and employee group, while keeping the figures internally consistent and clearly labelled as illustrative.
We measured development time across our workforce and present the mean hours per employee, split by gender and job level.
- Women: senior leaders 22 hours, supervisors 15 hours, production operatives 11 hours.
- Men: senior leaders 20 hours, supervisors 13 hours, production operatives 10 hours.
This example demonstrates a second plausible way to present the same information, using a different sector and different staff categories while still showing the average training time by gender.
Informes de empresas
Cómo informan las empresas sobre GRI 404-1 en la práctica
Ejemplos de práctica de reporte completa y parcial. Son análisis basados en evidencia, no plantillas exactas para copiar.
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Compruebe su comprensión
Escenarios para trabajar
A preparer is compiling the learning and development note for a group with three staff segments: senior managers, office staff, and field staff. The training log shows different totals for women and men in each segment, and some people joined part-way through the year.
A company has a mix of permanent employees, fixed-term staff, and agency workers. The HR system records training for everyone, but the reporting team is unsure whether to combine all of them into one average.
The training register shows 120 employees in one category. Ninety employees each completed 8 hours of training, while 30 employees completed none. The team is unsure whether the zero-hour group should be left out because it makes the average look lower.
A preparer has separate spreadsheets for women and men, but one category has only two employees and the other has 200. The team wonders whether it is acceptable to report only the larger group because the smaller one is easy to identify.
Referencias del marco
Requisitos aplicables de GRI y divulgaciones relacionadas
Referencias disponibles del marco y divulgaciones cercanas relevantes para preparar este requisito.
GRI
GRI 404-1
dentro de GRI 404: Training and Education
Relacionado y explorar
Más en GRI 404 → Ver el catálogo completo → Inicio de la Biblioteca de divulgaciones → Buscar en todas las divulgaciones →
Preguntas frecuentes
Preguntas que responde esta página
The page says to prepare three core datapoints: gender split, worker category and average training hours. Use those as the starting set for your data request and check they are available for the same reporting period and scope.
Use it as a working checklist to move from the plain-language explainer to the datapoints, then to methodology, evidence and draft output. It is designed to help you prepare the disclosure rather than just describe it.
The page is set up to help you define what population is included, how worker categories are treated and how the average training hours are calculated. Keep those choices consistent across the datapoints and explain them clearly in the draft.
The page is aimed at sustainability/ESG managers, HR or data owners, and assurance reviewers, so ownership should sit with the person who can confirm the source data and methodology. In practice, that usually means one named owner for the data and one reviewer for assurance readiness.
The page includes an evidence pack with five items and five assurance claims to verify. Use those to show the source data, the calculation approach and the checks that support the final figures.
The page says there are five claims to verify, each with a claim, risk and evidence prompt. Use them as a control list to test whether the disclosure is supported, where it could go wrong and what documents prove it.
The page lists common reporting gaps and mistakes so you can check for missing scope, unclear methodology or weak evidence before drafting. Use that section as a pre-submission quality check.
The page includes draft-output support with visualisation ideas, narrative starters and a GRI content-index line. Use those to turn the prepared data into a short, readable draft and then tailor the wording to your organisation.
The Download Centre includes a Prep & Assurance workbook in .xlsx format. Use it to organise the datapoints, evidence and assurance checks before you finalise the draft.
The Download Centre also includes a printable Library Card in .pdf format. It is a quick reference aid for the disclosure, useful when you want the key points in one place while you work through the data and evidence.
The page notes ESRS S1 (Own Workforce) as the closest correspondence, so the same underlying data may be reusable. Treat that as a practical link rather than assuming the reporting asks are identical.
Más preguntas con las que puede ayudar esta página
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