GRI 401: Employment 2016 · Topic Standard · Cross-sectoral
Disclosure GRI 401-1
New employee hires and employee turnover 8
Practical guidance for preparing this disclosure. Use this card to identify datapoints, verify claims and organise supporting evidence. For exact requirements, always refer to the official GRI source.
Open official GRI source
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Reviewed by
Dr Ross Kurinko · GRI Certified Trainer
To prepare this disclosure
7 datapoints ↓
6 claims to verify ↓
5 evidence areas ↓
3 report examples ↓
Disclosure focus
This disclosure asks an organisation to report two basic workforce movements over the reporting period: how many people joined and how many people left. The point is to show the scale of hiring and turnover in a way that can be compared over time and, where relevant, across different parts of the business.
The practical focus is on the scope of coverage. An organisation should be clear whether the figures cover the whole workforce or only certain entities, countries, or sites, and it should apply the same boundary consistently. If it only reports on flagship locations or selected operations, that limitation should be obvious so readers do not assume the numbers represent the entire organisation.
* This LRA educational guidance supports disclosure preparation. For the exact requirements, always refer to the official GRI source.
Before you start
A quick mental checklist before you prepare this disclosure — tick each as you settle it.
Preparation
Key datapoints to prepare
| Datapoint | What to capture | Evidence hint | Owner |
|---|---|---|---|
| Age bands | The age categories used to split the workforce figure, with the exact band names and cut-offs applied in the report. | HRIS demographic fields, reporting workbook, and the age-band definition used for the period. | HR / People Analytics |
| Gender split | The gender categories used for the workforce breakdown, using the same labels and classification basis as the source data. | HRIS self-identification fields, reporting extract, and the category mapping used for the disclosure. | HR / People Analytics |
| Geographic split | The regional categories used to group the workforce, with the exact geography basis and region names applied in the report. | HRIS location data, regional mapping table, and the reporting extract for the period. | HR / People Analytics |
| New joiner count | The number of people who started employment in the reporting period, counted on the same basis as the HR source and the report cut-off. | HRIS joiner report, payroll starter records, and period-end reporting extract. | HR / People Analytics |
| New joiner rate | The share of the workforce represented by new starters in the reporting period, using the same numerator and denominator basis as the underlying headcount measure. | Joiner count, workforce denominator used for the period, and the calculation workbook. | HR / People Analytics |
| Leaver count | The number of employees who left during the reporting period, using the same employment status rules and cut-off dates as the source records. | HRIS leaver report, payroll termination records, and the period reporting extract. | HR / People Analytics |
| Leaver rate | The share of the workforce that left in the reporting period, calculated from the leaver count and the agreed workforce base for the same period. | Leaver count, workforce denominator used for the period, and the calculation workbook. | HR / People Analytics |
Show GRI 401-1 sub-elements (LRA working checklist)
- Group employees by age band.
- Group employees by gender.
- Group employees by region.
- State the total number of leavers in the reporting period.
- State the total number of new starters in the reporting period.
- State the overall turnover rate for the reporting period.
- State the overall hiring rate for the reporting period.
LRA working checklist - paraphrased; see official source
How to prepare
- Set the reporting boundary first: decide which workforce population, locations and time period you will use, so the figures are built from one consistent basis.
- Define the categories you will split the data by. For this disclosure, prepare the breakdowns by age band, gender and region, and make sure those labels are applied the same way across all figures.
- Pull together the source records that support the counts. Use the underlying HR or payroll evidence that shows new joiners and leavers during the period, together with the details needed for each breakdown.
- Calculate and present both the headcounts and the rates for new hires and turnover. Keep the totals and the percentages aligned to the same reporting period and the same workforce scope.
- Record any exclusions, adjustments or changes in method. If you have excluded any part of the workforce or changed how you classify the data, note that clearly so the reported numbers can be traced and understood.
- Check the final disclosure against the official source before sign-off. Confirm that every required data point is covered, the wording of the categories matches your chosen definitions, and the evidence file supports the published figures.
Request the joiners and leavers data
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
How many people joined and left during the period, and how do those movements break down by age band, gender and region?
Use your organisation’s own people-data terms first, then map them to the reporting labels. For example, ask for joiners/leavers, starters/exits or headcount movements if that is how the data is held internally. Adapt the wording to your HRIS, payroll or workforce reporting setup, and check the source used before sign-off.
Weak request
Please provide the GRI 401-1 data for the year, including the required breakdowns and rates.
Why it fails: It uses framework language instead of the organisation’s own people-data terms, so the owner has to translate the ask before they can respond. It also leaves out the source system, population boundary, internal category labels and the basis for the rates, which makes the extract harder to validate.
Better request
Please send the joiner and leaver extract for [reporting period] for [entity], using the age bands, gender groups and regions from your HRIS or workforce report. Include the totals, the percentages, the definitions used, any exclusions and the final-check contact.
Formal email template
Subject: Request for joiner and leaver data for [reporting period] Hi [name], Could you please share the workforce movement data for [reporting period] for [entity / population boundary]? We need the figures split by the age bands, gender categories and regions used in your system, together with: - total number of people who joined during the period - joiner rate for the period - total number of people who left during the period - leaver rate for the period Please also include: - the source system or report used - the definitions applied for joiners and leavers - the grouping labels used for age, gender and region - any exclusions, adjustments or known data issues - the person who can confirm the extract is final A possible LRA training template is attached below for ease of response. Please adapt this to your organisation’s own terms and check the source before sign-off. Thanks, [preparer name]
Short Teams / Slack version
Hi [name] — could you send the [reporting period] joiner/leaver extract for [entity]? Please include the age bands, gender groups and regions you use internally, plus the totals and rates for people who joined and left. Also share the source report, definitions, any exclusions and who can confirm it’s final. Please adapt to your own terms and check the source before sign-off. Thanks.
Industry examples
Retail
Context. Store and distribution workforce across multiple regions
Adapted request. Please share the store and warehouse joiner/leaver report for [reporting period] for [entity], split by the age bands, gender groups and regions used in the people dashboard. Include the total starters, starter rate, total exits and exit rate, plus the source report, definitions and any exclusions.
Example response. Extract from the workforce dashboard covering all employees in scope, with age bands, gender categories and region labels as held in the system; totals and rates for starters and exits; notes confirming that internal transfers were excluded; and the HR reporting lead as the sign-off contact.
Manufacturing
Context. Plant workforce with site-based reporting and shift patterns
Adapted request. Please send the site workforce movement file for [reporting period] for [entity], using the age groups, gender categories and site regions already used in your monthly people pack. Include joiners, leavers, the related rates, the source report and any rules used to exclude temporary records or internal moves.
Example response. CSV export from the plant people report showing age group, gender and site region; joiner and leaver counts and percentages; a note that agency workers were excluded; and confirmation from the HR operations lead that the file is final.
The full request pack — response form, data table, evidence metadata and sign-off — is in the Download Centre.
Draft your disclosure
LRA training templates — adapt them to your organisation, and check the official source before sign-off.
Method note
State how you defined a new starter and a leaver for this report, and explain the basis used to count and rate them across the period.
Context note
Use the figures to show the scale of workforce inflow and outflow, and to indicate whether the organisation is expanding, stable, or seeing more exits than entries.
Fluctuation statement
If the numbers moved materially, point to the main operational drivers, such as recruitment activity, restructuring, seasonal demand, or local labour-market conditions.
Content index entry
GRI 401-1 New employee hires and employee turnover 8 — [location / page] / [notes]
Download Centre
Professional preparation tools and forms for GRI 401-1. Each download includes a concise “How to use” guide.
Assurance readiness
For each claim, check the evidence
| Claim | Risk | Evidence to check |
|---|---|---|
| I prepared the coverage figure using the age bands we apply in our HR system, and I checked that the grouping was consistent across the full population included in the calculation. | The assurer may probe whether the age bands were applied consistently, whether any employees were left out, and whether the grouping could be reproduced from source records. | HR extract showing employee ages or age bands; the calculation file; a note of the age-band definitions used; reconciliation to the headcount population included in the figure. |
| I built the figure from the workforce records we hold for sex or gender, and I verified that the same classification was used throughout the reporting population. | The assurer may probe whether the classification basis was stable, whether any records were missing or duplicated, and whether the reported split matches the underlying data. | HR master data extract; data dictionary or field definition for the classification used; calculation workbook; exception log for missing or corrected records. |
| I compiled the location split from the worksite or country information in our employee records, and I checked that the geographic grouping matched the way we manage the disclosed workforce. | The assurer may probe whether the regional grouping was defined before calculation, whether employees were assigned to the correct location, and whether cross-border cases were handled consistently. | Employee location extract; mapping of sites or countries to the reported regions; calculation file; evidence of review for employees with multiple or changing locations. |
| I counted the people who joined during the period from the payroll and onboarding records, and I reconciled the total to the source systems before publication. | The assurer may probe whether the joiner count includes only the intended population, whether duplicates or reversals were removed, and whether the total agrees with the underlying records. | Joiner report from HR or payroll; onboarding list; reconciliation to the final count; review sign-off showing the total was checked before release. |
| I calculated the joiner rate from the same underlying count and the agreed workforce base, and I checked the arithmetic before the figure went into the report. | The assurer may probe whether the denominator was the correct base, whether the formula was applied correctly, and whether the rate can be recalculated from the evidence held. | Calculation workbook with formulae; source count for joiners; agreed base population used in the rate; reviewer check or sign-off on the calculation. |
| I derived the leaver count from the exit records and payroll data, and I confirmed that the final number matched the reconciled source evidence. | The assurer may probe whether the turnover count includes the right leavers, whether timing cut-offs were applied consistently, and whether any adjustments were fully supported. | Exit or termination report; payroll movement data; reconciliation schedule; evidence of review of late or corrected leaver records. |
Evidence pack to prepare
- The governing policy or written commitment behind this disclosure
- A methodology / definition note setting out how the disclosure was scoped and prepared
- Source-system exports the figures or facts were drawn from
- The internal approval / sign-off record for the disclosure before publication
- Minutes or records evidencing the relevant engagement or consultation
Common reporting gaps
- A percentage is stated without the underlying counts (numerator and denominator).
- The denominator — what the figure is a share of — is not explained.
- Partial scope is reported as if it were complete coverage.
- One-off activities are counted as if they were ongoing programmes.
- Boundary or period changes that move the figure are not flagged.
- Exclusions from the reported scope are not listed or explained.
Mistakes to avoid when collecting the data
- Wrong data owner
Chasing the HR lead by default can miss the person who actually holds the joiners-and-leavers file, so the figures come from the wrong team.
- Framework words, not business terms
Asking for the data in disclosure language instead of the organisation’s own labels can leave people unsure which report, extract, or dashboard to use.
- Scope not pinned down
If the team does not agree which parts of the business are in scope, one site or subsidiary can be left out or counted twice.
- Wrong time basis
Pulling numbers from the wrong date range or using a different cut-off from the reporting period can make the headcount movement inconsistent with the rest of the pack.
- Mixed counting methods
Combining a point-in-time headcount with a period total in the same working paper can distort both the hire count and the exit count.
- Source labels lost
Copying figures into a new sheet without keeping the original file names, tab names, or field labels makes it hard to trace where each number came from.
- Populations merged
Putting permanent staff, contractors, and other worker groups into one pool can blur the joiner and leaver totals that should stay separate.
- No evidence trail
Saving the numbers without the supporting extract date, owner, and approval note leaves no clear path for later review or sign-off.
Where judgement is often needed
- Set the reporting perimeter after acquisitions or disposals
Decide whether people added or removed through a business change sit inside the period counts, then explain the cut-off you used so the headcount and movement figures are read on the same basis.
- Choose one rule where local employment definitions differ
If countries classify starters, leavers, or worker status differently, apply a single group-wide approach or clearly map local rules to it and state the method used.
- Agree how to treat people on the boundary of the workforce
Make a consistent call on interns, agency workers, fixed-term staff, contractors, and similar edge groups, then disclose which categories were included or left out.
- Align the timing for hires and exits
Use one date rule for when a person counts as joining or leaving, and explain whether that is based on contract start, first day worked, notice date, or another internal trigger.
- Decide whether to use actual records or estimates
Where complete records are not available, use a documented estimate only if it is the best available basis, and say which parts were measured and which were approximated.
- State the denominator used for the rate figures
Explain the workforce base behind the percentages, including whether it reflects average staff, year-end staff, or another internal population measure.
- Handle partial-year service and part-time staff consistently
Apply the same counting logic to people who worked only part of the year or part of the week, and describe any normalisation used before calculating totals or rates.
- Round numbers in a way that still ties back
Use one rounding rule across the table, and check that rounded totals and percentages remain understandable against the underlying records.
- Protect privacy when the workforce is small
If a split by age band, gender, or region could identify individuals, combine categories or suppress detail and explain the aggregation approach used.
Examples
Illustrative examples
Synthetic, written by LRA — not from a company report, not text from any standard.
Retail · synthetic · written by LRA
This example shows how to present hiring and turnover counts and rates with a simple breakdown by age, gender and region. It is illustrative only.
| Category | Women | Men | Total |
|---|---|---|---|
| Under 30 — hires | 18 | 22 | 40 |
| Under 30 — turnover | 9 | 11 | 20 |
| 30 to 49 — hires | 14 | 16 | 30 |
| 30 to 49 — turnover | 7 | 8 | 15 |
| 50 and over — hires | 4 | 6 | 10 |
| 50 and over — turnover | 3 | 4 | 7 |
Synthetic example only: we show new joiners and leavers for the year, split by age band, sex and region. The figures below are internally consistent and are meant to illustrate how we might present this information.
Manufacturing · synthetic · written by LRA
This example demonstrates a second way to disclose workforce inflows and outflows, using age, gender and region as the breakdowns. It is not a real company disclosure.
| Category | North America | Europe | Asia-Pacific | Total |
|---|---|---|---|---|
| Women 18 to 29 — hires | 12 | 10 | 8 | 30 |
| Women 18 to 29 — turnover | 6 | 5 | 4 | 15 |
| Men 18 to 29 — hires | 14 | 11 | 9 | 34 |
| Men 18 to 29 — turnover | 7 | 6 | 5 | 18 |
| Women 30 and over — hires | 9 | 8 | 7 | 24 |
| Women 30 and over — turnover | 4 | 4 | 3 | 11 |
Synthetic example only: we summarise recruitment and exits for the period across age bands and regions, with a split by gender. The numbers are made up for training purposes and remain mathematically consistent.
Draft output & visualisation ideas
How to turn the collected data into a draft disclosure. The charts below are drawn from the illustrative figures above — swap in your own data.
Other views you could build
- New joiners by age band, gender and region — stacked bar: How recent hires are distributed across age bands, split by gender and region to show where recruitment is concentrated.
- Leavers by age band, gender and region — stacked bar: How employee exits are spread across age bands, split by gender and region to highlight any uneven patterns.
- Hiring and turnover rates side by side — bar: A direct comparison of the two rates for the period, making it easier to see whether inflow or outflow is higher.
- Headcount movement summary — table: The total count and rate for new starters and for departures in one place, with the underlying breakdown fields alongside them.
- Regional pattern in workforce movement — map: Where new hires and departures are happening across regions, helping readers spot geographic differences.
From a number to a disclosure
What separates a figure from a disclosure.
Basic
We hired 24 people and 6 left during the period.
Better
We hired 24 people and 6 left during the period, with new starters split by age group, gender and region, and the hire and exit rates were 12% and 3%.
Best
For the year ended 31 December 2025, we hired 24 people and 6 left, with new starters split by age group, gender and region; the hire rate was 12% and the exit rate 3%, and the higher hiring level mainly reflected opening a new team.
Real reports where this topic is disclosed. The confidence label shows how closely each match maps to GRI 401-1 — these are report practice, not exact disclosure examples.
| Company | Sector · Country | Year | Match | Page | Report | Assurance | |||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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Compal Electronics, Inc. | Technology Hardware and Equipment · Taiwan | 2025 | Partial | p. 209 →p. 128 →p. 151 → | Compal ESG Report 2025 → | PwC | ||||||||||||||||||||||||
Evidence in Compal Electronics, Inc.’s reportWhat the report shows Compal Electronics’ 2025 ESG Report provides detailed data on workforce composition and turnover rates, including new hire rates and total turnover percentages by gender and age group (pp.125, 128-129). The report also includes numeric values on plant personnel distribution across regions (p.169) and turnover calculations explained on page 128. However, the report does not clearly present aggregated turnover rates or voluntary turnover trends over multiple years, nor does it provide contextual analysis of these figures.
Evidence-based summary of this company’s own report — not a disclosure template to copy, and not a compliance verdict. Datapoint coverage
Source trail
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Yuanta Financial Holding Co., Ltd. | Banks / Diverse Financials / Insurance · Taiwan | 2024 | Partial | p. 167 →p. 169 →p. 157 → | 2024 ESG Report → | PwC | ||||||||||||||||||||||||
Evidence in Yuanta Financial Holding Co., Ltd.’s reportWhat the report shows Yuanta Financial Holding Co., Ltd.'s 2024 ESG Report provides detailed data on workforce demographics and initiatives, including a "work adaptability management plan for middle-aged and senior workers" with six organised seminars (p.141). The report also presents gender distribution across regions with specific numbers for male and female employees (p.159), regional employee percentages (p.157), and employee turnover rates by gender and region (p.158). However, the report lacks clear numeric values or narrative items related to some other specific sustainability metrics, as no quotable evidence was found for those aspects.
Evidence-based summary of this company’s own report — not a disclosure template to copy, and not a compliance verdict. Datapoint coverage
Source trail
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ASE Technology Holding Co., Ltd. | Semiconductors · Taiwan | 2024 | Partial | p. 262 →p. 250 →p. 168 → | 2024 CSR Report → | Deloitte | ||||||||||||||||||||||||
Evidence in ASE Technology Holding Co., Ltd.’s reportWhat the report shows ASE Technology Holding Co., Ltd.'s 2024 CSR Report provides detailed data on workforce demographics and related metrics, including the percentage of employees qualified for parental leave by gender (63.82% male, p.251), new hire percentages by gender (55.76% male, p.250), and employee turnover rate at 11.4% with a noted decrease from the previous year (p.168). The report also includes information on occupational injury rates (p.254) and employee engagement survey coverage exceeding 90% (p.163). However, there is no clear evidence regarding other specific diversity or inclusion metrics beyond these datapoints, and some narrative items expected for comprehensive disclosure are not found in the report.
Evidence-based summary of this company’s own report — not a disclosure template to copy, and not a compliance verdict. Datapoint coverage
Source trail
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Check your understanding
Your HR system shows 18 people joined during the year and 12 left. The draft table also breaks the joiners and leavers down by age band, gender and region, but one region has been left blank because the team thought it was optional.Should you leave that region blank, or do you need to complete the breakdown before sign-off?
Model answer. You should complete the regional split before sign-off. For this disclosure, the joiner and leaver figures are not just totals: they are also presented by age group, gender and region, so a blank region would leave the picture incomplete. The totals must also stay internally consistent with the breakdowns, so the 18 joiners and 12 leavers should be traceable across the sub-groups.
Why this matters. Present both the overall counts and the three breakdowns, and make sure the parts add back to the totals.
A preparer has 24 new starters in the period and calculates a hire rate of 20%. Later, they realise the workforce denominator used for the rate was based on a different headcount date from the one used elsewhere in the report.Can you keep the 20% rate if the underlying base is not the same as the rest of the disclosure pack?
Model answer. No. The rate should be calculated from the same reporting basis used for the rest of the disclosure, so the method is consistent and the figure can be checked. If the base changes, the rate may still be mathematically correct, but it is not suitable for sign-off unless the calculation basis is aligned and explained in the working papers.
Why this matters. Use one consistent basis for the rate and keep the calculation trail clear.
The HR team reports 9 leavers in total, but the exit records show 6 voluntary departures and 3 redundancies. The draft only includes the total turnover number and rate, with no supporting split in the working file.Do you need to keep the underlying leaver categories in the evidence pack even though the published line only asks for the total?
Model answer. Yes. Even if the published line shows only the total number and total rate, the working papers should still let you trace that total back to the source records. Here, the 6 voluntary departures plus 3 redundancies equal the 9 leavers, so the evidence should show how the total was built up and allow a reviewer to follow the trail.
Why this matters. Keep enough source detail to prove how the total turnover figure was assembled.
A business unit hired 10 people in the year, but 2 of them were internal transfers from another part of the group. The preparer is unsure whether those 2 should sit inside the new-hire count or be excluded.How should you decide whether those 2 people belong in the new-hire total for this disclosure?
Model answer. You should first check whether your organisation treats internal moves as new hires for this metric and apply that approach consistently. The key is that the count reflects the organisation’s chosen reporting boundary and is used the same way across the period, with the age, gender and region breakdowns matching that same population. If the internal transfers are included, the total should be 10; if they are excluded, the total should be 8, and the working papers need to show the basis used.
Why this matters. Define the counted population clearly and apply the same rule throughout the period.
Analyse this disclosure across real reports
See how companies actually report GRI 401-1 — drawn from their own published reports, with the exact pages, and an LRA AI-assistant that works through it with you. Available to LRA Community members and to students throughout their platform access.
Related framework references
How this disclosure maps across the major reporting frameworks.
→
ESRSRelated
ESRS S1
Own Workforce — closest topical match (post-Omnibus ESRS catalogue).
→
IFRSNo equivalent
—
No direct IFRS S1/S2 topical equivalent.
Related & explore
Questions this page answers
How do I prepare GRI 401-1 Employment data for this page step by step?
Use the page’s plain-language explainer, then follow the step-by-step ‘how to prepare’ section to organise the disclosure. The page also points you to the datapoints to prepare, the evidence pack, and the draft-output section so you can move from raw data to a usable draft. ↑ section
What data do I need to collect for GRI 401-1 Employment on this page?
The page says to prepare age bands, gender split, geographic split, new joiner count, new joiner rate, leaver count, and leaver rate. It is set up to help you gather those datapoints and then turn them into a draft disclosure. ↑ section
How should I set the scope and methodology for the GRI 401-1 Employment figures on this page?
The page gives a step-by-step ‘how to prepare’ section, which is the place to use when setting scope and methodology. It also highlights common reporting gaps, so you can check that your approach is consistent before drafting. ↑ section
Who should own the GRI 401-1 Employment data and evidence pack?
The page is written for sustainability/ESG managers, HR or data owners, and assurance reviewers, so ownership should sit with the people who can source the workforce data and support it with evidence. Use the evidence pack and assurance claims to make responsibilities clear. ↑ section
What should go into the evidence pack for GRI 401-1 Employment?
The page includes an evidence pack with five items to support assurance readiness. Use that pack alongside the six assurance claims to show how the numbers were prepared and where they came from. ↑ section
What are the six assurance claims I need to verify for GRI 401-1 Employment?
The page says there are six assurance claims to verify, each with a claim, risk, and evidence angle. Use those claims to test whether the data, method, and supporting documents are strong enough for review. ↑ section
What are the common reporting gaps or mistakes on the GRI 401-1 Employment page?
The page lists common reporting gaps and mistakes to help you spot issues before you finalise the disclosure. It is useful for checking the completeness of the datapoints, the consistency of the method, and whether the evidence pack is ready. ↑ section
How do I use the workbook and printable Library Card downloads for GRI 401-1 Employment?
The Download Centre includes a Prep & Assurance workbook in .xlsx format and a printable Library Card in .pdf format. Use them to organise the preparation work, capture evidence, and keep a practical reference while drafting. ↑ section
Can I use the synthetic example disclosure on this page to draft my own GRI 401-1 Employment table?
Yes, the page includes synthetic illustrative example disclosures, including a quantitative table, to show how the disclosure can be presented. Treat it as a model for structure and formatting only, and make sure your own figures are internally consistent. ↑ section
How do I turn the GRI 401-1 Employment data into a draft narrative and content index line?
The draft-output section gives visualisation ideas, narrative starters, and a GRI content-index line. Use those prompts to turn the prepared data into a clear draft that can be reviewed and checked against your evidence. ↑ section
Can I reuse my GRI 401-1 Employment data for ESRS S1 Own Workforce reporting?
The page says the closest ESRS correspondence is ESRS S1 (Own Workforce), so the data may be reusable across both. It does not say the requirements are identical, so you should still check the other framework separately. ↑ section
More questions this page can help with
- GRI 401-1 Employment checklist for age bands, gender split and geographic split
- GRI 401-1 Employment new joiner count and leaver rate how to calculate and present
- GRI 401-1 Employment assurance evidence pack what documents do I need
- GRI 401-1 Employment common mistakes and reporting gaps to avoid
- GRI 401-1 Employment workbook download how to use the Prep & Assurance workbook
- GRI 401-1 Employment example disclosure table synthetic illustration
- GRI 401-1 Employment draft narrative starters and content index line
- GRI 401-1 Employment step by step preparation guide
- GRI 401-1 Employment evidence pack and assurance claims explained
- GRI 401-1 Employment ESRS S1 Own Workforce data reuse
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Sources, status and disclaimer
This LRA assistance tool is designed for educational and internal data-collection purposes. It is not an official interpretation of the GRI Standards, IFRS Sustainability Disclosure Standards or EU CSRD/ESRS requirements. When applying these frameworks in professional practice, users should consult and double-check the official standards, guidance and applicable regulatory sources.
