Disclosure focus
The main focus is coverage: whether the organisation applies these reviews across its operations and employee groups, or only in certain parts of the business such as head office or flagship sites. A useful report will make clear the basis of the percentage, so readers can understand who was included and how complete the process is.
This LRA educational guidance supports disclosure preparation. For the exact requirements, always refer to the official GRI source.
Prepare
What to collect before drafting
Tick each field as the evidence lands. Owners are the teams that usually hold the source files.
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Gender
HR / People AnalyticsThe gender groups used for reporting, with the wording and categories taken from the organisation’s own employee records or self-identification fields.
Evidence HRIS employee profile fields, workforce reporting extract, and the internal category definitions used for the period.
Watch for Categories do not match the employee self-identification source, so the reported split cannot be reconciled to HR records.
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Employee grouping
HR / People AnalyticsThe employee groups the organisation uses to classify its workforce for this disclosure, using the same definitions applied in internal reporting.
Evidence HR policy or reporting dictionary, workforce segmentation report, and the source extract from HRIS or payroll.
Watch for The grouping definition is changed for disclosure and no longer matches the source system’s employee categories.
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Review coverage rate
HR / Performance ManagementThe share of all employees who had a regular performance and career discussion during the reporting period, calculated against the correct total employee population for the same period.
Evidence Performance review tracker, HRIS headcount extract, and the calculation showing reviewed employees divided by total employees.
Watch for The numerator is taken from the review tracker but the denominator comes from a different headcount basis or period, so the percentage is not comparable.
Before you start
- Have you fixed which people are in scope for this count — for example, by gender and staff group — before you start calculating anything?
- Are you using the same reporting period and headcount basis throughout, so the percentage is built from one consistent population?
- Can you trace the figure back to a source record, such as HR or appraisal records, rather than relying on memory or a manual estimate?
- Have you agreed what counts as a routine performance-and-development check in your organisation, so the same definition is applied to everyone?
- Will you separate the results by the people group labels you use internally, so the final number can be checked and explained clearly?
How to prepare it
Request the data
Request the review coverage data from HR / People Analytics
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
What share of our workforce had a routine performance-and-development conversation during the reporting period, split by gender and employee group?
Use your organisation’s own labels first, then map them to the reporting categories. For example, if you talk about appraisal, check-in, talent review, development conversation or one-to-one review internally, use those terms in the request and only translate them afterwards for reporting.
Weak request
Can you send the GRI 404-3 data showing the the evidence needed for GRI 404:GRI 404-3, split by gender and employee category?
Why it fails: It uses reporting-framework language first, which can force the owner to translate before they can recognise their own data. It also leaves out the population, source, counting basis, and the internal name of the review process, so the result may be hard to verify or reconcile.
Better request
Can you send the review coverage extract for [reporting period] from [system/file]? Please show, for each internal employee group and gender, how many people were in scope, how many had a routine performance/development conversation during the period, and the resulting percentage. Include the population rules, exclusions, counting method, and extract date. I’ll map your terms to the reporting categories after I receive it.
Formal email template
Subject: Data request for [reporting period] review coverage Hi [name/team], I’m preparing a sustainability reporting data pack and need your help with the review coverage figures for [reporting period]. Please send a table showing, for the employee groups you use internally, how many people were in scope and how many had a routine performance and development conversation during the period, split by gender and employee category. Please also include the percentage covered. Could you return the data with the following details: - the period covered - the employee population included and any exclusions - the internal name of the review process used - the source system or file - the counting method used - the date the extract was run - any notes on data quality, gaps, or assumptions Please use your own internal terms in the extract, and I will map them to the reporting categories afterwards. A possible LRA training template is attached for reference only; please adapt this to your organisation and check the official source before sign-off. Thanks, [preparer name]
Short Teams / Slack version
Hi [name/team] — could you send the [reporting period] review coverage data? I need the headcount in scope, the number who had a routine performance/development conversation, split by gender and employee group, plus the % covered. Please include the source system, population rules, and any exclusions. Use your internal terms and I’ll map them afterwards. Thanks.
Industry examples
Retail
Context. Store-based workforce with seasonal staff and a separate head office population.
Adapted request. Please send the review coverage data for [reporting period] for store colleagues and head office staff, split by gender and the employee groups you use internally. Include permanent and fixed-term staff only, exclude agency workers, and show how many people were in scope, how many had an appraisal or development check-in, and the percentage covered.
Example response. Store colleagues: women 1,200 in scope, 960 reviewed, 80.0%; men 800 in scope, 600 reviewed, 75.0%. Head office: women 300 in scope, 270 reviewed, 90.0%; men 200 in scope, 180 reviewed, 90.0%. Source: performance system export; extract date: 5 Jan 2027.
Manufacturing
Context. Shift-based workforce with production and engineering job families, plus office staff.
Adapted request. Please provide the [reporting period] review tracker from HRIS for production, engineering, and office teams. Show the number of employees in each internal group, split by gender, who had a formal performance and development discussion during the period, plus the percentage covered. Please note whether contractors and agency labour are excluded.
Example response. Production: women 150 in scope, 120 reviewed, 80.0%; men 850 in scope, 680 reviewed, 80.0%. Engineering: women 40 in scope, 36 reviewed, 90.0%; men 260 in scope, 234 reviewed, 90.0%. Office: women 90 in scope, 81 reviewed, 90.0%; men 110 in scope, 99 reviewed, 90.0%. Source: HRIS and appraisal tracker; exclusions: contractors and agency labour.
Draft your disclosure
Notes that turn data into a disclosure
LRA training templates — adapt them to your organisation, and check the official source before sign-off.
Method note
State how you defined the employee groups and the review measure, and note whether the percentage is based on headcount or another agreed workforce basis for the reporting period.
Context note
Explain that the figures show how widely formal development conversations were used across the workforce, and that differences between groups can point to uneven access or inconsistent practice.
Fluctuation statement
If the figures moved materially from the prior period, link the change to practical drivers such as changes in workforce mix, coverage of the review process, or timing of the assessment cycle.
Content index entry
GRI 404-3 Percentage of employees receiving regular performance and career development reviews — [location / page] / [notes]Download Centre
Preparation tools & forms
Download preparation tools for GRI 404-3 with free verified email access for 24 hours. Source-report links remain public.
Check
For each claim, check the evidence
We prepared the coverage figure by splitting the workforce into the relevant people groups we use internally, so the number reflects the categories applied in our reporting system rather than a broad headcount only.
Risk The assurer may test whether the grouping logic is consistent, whether any staff were placed in the wrong bucket, and whether the reported figure could be distorted by inconsistent category definitions across sites or systems.
Evidence to check Workforce classification policy or reporting instructions; HR system extracts showing the category fields used; mapping between internal people-group labels and the reported figure; reconciliation from source records to the published number; review notes showing any reclassifications or exceptions.
We built the disclosed figure from the employee set we treated as in scope for the period, using our normal employment records to decide who counted and avoiding double counting where someone moved between roles or locations.
Risk The assurer may probe whether the scope was applied consistently, whether joiners, leavers, transfers, part-time staff, or temporary workers were handled correctly, and whether the same person could have been counted more than once.
Evidence to check Population definition used for the period-end or average calculation; payroll/HR extracts; joiner-leaver and transfer logs; reconciliation between source population and the published figure; controls over duplicates and manual adjustments; sign-off showing the scope decision was reviewed.
For the review-rate figure, we used the records of employees who had a formal performance and development discussion during the year and checked the underlying logs before publication to confirm the count was complete and correctly calculated.
Risk The assurer may test whether the review records are complete, whether the timing window was applied correctly, whether the numerator and denominator were built from the same employee base, and whether the percentage was calculated accurately.
Evidence to check Performance review tracker or HR system reports; evidence of the review cycle dates used; employee population used as the denominator; calculation workbook showing the percentage formula; sample review records or manager attestations; management review and approval evidence; checks for missing, duplicate, or late-recorded reviews.
The reporting boundary used for this disclosure is documented.
Risk Coverage exclusions or late scope changes are not evidenced.
Evidence to check Boundary memo, entity or site list, and sign-off record.
Evidence pack to prepare
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.
Where drafts go wrong
Mistakes to avoid and where judgement is needed
The left column is what preparers get wrong while collecting; the right column is where you will have to make and explain a judgement.
Mistakes to avoid
- Wrong ownerThe data request goes to HR alone when the review records sit with line managers, payroll, or local business leads, so the team never gets a complete source set.
- Framework language in the askPeople are asked for a GRI-style metric instead of the organisation’s own review-cycle terms, and they return the wrong extract or a partial one.
- Scope left vagueNo one states which parts of the business, worker groups, or locations are in scope, so different teams count different populations.
- Boundary not fixedThe collector does not say whether to include only current staff, leavers, or other worker groups, which leads to inconsistent inclusion and exclusion decisions.
- Wrong time basisThe team pulls records from the wrong review cycle or a different cut-off date, so the figures do not match the reporting period being used.
- Mixed counting basisHeadcount, full-time equivalent, and individual review counts are blended together, which makes the percentage impossible to reconcile.
- Source labels lostThe original file names, field names, or system tags are stripped out during consolidation, so nobody can trace each number back to its source.
- Groups merged too earlyGender and employee group breakdowns are combined before checking the source data, which hides gaps that should have been kept separate.
- Evidence trail missingThe team keeps the final spreadsheet but not the supporting extracts, date stamps, or reviewer sign-off, so the calculation cannot be checked later.
Judgement needed
- Acquisition and disposal cut-offSet a clear cut-off for joining or leaving teams during the period, apply it consistently to the headcount used in the percentage, and explain any business changes that affect the comparison.
- Different local review cyclesWhere countries or business units use different review calendars or naming conventions, map them to one internal rule for what counts as a regular review and disclose that rule.
- People on the boundary of the employee poolDecide up front whether to include workers who are on leave, probation, fixed-term assignment, or otherwise partly active in the period, then explain the inclusion rule used.
- Part-year service and timing basisChoose whether the measure is based on the position at period end or on everyone employed at any point in the period, use that basis consistently, and state it clearly.
- System records versus manual checksIf the review status comes from HR records, manager logs, or sampled checks rather than a full count, say so and explain any estimation or reconciliation used.
- Rounding and percentage presentationRound the result using one consistent method, make sure the rounded figure still reflects the underlying count, and note the rounding approach if it could affect interpretation.
- Privacy-driven groupingWhen small teams or locations could identify individuals, combine categories to protect privacy, and explain any grouping so readers understand the level of detail shown.
- Mixed employee categoriesIf your workforce includes different internal categories, define which ones sit inside the total for this measure and disclose any exclusions or separate treatment.
Examples
How it reads on the page
Synthetic, written by LRA — not from a company report, not text from any standard.
During the year, we completed formal performance-and-development conversations for 1,260 of our 1,400 employees, equivalent to 90% of the workforce.
- By gender, 92% of women and 88% of men had a review.
- By job level, the figures were 94% for senior leaders, 91% for managers and 89% for other staff.
This example shows how to describe coverage of regular review conversations using a simple narrative, while splitting the result by gender and by employee level. The figures are internally consistent and illustrative only.
We carried out annual development reviews for 735 of our 900 people, which is 82% overall.
- By gender, 84% of women and 80% of men were covered.
- By employee group, 90% of supervisors, 83% of skilled operatives and 75% of office staff received a review.
This example demonstrates a second way to present the same disclosure, using different sector language and a different employee grouping. The numbers are made up for training purposes and remain mathematically consistent.
Quality ladder
- Basic
We reported that 78% of our employees had a regular performance and career development review during the period.
- Better
We reported that 78% of our employees had a regular performance and career development review during the period, split by gender and employee group.
- Best
We reported that 78% of our employees had a regular performance and career development review during the period, covering all staff and split by gender and employee group; the figure was unchanged from last year because our review cycle and coverage stayed steady.
Check your understanding
Scenarios to work through
A people team has headcount records for the year and a review tracker showing which staff had a scheduled performance-and-development conversation during the reporting period. Some workers joined late in the year, and a few were on long leave, so the team is unsure whether to count them in the total.
A business has separate employee groups: permanent staff, fixed-term staff, and a small number of interns. The HR system can show review completion for each group, but the team is unsure whether the disclosure should be split by gender and employee category or presented only as one overall figure.
At year-end, the HR team finds that some managers held annual review meetings, while others used mid-year check-ins and informal coaching notes. They want to count all of these as the same thing because each employee had some form of development discussion.
A preparer has calculated that 84 out of 120 employees had a regular review during the year, which gives 70%. The same dataset shows 50 of 60 women and 34 of 60 men received reviews, but the team is unsure whether the subgroup figures need to align with the overall total.
Real reports
How 3 companies report it
Examples of full and partial reporting practice. These are evidence-led reviews, not exact disclosure templates to copy.
Re Sustainability Limited
Exact
Grupo Cibest S.A.
Partial
Thai Beverage Public Company Limited
Partial| Field | Re Sustainability Limited | Grupo Cibest S.A. | Thai Beverage Public Company Limited |
|---|---|---|---|
| Gender | Not found | Not found | Not found |
| Employee grouping | Not found | Not found | Not found |
| Review coverage rate | Not found | Not found | Not found |
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Advice, not assurance
Framework references
Relevant GRI requirements and related disclosures
GRI
GRI 404-3
within GRI 404: Training and Education
Related & explore
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FAQ
Questions this page answers
Start with the plain-language explainer, then work through the step-by-step preparation section, the datapoints to prepare, and the draft-output section. The page is designed to help you turn source data into a draft narrative, a content-index line, and supporting visuals.
The page highlights three datapoints to prepare: gender, employee grouping, and review coverage rate. Use those as the core inputs when you are gathering data for the disclosure.
Use the page’s step-by-step preparation guidance and the employee grouping datapoint to decide which workforce groups are included in your dataset. Keep the scope consistent across the data table, narrative, and evidence pack.
The page is useful for a sustainability/ESG manager, HR or data owner, and assurance reviewer, so ownership should sit with the person who can gather the source data and maintain the evidence pack. The workbook and assurance section are there to support that handover and review.
The page includes an evidence pack with five items and four assurance claims to verify, each with a claim, risk, and evidence angle. Use those to build a file that shows how the figures were prepared and checked.
The page lists common reporting gaps and mistakes, so it is a good check against missing scope, weak evidence, or unclear methodology. Review those before finalising the draft so the narrative, data table, and supporting documents line up.
The Download Centre includes a Prep & Assurance workbook in .xlsx format, which is meant to support preparation and assurance readiness. Use it alongside the page’s step-by-step guidance, evidence pack, and draft-output section.
The page includes synthetic illustrative example disclosures, including a quantitative table, to show how the disclosure can be presented. Treat these as examples only and use them to shape your own draft structure and wording.
The draft-output section gives visualisation ideas, narrative starters, and a GRI content-index line. Use those outputs to convert your prepared data into a first draft that is easy to review and update.
The page notes ESRS S1 (Own Workforce) as the closest correspondence, so the data may be reusable across frameworks. That does not mean the reporting requirements are identical, so check the other framework separately before relying on the same dataset.
More questions this page can help with