GRI 2: General Disclosures · Universal Standard
Disclosure GRI 2-7
Employees
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.
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Reviewed by
Dr Ross Kurinko · GRI Certified Trainer
To prepare this disclosure
22 datapoints ↓
4 claims to verify ↓
5 evidence areas ↓
3 report examples ↓
Disclosure focus
This disclosure asks an organisation to explain how many people it employs, and to do so in a way that gives a clear picture of its workforce rather than just a headline total. The emphasis is on employees, not contractors or other workers, and on presenting the information in a way that is understandable and comparable across the reporting period.
In practice, the focus is usually on whether the figures cover the organisation’s full operations, including different sites, countries or business units, rather than only its largest or most visible locations. The key question is whether the reported employee numbers reflect the whole employed workforce and are explained clearly enough for a reader to understand the scope and basis of the count.
* 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 |
|---|---|---|---|
| Total workforce | The overall employee count for the reporting period, using the organisation’s chosen counting basis. | HRIS headcount extract, payroll summary, or workforce report; reconcile to the source used for the disclosed methodology. | HR / People Operations |
| Workforce by gender | Employee numbers split by gender for the reporting period, using the organisation’s defined gender categories. | HRIS demographic report and the organisation’s gender classification rules; check the split ties to the total workforce count. | HR / People Operations |
| Workforce by region | Employee numbers split by geographic region for the reporting period, using the organisation’s regional grouping. | HRIS location report, legal-entity mapping, or regional workforce dashboard; confirm each employee is assigned to one region only. | HR / People Operations |
| Permanent staff total | The overall count of employees on ongoing contracts for the reporting period. | HRIS contract-type report and payroll records; reconcile the permanent category to the organisation’s employment-status definitions. | HR / People Operations |
| Permanent staff by gender | Employees on ongoing contracts split by gender for the reporting period. | HRIS contract-type and demographic extract; verify the permanent subset is the same population used for the gender split. | HR / People Operations |
| Permanent staff by region | Employees on ongoing contracts split by geographic region for the reporting period. | HRIS contract-type, location, and regional mapping report; check the permanent subset is assigned consistently across regions. | HR / People Operations |
| Temporary staff total | The overall count of employees on temporary contracts for the reporting period. | HRIS contract-type report, agency worker listing if applicable, and payroll records; reconcile to the organisation’s temporary-worker definition. | HR / People Operations |
| Temporary staff by gender | Employees on temporary contracts split by gender for the reporting period. | HRIS contract-type and demographic extract; confirm the temporary subset is the same one used for the gender analysis. | HR / People Operations |
| Temporary staff by region | Employees on temporary contracts split by geographic region for the reporting period. | HRIS contract-type and regional location report; verify temporary workers are assigned to the same region logic as the total. | HR / People Operations |
| Zero-hours staff total | The overall count of employees with no guaranteed hours for the reporting period. | HRIS contract-type report and payroll roster for casual or variable-hours staff; reconcile to the organisation’s no-guarantee-hours definition. | HR / People Operations |
| Zero-hours staff by gender | Employees with no guaranteed hours split by gender for the reporting period. | HRIS contract-type and demographic extract; check the no-guaranteed-hours subset is complete before the gender split is calculated. | HR / People Operations |
| Zero-hours staff by region | Employees with no guaranteed hours split by geographic region for the reporting period. | HRIS contract-type and regional assignment report; confirm all no-guaranteed-hours workers are mapped to one region. | HR / People Operations |
| Full-time staff total | The overall count of employees working full-time for the reporting period. | HRIS working-pattern report and payroll records; reconcile the full-time category to the organisation’s working-hours definition. | HR / People Operations |
| Full-time staff by gender | Employees working full-time split by gender for the reporting period. | HRIS working-pattern and demographic extract; verify the full-time subset is the same population used for the gender split. | HR / People Operations |
| Full-time staff by region | Employees working full-time split by geographic region for the reporting period. | HRIS working-pattern and regional location report; check the full-time subset is assigned consistently across regions. | HR / People Operations |
| Part-time staff total | The overall count of employees working part-time for the reporting period. | HRIS working-pattern report and payroll records; reconcile the part-time category to the organisation’s hours-based definition. | HR / People Operations |
| Part-time staff by gender | Employees working part-time split by gender for the reporting period. | HRIS working-pattern and demographic extract; confirm the part-time subset is complete before the gender split is produced. | HR / People Operations |
| Part-time staff by region | Employees working part-time split by geographic region for the reporting period. | HRIS working-pattern and regional assignment report; verify the same region logic is used for both the total and the breakdown. | HR / People Operations |
| Counting method | A plain explanation of how the workforce figures were built, including whether they are based on individual people, FTE, or another counting basis. | Disclosure methodology note, HR reporting policy, and the source report definitions; keep the basis consistent across all workforce tables. | HR / People Operations |
| Timing basis | A plain explanation of whether the workforce figures reflect the period-end position, an average over the period, or another timing basis. | Disclosure methodology note and reporting calendar; confirm the same timing basis is used throughout the workforce disclosure. | HR / People Operations |
| Workforce context | Any background needed to make the workforce figures understandable, such as organisational changes, scope boundaries, or classification rules affecting the reported numbers. | Management commentary, HR reporting notes, and scope mapping; include only context that helps explain the reported workforce data. | HR / People Operations |
| Workforce movements | A clear explanation of any major rises or falls in employee numbers during the period and compared with prior periods. | Month-by-month HRIS trend, restructuring records, and joiner/leaver analysis; tie the explanation to the reported workforce totals. | HR / People Operations |
Show GRI 2-7 sub-elements (LRA working checklist)
- Flag any material rises or falls in employee numbers during the year, and when comparing one period with another.
- Explain the method and assumptions used to build the figures, including whether they are taken at period end, averaged over the period, or calculated another way.
- Explain the method and assumptions used to build the figures, including whether they are shown as headcount, FTE, or calculated another way.
- Show employee numbers split by gender.
- Show employee numbers split by region.
- Show full-time staff numbers split by gender.
- Show full-time staff numbers split by region.
- Show non-guaranteed-hours staff numbers split by gender.
- Show non-guaranteed-hours staff numbers split by region.
- Show part-time staff numbers split by gender.
- Show part-time staff numbers split by region.
- Show permanent staff numbers split by gender.
- Show permanent staff numbers split by region.
- Show temporary staff numbers split by gender.
- Show temporary staff numbers split by region.
- Add any context needed to make the figures for the two split disclosures understandable.
- State the total number of employees.
- State the total number of full-time employees.
- State the total number of non-guaranteed-hours employees.
- State the total number of part-time employees.
- State the total number of permanent employees.
- State the total number of temporary employees.
LRA working checklist - paraphrased; see official source
How to prepare
- Set the reporting boundary first: decide which workforce population you are counting and make sure the same scope is used across the whole disclosure, so the totals and splits all relate to the same employee base.
- Define the categories you will use before you start counting. Separate the workforce into the required employment types, then sort each group by gender and by region, so every figure can be placed in the right bucket.
- Choose and record the counting method up front. Confirm whether you are using individual people, full-time equivalent measures, or another approach, and note whether the figures reflect the period-end position, an average over the period, or a different timing basis.
- Gather the source records and build the numbers from them. Use payroll, HR or equivalent internal records to compile the totals for each employment type and the related gender and regional splits, checking that the figures are complete and internally consistent.
- Add the explanatory context needed to make the data understandable. Include any notes that help a reader interpret the figures, and explain any material movement in employee numbers during the period and compared with the prior period.
- Document any exclusions, changes in method, or other assumptions, then compare the draft against the official source to confirm every required total, split and narrative point is covered and nothing has been omitted or mis-stated.
Request the workforce headcount and mix data
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
What is the workforce count and how is it split across contract type, gender and region for the reporting period, with the method and any notable movements explained?
Use your organisation’s own workforce labels first (for example, staff, colleagues, workers, contingent labour, fixed-term, casual, bank, agency, or similar), then map them to the reporting categories needed for sign-off. Keep the request in business language that your team already uses, and only translate into the reporting view at the end.
Weak request
Please provide the GRI 2-7 employee disclosure data, including the required breakdowns and methodology.
Why it fails: This uses framework wording that may not match how the business stores or talks about the data, so the owner may not know which report, system, or internal categories to pull. It also leaves out the practical details needed to reconcile the numbers, such as the period, boundary, basis, and explanation of movements.
Better request
Please send the workforce headcount pack for [period] covering [scope]. Use your normal internal labels for staff groups, gender and region, and include totals, the counting basis, whether the figures are at period end or averaged, the source system, assumptions, and any material changes this period.
Formal email template
Subject: Request for workforce headcount and mix data for [reporting period] Dear [name/team], Please could you share the workforce data pack for [reporting period] for the entities/sites in scope for [reporting boundary]. For the pack, please use the organisation’s own workforce labels first, then map them to the reporting view. I need the following: - total workforce count - split by contract type used internally - split by gender using the labels in your system - split by region / geography used in the business - the counting basis used (for example, headcount or FTE) - whether the figures are taken at period end, averaged over the period, or calculated another way - any context needed to explain the numbers - any notable changes during the period and compared with the prior period Please also include the source system, extraction date, and any assumptions or exclusions. A possible LRA training template only — please adapt this to your organisation and check the official source before sign-off. Many thanks, [preparer name] [team] [contact details]
Short Teams / Slack version
Hi [name], could you send over the workforce pack for [period] for [scope]? Please use your usual internal labels first, then map them for reporting. I need totals plus splits by contract type, gender and region, along with the counting basis, timing basis, source system, assumptions, and any big changes this period. Thanks — [name]
Industry examples
Retail
Context. A chain with stores, head office, and seasonal staff across several countries.
Adapted request. Please provide the workforce pack for [period] covering stores, distribution centres, and head office in scope. Use our usual labels for permanent staff, fixed-term staff, seasonal staff, and part-time staff, then map them to the reporting view. Include totals, splits by gender and region, the counting basis, timing basis, source system, and any seasonal peaks or store closures that affected the numbers.
Example response. Returned table shows permanent, fixed-term, seasonal, and part-time staff by gender and region, plus a note that December trading drove a temporary increase in seasonal staff in two regions.
Manufacturing
Context. A multi-site business with shift workers, agency labour, and a central payroll system.
Adapted request. Please send the workforce data pack for [period] for all plants and the central office in scope. Use the site’s own worker labels first, then map them for reporting. Include totals, splits by gender and region, and separate lines for permanent, temporary, agency, and part-time staff, together with the counting basis, whether the figures are period-end or average, and any plant shutdowns or ramp-ups that explain changes.
Example response. Returned table shows headcount by worker group, gender, and region, with a note that one plant shutdown reduced temporary staff in the final quarter and a new line start-up increased permanent hires in another region.
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 counted people for the reporting period, including what you treated as each employment category and how you assigned gender and region for the breakdowns.
Context note
Explain that the figures describe the size and make-up of the workforce at the reporting date, and that the splits help readers understand how employment is distributed across contract type, gender and location.
Fluctuation statement
If the numbers moved materially, note the main operational reasons, such as hiring, departures, contract changes or shifts between regions, and say whether the change was temporary or expected to continue.
Content index entry
GRI 2-7 Employees — [location / page] / [notes]
Download Centre
Professional preparation tools and forms for GRI 2-7. Each download includes a concise “How to use” guide.
Assurance readiness
For each claim, check the evidence
| Claim | Risk | Evidence to check |
|---|---|---|
| The information reported for this disclosure reconciles to the underlying source records. | What is reported cannot be traced back to the systems or documents it was drawn from, or does not tie out to them. | calculation_workbook reconciling the reported value to source_system_export |
| The information reported for this disclosure is current as at the reporting date. | The disclosure reflects a different period, a cut-off before the reporting date, or stale data carried over from a prior period. | approval_record showing the data cut-off date and the period covered |
| The scope behind the information reported for this disclosure is applied consistently. | Parts of the organisation are silently in or out of scope, or the scope differs from the prior period without that change being explained. | methodology defining the scope and a site_register of what it covers |
| Everything in scope is included in the information reported for this disclosure — nothing material is left out. | Parts of the population that should be reported are omitted, understating or overstating the disclosure. | site_register of the full population vs the calculation_workbook of what was actually included |
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
- 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.
Mistakes to avoid when collecting the data
- Wrong data owner
Chasing the wrong team for the headcount file leaves HR, payroll, and local managers each assuming someone else has the source numbers.
- Framework language in the request
Asking for the figures using disclosure jargon instead of the business’s own labels makes the data owner map the request to the wrong report or field.
- No clear scope or boundary
Failing to state which entities, sites, or worker groups are in scope leads to some people being counted twice and others not at all.
- Mixed timing basis
Pulling some figures from the period-end snapshot and others from an average over the year creates numbers that cannot be compared cleanly.
- Mixed counting method
Combining headcount-style records with full-time equivalent-style records in the same table distorts the totals and the splits by group.
- Source labels stripped out
Copying the numbers without the original field names or report labels makes it hard to trace each figure back to the system extract.
- Groups merged that should stay separate
Rolling permanent, temporary, non-guaranteed-hours, full-time, and part-time workers into one pool hides the breakdowns needed for the disclosure.
- No evidence trail
Saving only the final spreadsheet, with no extract date, version, or sign-off record, leaves no way to show where the figures came from or who checked them.
Where judgement is often needed
- Set the group boundary after deals and closures
Explain which employing entities are included after acquisitions, disposals or other structural changes, and keep the same cut-off logic clear across the totals and each split.
- Choose one people-count basis and stick to it
State whether you used a simple person count, a full-time equivalent approach, or another internal method, and apply that basis consistently across all employee categories.
- Fix the timing rule for the numbers
Say whether the figures reflect the position at period-end, an average over the year, or another timing basis, and use that same timing for every table line.
- Handle local job labels with a clear mapping
Where country-level employment labels do not line up neatly with your reporting buckets, explain the mapping you used and how you treated roles that sit between categories.
- Decide how to treat people on the boundary of employment status
Set out whether workers with uncertain hours, short contracts, probationary status or similar edge cases are counted in the relevant group, and explain the rule used.
- Use estimates only where direct counts are not available
If some sites or systems cannot provide exact figures, disclose that estimates were used, describe the basis for them, and keep the method consistent across the dataset.
- Round in a way that still reconciles
If you round figures for presentation, explain the rounding approach and make sure the rounded subtotals still make sense against the overall total.
- Protect privacy when small teams could identify people
Where a regional or gender split would expose individuals in a small population, aggregate the data further or explain the privacy-driven grouping used.
- Explain what changed when year-on-year numbers move sharply
If headcount shifts materially between periods, describe the operational reason in plain language and link it to the relevant change in the workforce base.
Examples
Illustrative examples
Synthetic, written by LRA — not from a company report, not text from any standard.
Food manufacturing · synthetic · written by LRA
This example shows how a company can present a single workforce snapshot with separate views by contract status, gender and geography, while keeping the totals aligned across each breakdown.
| Category | Women | Men | Total |
|---|---|---|---|
| All staff | 420 | 380 | 800 |
| Permanent staff | 300 | 260 | 560 |
| Temporary staff | 80 | 70 | 150 |
| Non-guaranteed hours staff | 40 | 50 | 90 |
| Full-time staff | 260 | 240 | 500 |
| Part-time staff | 160 | 140 | 300 |
Synthetic illustration only: we set out our workforce headcount by contract type, gender and region, and also show the split between full-time and other working patterns. The figures below are internally consistent and are for training purposes only.
Logistics and distribution · synthetic · written by LRA
This example demonstrates a second way to organise the same workforce information, using regional groupings alongside contract type and gender so the reader can see how the totals are built up.
| Category | North America | Europe | Asia-Pacific | Total |
|---|---|---|---|---|
| All staff | 220 | 180 | 100 | 500 |
| Permanent staff | 150 | 120 | 70 | 340 |
| Temporary staff | 40 | 30 | 20 | 90 |
| Non-guaranteed hours staff | 30 | 30 | 10 | 70 |
| Full-time staff | 180 | 140 | 80 | 400 |
| Part-time staff | 40 | 40 | 20 | 100 |
Synthetic illustration only: we present our workforce counts by employment status, with matching splits by gender and region, plus a separate view of full-time and other working patterns. All numbers are made up for educational use and reconcile within each line.
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
- Workforce headcount by employment type — stacked bar: How the overall workforce is split across permanent, temporary, non-guaranteed-hours and full-time categories, using the totals provided for each group.
- Gender mix within each employment group — stacked bar: The male/female or other gender breakdown for each employment category, so readers can compare composition across contract types.
- Geographic spread of employees — map: Where employees are located by region, using the regional breakdowns for the total workforce and for each employment group.
- Employee totals by contract status — bar: A side-by-side comparison of the total number of people in each employment category, highlighting the relative size of permanent, temporary, non-guaranteed-hours and full-time staff.
- Permanent and temporary workforce profile — table: A compact summary of totals plus gender and regional splits for permanent and temporary staff, making the underlying counts easy to check.
- Non-guaranteed-hours workforce profile — donut: The share of employees on non-guaranteed-hours arrangements, with a linked breakdown by gender and region to show who is in this group.
From a number to a disclosure
What separates a figure from a disclosure.
Basic
We had 1,240 employees at year-end.
Better
We had 1,240 employees at year-end, split into 720 women and 520 men across Europe, the Americas and Asia-Pacific.
Best
We had 1,240 employees at 31 December 2025, counted as headcount at period end; 720 were women and 520 were men, with 680 in Europe, 340 in the Americas and 220 in Asia-Pacific, and the rise from 1,180 last year mainly reflected the opening of a new site and higher seasonal demand.
Real reports where this topic is disclosed. The confidence label shows how closely each match maps to GRI 2-7 — these are report practice, not exact disclosure examples.
| Company | Sector · Country | Year | Match | Page | Report | Assurance | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Aena S.M.E., S.A. | Air Transportation — Airport Services · Spain | 2025 | Partial | p. 222 →p. 304 →p. 212 → | Sustainability report – Non-financial information statement Aena 2025 → | BSI | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evidence in Aena S.M.E., S.A.’s reportWhat the report shows Aena S.M.E., S.A.'s 2025 sustainability report provides detailed data on employees by contract type and gender, showing a total workforce of 11,053 with 4,222 females and 6,831 males (p.213). The report also includes employee distribution by gender, age, region, and professional category for Spain and the United Kingdom (p.291), as well as figures on permanent, temporary, and part-time employees by gender and region for 2024 and 2025 (p.292). However, the report lacks clear narrative or methodological explanations for these data points, and several expected disclosures are not found or remain unclear.
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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Firstsource Solutions Limited | Professional Services · India | 2025 | Partial | p. 101 →p. 224 →p. 116 → | ESG Report FY 2024-25 → | BSI | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evidence in Firstsource Solutions Limited’s reportWhat the report shows Firstsource Solutions Limited’s ESG Report FY 2024-25 provides detailed headcount data by age group and management level, showing numbers of permanent employees across categories such as top, middle, junior, and non-management on pages 124 and 125. The report also includes gender distribution within employee categories on page 90, with specific figures for male, female, and others. However, there is no clear evidence on methodology or narrative explanations for these data points, and several expected narrative items are not found or remain unclear 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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Taiwan Cooperative Financial Holding Co., Ltd. | Banks / Diverse Financials / Insurance · Taiwan | 2024 | Partial | p. 45 →p. 116 →p. 127 → | 2024 ESG Report → | Deloitte | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evidence in Taiwan Cooperative Financial Holding Co., Ltd.’s reportWhat the report shows Taiwan Cooperative Financial Holding Co., Ltd.'s 2024 ESG Report provides detailed gender and diversity statistics for employees from 2022 to 2024, including percentages of total employees by gender (p.175) and specific numbers of male and female employees in senior management and management roles (p.176). The report also includes data on new hires and employee transfers or promotions by gender for 2022 to 2024 (p.177). However, the report lacks clear narrative or methodological explanations for these figures, and several expected narrative items related to diversity disclosure are not found or unclear 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
A group HR report shows 420 people on the payroll at year-end, but the payroll team also has 35 agency workers and 18 contractors on site. The draft note currently mixes all three groups together in one table.How should you decide which people to include in the employee figures, and what extra detail needs to sit alongside the numbers?
Model answer. Use the organisation’s own method consistently and make clear what the counts cover. If the figures are based on people on the payroll, keep that scope separate from agency workers and contractors, then explain the counting basis and any assumptions so readers can understand the totals, the gender split, and the regional split.
Why this matters. Keep the scope of the workforce count clear, and explain the method used to build the figures.
A business has 260 permanent staff, 90 temporary staff, 40 people on zero-hours arrangements, 120 full-time staff and 170 part-time staff. The regional team has only prepared a single overall headcount and says the split by gender can be added later if time allows.What should you check before sign-off for this disclosure?
Model answer. The disclosure needs a total for each employment group that applies, plus a breakdown of each group by gender and by region. You should not leave out any of the groupings that are relevant to the workforce profile, and the presentation should make it clear how the totals relate to the sub-totals.
Why this matters. Report the workforce in the required slices, not just as one overall number.
The HR system records 310 employees at the end of the year, but the sustainability team has used an average monthly figure of 298 for the narrative. The draft note does not say which approach was used for the employee tables.What needs to be clarified so the reader understands the figures correctly?
Model answer. State the counting basis plainly, including whether the numbers are taken at the period end, averaged across the year, or built another way. If the tables use one approach and the narrative uses another, that difference should be explained so the figures are not mistaken for the same type of measure.
Why this matters. Tell readers how the numbers were compiled, especially the timing basis.
Employee numbers fell from 540 last year to 470 this year after a site closure, while a new shared-service centre added 60 staff in another region. The draft only shows the current-year totals and gives no explanation for the movement.What should the preparer add to help users understand the change in the workforce figures?
Model answer. Add context that explains the main reasons for the movement in employee numbers during the year and compared with the prior year. The explanation should help the reader understand why the totals changed, rather than leaving the shift unexplained.
Why this matters. When the workforce changes materially, explain the main drivers behind the movement.
Analyse this disclosure across real reports
See how companies actually report GRI 2-7 — 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.
Related & explore
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Questions this page answers
How do I prepare a GRI 2-7 Employees disclosure?
Fix the reporting boundary first, then work through the datapoints in the preparation table: define what counts as an employee, choose the counting basis and timing, gather the headcount records for every entity in scope, and build the gender, region and employment-type splits before you draft. The step-by-step sequence is in the preparation section. ↑ section
What employee data do I need to collect for GRI 2-7?
You need the total workforce plus breakdowns by gender and by region, and the same splits for each employment category the disclosure recognises — permanent and temporary contracts, full-time and part-time staff, and any non-guaranteed-hours arrangements. The preparation table lists each datapoint with what to capture, an evidence hint and a suggested owner. ↑ section
How should I define the reporting boundary for employee data?
Decide which legal entities and operations are in scope and whether that boundary matches your financial reporting boundary or a custom sustainability one, then state which entities are included or excluded and why. The workbook's prep & scoping sheet has an A/B boundary block to record this. ↑ section
Should I report GRI 2-7 using headcount, FTE, period-end or average figures?
Choose one consistent basis and state it: a simple person count or an FTE approach, and whether the figures are at the reporting-period end or an average across the period. Keep the same basis across periods so the numbers stay comparable, and note the choice alongside the data. ↑ section
How do I split employees by gender, region and employment type?
Capture each headcount once, then break it down consistently by gender, by region and by employment category so every subtotal reconciles back to the total. The illustrative example shows the same total presented across each breakdown. ↑ section
How should I report the different employment categories (permanent and temporary contracts, full-time and part-time staff)?
Report each employment category separately and apply the same gender and region splits to each, using definitions you can apply consistently. Document any category that is not used or not material — for example non-guaranteed-hours work — so the omission is explained rather than silent. ↑ section
Who in the organisation should provide, check and approve GRI 2-7 data?
Employee data usually comes from HR or the HRIS/payroll system, is consolidated by the sustainability or reporting team, and is checked by the data owner before sign-off. The preparation table names a suggested owning function for each datapoint so accountability is explicit. ↑ section
What evidence do I need for assurance or pre-audit review of GRI 2-7?
An assurer will trace each figure back to source — typically HRIS or payroll extracts, the headcount reconciliation and your scope and boundary notes. The assurance-readiness section lists the evidence pack to keep on file and the claims an assurer commonly probes. ↑ section
How can I use the GRI 2-7 workbook to collect data and build an evidence pack?
The Prep & Assurance workbook gives you a datapoints sheet to fill in (with per-datapoint risk and evidence-to-check), an evidence-pack sheet, a prep & scoping sheet for the boundary, and a readiness dashboard that flags what is still missing. Download it from the Download Centre. ↑ section
What checks should I run before publishing GRI 2-7?
Confirm every total and subtotal reconciles, the gender and region splits sum to the headcount, the counting basis and boundary are stated, and any major change is explained. The workbook's readiness dashboard turns these into a Yes/No checklist with a single READY indicator. ↑ section
How should I explain major changes in employee numbers during the reporting period?
Set out the reason for any material swing — acquisitions, divestments, restructuring or seasonal effects — and note any restatement of prior-year figures. The draft-output section gives narrative starters for explaining fluctuations alongside the data. ↑ section
What are the most common mistakes when reporting GRI 2-7?
Frequent pitfalls include mixing headcount and FTE without saying so, splits that do not reconcile to the total, an unstated or shifting reporting boundary, and unexplained year-on-year movements. The assurance-readiness section lists the gaps to check for. ↑ section
More questions this page can help with
- What does a good GRI 2-7 disclosure example look like?
- What is the difference between employees and non-employee workers in GRI reporting?
- How can GRI 2-7 support ESRS / CSRD workforce reporting?
- What should I include in the GRI content index for GRI 2-7?
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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.
