{"id":15099,"date":"2026-06-04T17:26:37","date_gmt":"2026-06-04T15:26:37","guid":{"rendered":"https:\/\/actongroup.com\/les-referentiels-rh-a-lepreuve-de-la-transparence-salariale\/"},"modified":"2026-07-02T14:39:37","modified_gmt":"2026-07-02T12:39:37","slug":"hr-reference-frameworks-put-to-the-test-by-pay-transparency","status":"publish","type":"post","link":"https:\/\/actongroup.com\/en\/hr-reference-frameworks-put-to-the-test-by-pay-transparency\/","title":{"rendered":"HR Reference Frameworks Under the Pressure of Pay Transparency"},"content":{"rendered":"\n

When an organization has to explain a pay disparity, it generally assumes its data tells the same story across the entire company. That assumption is more fragile than it appears.<\/strong><\/p>\n\n\n\n

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Imagine two HR teams analyzing the same compensation data at the same time using systems considered highly reliable. Yet they reach different conclusions. Nothing dramatic: a few percentage points of difference, a slightly different employee population, or responsibility levels classified differently across their respective HRIS platforms.<\/p>\n\n\n\n

At first glance, these discrepancies look like ordinary reporting or data consolidation issues. Yet they sometimes persist even after the data has been validated, calculations verified, and methodologies fully documented.<\/p>\n\n\n\n

In these situations, the problem is not the data itself. It is the way the data is being compared.<\/p>\n\n\n\n

The European Pay Transparency Directive did not create this issue, but it makes it far more visible. Comparing jobs of equal value, documenting pay disparities, and explaining differences between comparable employee groups all require organizations to examine whether the reference frameworks that structure their data remain internally consistent.<\/p>\n\n\n\n

At first sight, this may seem like a compliance issue. In reality, it raises a much deeper question: how can organizations maintain reliable comparisons when job classifications, organizational structures, and business systems evolve faster than the reference frameworks designed to connect them?<\/p>\n\n\n\n

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WHAT HRIS PLATFORMS DO NOT GUARANTEE<\/strong><\/h2>\n\n\n\n
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Human Resource Information Systems were originally designed to support operational processes: running payroll, administering employment contracts, meeting statutory reporting requirements, and tracking workforce data. Over time, each business unit developed its own grades, job classifications, and organizational taxonomies tailored to its operational needs. In that environment, data is considered reliable as long as it enables business processes to function correctly.<\/p>\n\n\n\n

A hire date or full-time equivalent (FTE) percentage fits this model relatively well because its definition rarely changes. Job classifications, grades, and job families operate differently. Their meaning exists only within a reference framework that itself evolves as the organization changes.<\/p>\n\n\n\n

That framework changes through acquisitions, reorganizations, the emergence of new roles, and evolving management structures. A job title may therefore remain exactly the same even though the actual responsibilities have changed significantly. Conversely, similar roles may belong to different classification systems across business units. In other words, data remains internally consistent within its original system until the moment different reference frameworks must be reconciled.<\/p>\n\n\n\n

The challenge, therefore, is not simply producing reliable data. It is preserving the rules that allow the data to be interpreted consistently over time. Yet according to an Esteval study published in 2026, only 13.5% of organizations using an HRIS have digitized job or grade reference frameworks.1<\/sup> 2<\/sup><\/p>\n\n\n\n

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MAPPING DEBT STARTS LONG BEFORE PAY GAP ANALYSIS<\/strong><\/h2>\n\n\n\n
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Comparing employees performing work of equal value first requires demonstrating what actually makes those positions comparable. That demonstration depends on a network of mappings: between grades and responsibilities, between local classifications and enterprise-wide frameworks, and between successive versions of the organization's operating model.<\/p>\n\n\n\n

Following a reorganization, a grade's scope of responsibility may change without that change ever being formally documented. After an acquisition, a local classification system may be retained without ever being fully aligned with the corporate framework. At the same time, variable compensation may be included in an HR analysis while being excluded from a Finance calculation. Taken individually, each inconsistency is generally manageable. Together, however, they gradually create what can be described as mapping debt: a collection of undocumented relationships that the organization must reconstruct every time it attempts to reconcile, compare, or consolidate its data.<\/p>\n\n\n\n

A common reference framework is far more than a standardized job title dictionary. Standardizing the title \"Business Development Manager\" across all subsidiaries accomplishes very little if the relationships between the underlying concepts have never been defined or modeled. Two positions may share the same title while representing very different levels of responsibility. Conversely, roles with different titles may contribute at the same organizational level. More than a dictionary, a reference framework serves as a system of analytical continuity. It should describe what a role represents at a given point in time, track how it evolves, and explain how a level translates from one framework or classification system to another.<\/p>\n\n\n\n

Before measuring a pay gap, organizations must first be able to demonstrate that the elements being compared are genuinely comparable.<\/p>\n\n\n\n

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GOVERNING REFERENCE FRAMEWORKS IS AS MUCH AN ORGANIZATIONAL ISSUE AS A TECHNICAL ONE<\/strong><\/h2>\n\n\n\n
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This raises a frequently overlooked issue: ownership. Within multi-entity organizations, the boundary between what is standardized centrally and what individual business units may adapt locally is rarely defined with precision. Corporate reference frameworks therefore coexist with inherited local classifications, often without explicit rules governing what may be modified, by whom, under what conditions, or through which approval process.<\/p>\n\n\n\n

The absence of clearly assigned ownership becomes particularly problematic as organizations evolve. Roles change and organizational structures shift. The challenge is no longer simply defining an appropriate reference framework at a given point in time, but managing how that framework evolves.<\/p>\n\n\n\n

Data professionals refer to this concept as \"Slowly Changing Dimensions<\/em>\". Behind the technical terminology lies a very practical concern: ensuring that an analysis produced today will still carry the same meaning when reviewed two years later, even after the organization has undergone multiple transformations. Maintaining historical versions provides part of the answer, but it is insufficient without governance capable of managing changes in a controlled manner.<\/p>\n\n\n\n

Such governance necessarily involves multiple stakeholders. Regardless of the architectural approach chosen, whether maintaining version-controlled reference frameworks or consolidating data across subsidiaries, the IT organization must be involved. Once reference frameworks affect HRIS structures, data flows, or consolidation processes, responsibility can no longer rest solely with HR. This is precisely where many organizations struggle, not because they lack commitment, but because no one has been formally assigned responsibility for managing what connects business requirements with technical implementation.<\/p>\n\n\n\n

The consequences can be significant. Updating a reference framework during a compensation review cycle may break comparability with previous years. Leaving it unchanged after a major reorganization may produce results that appear consistent but are misleading in practice. According to an ANDRH survey, only 22% of organizations preparing for the directive are currently updating their job reference frameworks. Its Vice President, Laurence Breton-Kueny, estimates that building a sufficiently robust job classification system typically takes two years.3 4<\/sup><\/p>\n\n\n\n

That timeline reflects a deeper issue: many of the categories organizations rely on every day were never designed to remain consistent through continuous organizational change. The real challenge is therefore not simply defining a reference framework, but determining when and how it should evolve, while collectively assuming responsibility for its governance over time.<\/p>\n\n\n\n

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WHEN DEFINITIONS DRIFT, ANALYSIS ERODES<\/strong><\/strong><\/h2>\n\n\n\n
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Organizations that establish a common reference framework typically experience one immediate benefit: analyses that previously depended on extensive manual adjustments become far easier to perform. Work that once required weeks of reconstructing comparable employee populations can be repeated without relying exclusively on individuals who happen to \"know\" the historical data. Persistent differences between HR and Finance views of payroll costs gradually diminish as a common layer of definitions and historical tracking becomes established.<\/p>\n\n\n\n

These benefits initially improve traditional reporting and analytics. Their impact expands as organizations adopt more advanced uses of their workforce data. As processes become standardized, analyses multiply, and decision-making increasingly relies on analytical models, stable definitions become essential for producing reliable results.<\/p>\n\n\n\n

This is especially true when those results are generated by predictive models. Applied to HR data, such models rely on an assumption that is rarely stated explicitly: that the variables they use retain sufficiently stable meanings over time. Yet that stability cannot be taken for granted. Job families may be redefined, classification rules revised, or categories reinterpreted as organizations evolve.<\/p>\n\n\n\n

An internal mobility indicator calculated using job populations that changed between reporting periods may therefore signal a trend that does not actually exist, or fail to detect one that does. The models continue producing results. What becomes uncertain is the ability to interpret those results correctly. An observed variation may reflect an organizational change just as easily as a silent shift in the categories used to measure it.<\/p>\n\n\n\n

This type of weakness rarely appears as an obvious error. Instead, it develops gradually. As definitions evolve without consistent historical tracking or governance, the ability of systems to produce comparable analyses over time steadily deteriorates. Metrics continue to be calculated, dashboards remain available, but confidence in what they actually measure gradually diminishes.<\/p>\n\n\n\n

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WHAT HR DATA WILL NOW HAVE TO PROVE<\/strong><\/h2>\n\n\n\n
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By requiring organizations to justify pay disparities and compare jobs of equal value, the Pay Transparency Directive places unprecedented analytical demands on classification systems that were rarely designed for this purpose. This work must necessarily be incremental and cannot be delegated entirely to technology, since it requires maintaining categories whose meaning evolves alongside the organization itself.<\/p>\n\n\n\n

Yet the challenge now extends well beyond regulatory compliance. HR systems no longer exist solely to administer the workforce or produce reports. They are increasingly becoming the infrastructure through which organizations seek to understand their own evolution: changing skill needs, compensation trajectories, career mobility, pay practices, and forward-looking workforce analyses.<\/p>\n\n\n\n

In this context, the issue is no longer simply having more data. It is preserving, over time, the consistency of the categories that give that data meaning. When definitions evolve faster than the mechanisms designed to document and preserve them, confidence in the resulting analyses inevitably begins to erode.<\/p>\n\n\n\n

This is precisely where ACT-ON DATA's teams support HR leaders. Beyond meeting regulatory requirements, the objective is often more fundamental: ensuring that the decisions made today can still be understood, explained, and meaningfully compared tomorrow using the same analytical reference points.<\/p>\n\n\n\n

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Have a project? Contact us<\/strong><\/a> to discuss it\u2026<\/p>\n\n\n\n

Find out more about our customer projects!<\/a><\/strong><\/p>\n\n\n\n

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[1] Directive (UE) 2023\/970<\/a> du Parlement europ\u00e9en et du Conseil du 10 mai 2023.<\/p>\n\n\n\n

[2] Esteval, \u00ab Transparence salariale : 7,2 % d\u2019\u00e9cart inexpliqu\u00e9 \u00e0 poste \u00e9gal F\/H<\/a> \u00bb, \u00e9tude 2026.<\/p>\n\n\n\n

[3] ANDRH, \u00ab Transparence des r\u00e9mun\u00e9rations : les DRH alertent sur les risques d\u2019une transposition pr\u00e9cipit\u00e9e<\/a>\u00bb, enqu\u00eate janvier-f\u00e9vrier 2026.<\/p>\n\n\n\n

[4] La Gazette France, \u00ab Transparence salariale : un chantier RH \u00e0 haut risque social<\/a> \u00bb, conf\u00e9rence ANDRH, f\u00e9vrier 2026.<\/a><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

When an organization has to explain a pay disparity, it generally assumes its data tells […]<\/p>\n","protected":false},"author":5,"featured_media":14621,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[1836],"tags":[1920,1923,4877,1921],"fonction":[2514,2513,2509],"fonction-belgium":[],"fonction-germany":[],"fonction-switzerland":[],"secteur":[],"secteur-belgium":[],"secteur-germany":[],"secteur-switzerland":[],"class_list":["post-15099","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-new-perspective","tag-act-on-group-en","tag-data-en","tag-referentiels-rh","tag-rh-en","fonction-cfo","fonction-gm","fonction-hrd"],"acf":[],"yoast_head":"\nHR Frameworks Under Pressure of Pay Transparency - ACT-ON GROUP<\/title>\n<meta name=\"description\" content=\"HR 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