In just over a year, the EU Pay Transparency Directive will mandate the adoption of pay transparency processes and reporting for companies with over 100 employees in the EU.
In preparation, organisations across the EU are grappling with a fundamental question: how to identify potential areas of concern that need to be addressed in advance of the legislation coming into force. The answer lies in a critical component of pay transparency implementation, job groupings.
Job groupings are the organisational equivalent of creating a detailed map before embarking on a complex journey. Properly structured job groupings provide the essential framework for meaningful pay transparency. They serve as the foundation upon which organisations can build equitable reward structures, identify potential pay gaps, and demonstrate compliance with the new Directive.
As Job groupings can be identified from a job architecture, for those organisations with a job architecture in place, they will have the ability to easily identify job groupings and will find themselves at a significant advantage when the Directive comes into force. Not only will these groupings help highlight any pay inequalities that need to be addressed, but they will also provide a structured framework for explaining pay differences based on objective criteria – a key requirement under the new legislation.
In this long-form article, we'll explore what the Directive says about job groupings and what this means for organisations. We will also talk about the different ways of developing job groupings. Finally, we’ll outline how RoleMapper is leveraging machine learning to help organisations with the formation of job groupings and ultimately with compliance with pay transparency legislation.
To comply with the right for employees to know the criteria being used for determining pay and what comparable employees are paid, as well as the equal pay reporting requirements, the EU Directive requires jobs to be grouped into “Categories of Worker”.
The Directive uses the term “categories of worker” to describe job groupings.
The Directive defines ‘category of workers’ as:
"Workers performing the same work or work of equal value grouped in a non-arbitrary manner based on the non-discriminatory and objective gender-neutral criteria”
This means that employees have the right to request, and receive in writing, information on their individual pay level and the average pay levels, broken down by sex, for categories of workers performing the same work as them or work of equal value to theirs.
Although the Directive refers to workers, it is important to consider this as being about jobs and not people. Therefore, we will be referring to job groupings and not worker groupings.
Fundamentally, employees have a right to request information about pay levels for groups of workers who perform what is deemed to be the same work, similar work or work of equal value as them. This means that employees can ask which job grouping they are in and receive information about it. If employers have not grouped jobs in understandable and explainable ways, employees can challenge whether they are in the correct grouping.
Therefore, in advance of the Directive’s implementation, organisations need to ensure they have an up-to-date, well-structured job architecture in place. From this, job groupings can be determined to show which jobs are equal in terms of work or equal value.
To form a comprehensive picture, at RoleMapper, we advise organisations to use their job architecture to build up their job groupings in three ways:
First, identify jobs of equal work.
Grouping jobs together of equal work involves identifying jobs where the same work is being done. These are usually jobs with the same job title and/or the same job description. For example, two HR Business Partner jobs might face off to different parts of the organisation, but the job content of their roles is essentially the same, as are the job titles and job descriptions. These groupings could exist as job families in some organisations.
Grouping jobs together doing similar work involves identifying jobs that are doing similar work at a similar level or jobs with similar characteristics. Organisations need to understand which jobs are similar both in terms of the work but also in terms of one or more of the factors that make up the value of a job, i.e. skill, effort, responsibility and working conditions. These are the objective job evaluation criteria outlined stated in the Directive
Finally, identify jobs of equal value.
A job grouping with jobs of equal value would include all roles where the value, as determined by objective criteria (skills, effort, responsibility, and working conditions), is equal.
Whereas jobs in the previous category may be similar in only one factor, jobs of equal value are similar when summing up all the factors. If an organisation uses a structured job evaluation process, a way of assessing whether jobs are of equal value would be whether the scores at the end of the process are similar or equal.
To illustrate, this diagram shows the output of a job evaluation process on three roles.
The jobs have different scores in the four factors, but the total value is the same. They are therefore of equal value.
If organisations don’t currently use a structured job evaluation process, they will need to ensure that there is some way of assessing the total value of jobs to determine whether they are of equal value.
What this means is that organisations will need to have the ability to look at the value of their jobs across the whole organisation. There will need to be a way of finding jobs that on the surface may have no similarities at all, but could actually be deemed to be of equal value.
In some high profile (and high cost to the organisation) recent court cases, examples of different jobs which have been ruled by the courts to be of equal value include:
These examples show that a wide range of jobs can be categorised at the same level in terms of value and therefore pay.
In the previous section, we discussed different ways to form job groupings. The reason for identifying these groupings is to see if there are any pay anomalies within the groupings that need to be addressed.
The reality of the EU Directive is that employees can request to see the pay level of other employees whose jobs are at the same level of value. So organisations need to have a way of easily grouping jobs of equal value to address any pay anomalies in advance of the legislation.
However, for many organisations, there are some key obstacles:
Many organisations think they can rely on job titles as a mechanism to identify jobs of equal value. Whilst this can be a good starting point, there are usually issues with the state of job titling across organisations that make this approach problematic:
Inconsistent job titles: For many organisations, job titles are a bit of a mess. With no central framework for job titles, it can be challenging to easily group jobs together in this way.
An example there might be two roles called Data Scientist and Data Engineer, which, despite the different job titles, are very similar in terms of job content. If these roles sit in separate areas of the organisation, their similarity may not be immediately apparent, and they could end up in different job groupings.
Another example of two seemingly different jobs involving similar work might be a Project Manager role and a Change Manager role. Despite the different job titles, the job content could actually show many similarities.
Same job title, different job: For those organisations that do have a structured job title framework, it is often the case that this is not consistently applied across the organisation, so it is very likely that anomalies exist.
There is often not a great deal of governance around job titling, which means that local job titles will not match the standard job title. For example, we hear a lot of examples where managers have used the job profile title to get the appropriate level (and salary) for a role, but then created a job that is fundamentally different to the original intended job title.
Same job title, different value of work: The next challenge is where jobs have the same title, but a fundamentally different level of work is involved. For example, take a Project Manager in an Engineering team vs a Project Manager in Finance. It is highly likely there will be a difference in the skill levels and responsibility involved in projects managing scrum teams or technology development, compared to the skills and experience required to project manage Finance projects.
These skills and experience would be reflected in availability and price in the marketplace. If relying on job title alone, these jobs would appear to be of equal value. But if both roles were evaluated using a structured process, the difference in their value would become apparent.
Therefore, relying on job titles to identify job groupings will not be enough to comply with the requirements of the Directive. It could cause issues with accuracy of reporting and open an organisation up to risk.
Although job descriptions aren’t explicitly mentioned in the Directive, they are the fundamental building blocks for job evaluation and the creation of job groupings.
Job descriptions outline the key responsibilities and requirements of a role, which is used to determine the objective criteria (skills, level of responsibility, effort and working conditions) for job evaluation. They are therefore a critical input for determining job groupings.
However, there are also fundamental issues with job descriptions in organisations:
Lack of consistency - Often, there is no standardised process, format, or central repository for job descriptions. Different teams create their versions, leading to duplication and inconsistency. For example, multiple versions of a Project Manager job description may exist, each with varied content despite describing the same role.
No overall governance or audit trail - There’s also often a lack of centralised oversight for the job description process. Changes are typically made through endless email chains with tracked changes, making it nearly impossible to decipher who made what changes and when. This chaotic approach leads to confusion, inefficiency and inadequate records.
Out of date - Job descriptions frequently fail to reflect the current skills required for a role. They may be outdated or written by someone unfamiliar with the role. An up-to-date job description is essential for accurately determining which job groupings a role should be in.
There are some key ways that technology can be leveraged to help organisations identify job groupings.
We are using automated text extraction tools to pull structured information from unstructured data sources, like PDFs or scanned job descriptions provided by clients. These tools extract relevant fields (e.g. job titles, job description, requirements, etc) and convert them into a structured format for further processing.
This means that all the job descriptions for an organisation can be pulled together in a central location and structured in a consistent format. This is a fundamental starting point for determining which jobs are of equal value.
Machine learning can then be used to automatically cluster and classify roles based on historical data to build an intelligent role taxonomy. This helps with grouping similar roles and ensuring consistent use of terms across different job descriptions.
Often, job content is static bits of data housed on a spreadsheet. It is challenging to manually analyse this to find similarities in job roles.
We are leveraging advancements in AI and Natural Language Processing to process large data sets from across an organisation and rapidly identify similarities and commonalities in job roles. This enables the creation of groupings which might not be apparent on the surface.
This technology enables organisations to look across their whole organisation to rapidly identify:
These can then form the focus of further analysis from a pay point of view to see if there are disparities that need to be urgently addressed.
As companies prepare to meet the European Pay Transparency Directive's requirements for pay reporting and disclosure, those with a job architecture in place and well-defined job groupings will find themselves at a significant advantage. Not only do these groupings facilitate more accurate pay gap analysis, but they also provide a structured framework for explaining pay differences based on objective criteria – a key requirement under the new legislation.
However, for many organisations, identifying job groupings can be a challenging process because of factors such as a chaotic job titling structure and inconsistent, ungoverned and out-of-date job descriptions.
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