Data readiness for the EUPTD with PayAnalytics

The EU Pay Transparency Directive (EUPTD) is just as much a data project as it is a compliance project. While preparing for compliance, many organizations discover that their employee and compensation data does not prove as clean, consistent, or complete as they would like. Job architectures have grown inconsistent or outdated, allowances get applied randomly, historical data is patchy and scattered across multiple systems, and some pay decisions live only in managers’ spreadsheets.

The good news? Organizations can comply without perfect data. What matters far more is approaching data readiness in a structured, transparent, and well-documented way.

Below we share pragmatic recommendations we see working well across organizations that prepare for the Directive.

We also recommend viewing our dedicated on-demand workshop to help kick-start your pay equity and transparency journey.

Prioritizing job architecture and leveling early

Of all the readiness topics, job architecture consistently has the highest impact – and the highest risk if ignored.

You do not need a perfect, hyper-granular job framework to comply. However, you do need three things in place:

• A defensible way to group work of equal value

• Clear criteria for job comparisons

• Definitions across geographies and functions

Organizations that handle this well tend to follow a few common principles: they stabilize job families and levels even if titles vary locally, they avoid over-engineering role descriptions, and they focus on comparability rather than customization.

This is also where many organizations choose to engage a consulting partner – not to redesign everything from scratch, but to accelerate leveling decisions, apply market-tested frameworks, and provide external defensibility if pay decisions are challenged later. beqom works with a range of consulting, legal, and software partners who specialize in exactly this. Visit our website to learn more.

Importantly, your job architecture forms the basis for defining categories of workers – a key requirement under the Directive. Refer to Getting ready for the EUPTD with PayAnalytics for information on this and other EUPTD best practice topics.

Considering the scope of compensation data

The EU Pay Transparency Directive defines pay broadly. For pay gap analysis and reporting, organizations must take into account total gross remuneration on an annual and hourly basis, covering:

• Base salary

• Variable pay (bonuses, incentives, commissions)

• Allowances (location, shift, mobility, on-call)

• Quantifiable benefits linked to remuneration

This scope often extends beyond what organizations centrally manage or consistently record today. In practice, variable pay, allowances, and benefits may be distributed across multiple systems, locally administered, or historically inconsistent.

Using a data snapshot and reference period

Data snapshot

The snapshot determines which employees fall into worker categories, as well as the gender composition of comparable roles and average compensation per category – both total and by gender.

Compensation reference date

This date typically falls at one of the following:

• End of calendar year (for example, 31 December 2025)

• End of a compensation round or payroll period close to the disclosure date

• End of the most recent completed performance review for variable compensation

At that date, compensation figures should reflect actual paid-out amounts where available, with contractual amounts as a backup. Employees who did not complete a full year should have their compensation annualized to enable like-for-like comparison.

In practice, most organizations define their employee population as of the snapshot date and measure compensation using the most recent reliable data available.

Employees in the snapshot with incomplete or missing data

In accordance with Article 7 of the Directive, employers must provide meaningful pay information upon request, including for new hires who are not covered by the snapshot-based calculations. For these cases, we recommend the following approach:

1. Use the employee's annual contractual compensation as the pay reference.

2. Apply the same job category or comparator group defined at the snapshot date.

3. Provide average pay levels and gender pay gap data for that category based on the snapshot gross paid compensation reference date.

4. Clearly state that the comparator figures derive from a snapshot taken before the employee's hire date, and that the employee's compensation measure differs from the comparator group in the snapshot.

This approach ensures that new hires receive meaningful information without requiring organizations to recalculate disclosures on a rolling basis.

Managing inconsistent FTE and hourly pay data

One common operational challenge under the EU Pay Transparency Directive involves achieving consistent comparability between employees paid on a full-time equivalent (FTE) basis and those paid hourly. Differences in working time arrangements, local payroll practices, and historical data quality often complicate the analysis.

Converting to a common reference

The most widely used approach converts compensation to an annualized FTE equivalent, using contracted hours as the primary reference point and standard full-time hours as defined per country or collective agreement. Note that full-time hours vary by employee location.

This enables comparability across full-time and part-time employees, aggregation at job category level, and consistent gender pay gap calculations.

Where FTE data is missing or unreliable, organizations should document any proxy assumptions applied – for instance, defaulting to 100% FTE and 40 hours for full-time contracts. Proxies should be treated as temporary. Replace them with exact data as part of ongoing data clean-up.

Separating base pay from time-driven pay elements

Overtime, shift premiums, and ad-hoc hourly supplements should be treated as separate pay components. Keeping them out of base pay comparisons avoids distorting results due to irregular working patterns.

Documenting your methodology

Consistency and documentation matter more than methodological sophistication. Organizations should define and record:

• Which pay elements are normalized to FTE

• Which elements are excluded from normalized comparisons

• How leave, absences, and unpaid time are treated

Consolidating employee compensation data

Organizations frequently face difficulties in assembling a complete and fully reliable view of total gross remuneration at the outset. One of the major challenges is consolidating data from across multiple systems. We generally see the following data sources in play:

• HRIS: holds contractual base salary, annual bonus targets (if applicable), and key objective factors such as job families, job levels, employment dates, and performance ratings.

• Payroll system(s): contain actual gross and net payments of salary, bonus, overtime, and certain allowances.

• Sales compensation systems: handle commission calculations and incentive payments; these may or may not already be included in the payroll system.

• Benefits administration systems: track pension contributions, health insurance values, and other benefits with monetary value.

• Equity platforms: manage equity grants, vesting schedules, and exercise data.

• Expense management systems: cover travel, meal, and car allowances, as well as other vouchers.

Bringing this data together should be treated as a full-scale project with a dedicated task force. See more details in Setting up a cross-functional data task force.

At this stage, two key issues come up:

• Different unique employee IDs used in systems – it might be a system ID in one and a Sofi number or email address in another.

• Inconsistent compensation element mapping – these elements may carry different naming conventions across local systems or live in entirely different systems depending on the country.

Addressing data gaps in compensation components

Where data gaps exist, best practice is to:

1. Use reliable and consistently available compensation data as the initial basis for analysis and disclosure.

2. Clearly document which pay components are included and which are excluded.

3. Record known data limitations, assumptions, and interim methodologies.

4. Define a structured plan to progressively incorporate additional pay elements as data quality improves.

The Directive does not require all compensation components to be fully mature from the first reporting cycle. However, it does require that methodologies are consistently applied, explainable, and documented.

Establishing a data improvement roadmap

Organizations are encouraged to treat compensation data readiness as an iterative process. Common roadmap actions include:

• Standardizing allowance definitions and eligibility criteria

• Centralizing variable pay outcomes and payout data

• Improving the valuation and tracking of benefits

• Strengthening integration between HR, payroll, and reward systems

This phased approach supports initial compliance while enabling gradual improvements in data completeness and analytical accuracy over time.

Setting up a cross-functional data task force

Pay transparency is not an HR-only initiative. Organizations that struggle most tend to treat it as a compliance checkbox owned by one team.

A better approach is to establish a small, empowered internal task force with clear ownership across HR / Rewards, Legal / Compliance, Data / HRIS, and employee relations or works council representatives (where relevant).

This group should agree on core definitions (pay, variable pay, allowances, job categories), prioritize data remediation topics, decide where interim solutions are acceptable, and own internal messaging and escalation paths. Crucially, the task force creates alignment before disclosure, avoiding last-minute disagreements when timelines are tight.

Going live with imperfect data

From a compliance and risk management perspective, proceeding with disclosures using incomplete but reliable data is generally preferable to delaying implementation due to unfinished data remediation.

Failure to meet disclosure or reporting obligations presents a higher compliance risk than publishing results based on a clearly defined scope, as long as:

• The scope of included compensation elements is explicitly stated

• Limitations are disclosed internally and, where relevant, externally

• There is evidence of an active remediation roadmap

An incomplete dataset does not invalidate compliance, provided the approach remains transparent and defensible.

Importing and configuring your dataset in PayAnalytics

The PayAnalytics data model is flexible and can accommodate any Excel file as long as it meets the requirements documented in Preparing your data and Uploading your data. Read these articles to find out more about data import and configuration in our application.

Data import in Employee Datasets

This is a tip message.

If you are on the Pay Equity & Transparency Enterprise license, you may use the data sync option from the Pay Transparency module within beqom Pay Suite to load your dataset into PayAnalytics. In this case, refer to the Data foundation section of the Pay Suite Help Center.

Note that you can still use the PayAnalytics UI data import. However, this dataset will not sync with or necessarily align with your pay transparency data, and the data fields – as well as results of a pay equity analysis – cannot be used in your pay transparency employee communications or statements.

Considerations and best practices for EUPTD

1. For the Main group field, select Category of Worker (CoW) as defined in your dataset. It is not possible to configure the CoW within the application based on your available data fields – this work needs to be done in the data preparation stage ahead of import.

   

   Category of Worker selected in the Employee ID and group section

2. For the Compensation main element, select Gross Annual Pay and disclose in a separate document which compensation elements are included or excluded.

3. For usage in the Employee pay transparency report, check Use additional compensation settings and choose the relevant elements to include, usually a form of base salary, variable, benefits, and hourly pay. Keep in mind that you cannot configure hourly pay from annual pay within the system; this needs to be done during data preparation before the import.

   

   Use additional compensation settings option in Compensation

4. If you have imported individual compensation elements but do not have total gross compensation in your dataset, PayAnalytics allows you to build a Compensation component aggregate by selecting the individual components to aggregate and providing a descriptive name. This field can then be used in the Compensation main element.

   

   Create component aggregate button in Compensation

5. If your compensation elements reflect actual pay and have not yet been annualized, PayAnalytics provides the Part-time employees feature to automatically scale your selected compensation to a full-time equivalent. This requires a part-time or FTE column in your dataset with values between 0 and 1. Note that the FTE hours basis must be consistent across all employees in the dataset.

   

   Part-time employees feature

6. For demographic variables, PayAnalytics offers two options, but for EUPTD purposes we recommend using only the First demographic variable and selecting Gender. From a regulatory perspective, Female and Male are the most commonly used gender values, though the platform also supports Nonbinary and Not reported.

   

   Gender as a First demographic variable

7. Preview your dataset to ensure completeness and click Save.

   

   Dataset preview and Save

Pay bands and benchmarking data

Pay bands and Compensation benchmarking data are commonly used in EUPTD pay gap reporting and employee pay transparency communications. These data points can be imported and configured separately from the employee dataset. They help evaluate an employee's position within their pay range and validate pay practices against the market.

Strategies for closing the pay gap

This is an note/information message.

We cover FTE annualization and part-time employee handling earlier in this article. This section focuses on the compliance rationale and configuration implications.

A critical distinction when preparing for the EU Pay Transparency Directive is separating the metric you report externally from the metric you use to fix pay gaps internally. Mixing up your compliance reporting strategy with your remediation strategy can create both budgeting and technical complications.

Here is how we translate this challenge into an actionable approach for your PayAnalytics configuration.

The EUPTD reporting reality: total compensation

For EUPTD compliance reporting, the definition of pay is extremely broad. To comply with the Directive, you are required to report on total compensation, which includes base salary plus any variable components, bonuses, and allowances.

However, generating raise suggestions directly from a fluctuating total compensation or actual pay figure becomes highly problematic because you cannot easily or permanently operationalize a raise on a variable, one-time bonus.

Why we recommend remediating on contractual pay

For your internal budget planning and remediation, or the "fixing" phase, we strongly advise running your analysis using contractual base pay. Base pay forms the foundation of your compensation structure and is typically where the most significant, systemic pay gaps reside. By fixing the base, you correct permanent structural inequities.

The FTE like-for-like requirement

Even when using contractual pay, you must be careful with part-time employees. The EUPTD strictly dictates that pay comparisons rely on a like-for-like basis to avoid penalizing part-time workers, who are disproportionately women.

Because the PayAnalytics regression models require full-time annualized compensation data to run an accurate comparison, any contractual pay that reflects part-time hours must be scaled up to a full-time equivalent.

How to configure this in the system:

• The data – ensure your file has a dedicated FTE column with values ranging from 0 (no work) to 1 (full-time).

• The setting – during data import, check the Automatically scale compensation components for part-time employees option in the Part-time employees section. Map your contractual base pay column to your FTE data field. The system will automatically convert part-time contractual pay into full-year equivalents for the analysis.

Consultant's action plan for the EUPTD

To satisfy both your practical remediation needs and your EUPTD reporting requirements, we recommend this two-step workflow:

Step 1 – Remediate the base

Upload your contractual base pay alongside your FTE column. Use the auto-scale feature to run your analysis and calculate your raise suggestions. Use the pro-rated raise output to allocate your salary increase budget.

Step 2 – Audit variable pay

Upload separate columns for base salary, variable pay/bonuses, and total compensation. After planning your base salary raises, run a secondary analysis on the total compensation column. This ensures that discretionary elements like bonuses are not unintentionally widening the gender pay gap before you generate your final regulatory reports.

Data foundations for pay transparency

Actual pay vs. annualized pay for EUPTD compliance

Clients frequently ask: "If the EU Directive requires reporting on actual pay, isn't it technically inaccurate or 'fake' to annualize a three-month salary into a twelve-month figure?" As a result, some organizations attempt to upload raw, partial-year pay and use time worked or tenure as an objective factor in the regression model to mathematically explain the difference.

We would advise against this approach. Here is how to turn the Directive's requirements into compliant, workable system configurations instead.

The strategic reality: like-for-like comparisons

While the Directive references actual pay levels, its fundamental requirement is that pay comparisons be made on a like-for-like basis. Comparing the raw actual pay of an employee who worked three months against one who worked twelve – or comparing part-time to full-time – artificially creates large, non-meaningful pay gaps. If you use raw, un-annualized pay, your unadjusted pay gaps and system graphs will be severely distorted. While adding time worked as an objective factor might technically explain the gap in statistical terms, it completely undermines transparency, the Directive's ultimate goal. When you eventually generate employee pay transparency reports, the raw data will appear highly inconsistent, prompting confusion and grievances from employees rather than providing clarity.

Actionable best practice: annualize the data

To ensure both legal compliance and statistical validity, annualizing the data to a full-time equivalent is the required standard for PayAnalytics models.

To implement this correctly and transparently, follow these steps:

1. Apply annualization selectively – you must be strategic about which pay components you annualize. While it is standard practice to annualize contractual base pay, exercise caution with variable pay, one-time bonuses, or specific benefits. Annualizing a one-time quarterly bonus across a full twelve months will inflate the employee's earning potential unrealistically and distort your compliance reporting.

2. Document your assumptions – in accordance with EUPTD best practices, ensure that your exact methodology for annualizing partial-year or part-time data is clearly documented in your internal compliance and works council files.

3. Drive transparency in employee statements – to address the concern that annualized numbers may feel "fake" to the employee, make it explicitly clear in the final reports that the figures are annualized for fair comparison purposes.