In this article, we'll look at job evaluation for EU pay transparency, the different methods organisations can use and how to decide on the best approach.
With the EU Pay Transparency Directive due to become law across EU member states in 2026, job evaluation is a key process that enables organisations to systematically value roles based on objective criteria.
While job evaluation has been used for years, particularly in the public sector, it has fallen out of favour in the private sector, with many organisations having moved to a more flexible approach to jobs and pay.
The EU Pay Transparency Directive talks about the need to have pay structures in place based on job evaluation and classification systems that use 'objective, gender-neutral criteria'.
This EU legislation has now brought evaluation back into focus in the private sector, as it provides a systematic, objective framework to assess the relative worth of different jobs within an organisation.
Job evaluation and classification systems should ensure that any pay differences are based on legitimate job-related factors rather than bias or discrimination, helping organisations comply with pay transparency legislation and promote workplace fairness.
There are several different methods used by organisations to evaluate and classify jobs. They range from very structured processes based on quantitative data to more informal, less structured systems that utilise qualitative data.
This is one of the more simplified approaches to job evaluation, where positions are directly assigned to predetermined grades or salary levels based on a quick comparison with benchmark positions.
Rather than conducting detailed point-factor evaluations, job descriptions are compared to established role profiles and then placed in the most appropriate grade.
The benefit is that ranking is faster and less resource-intensive than other job evaluation methods, making it particularly useful for smaller organisations or when evaluating new positions.
However, it can be less precise and more subjective than comprehensive evaluation methods, which could lead to concerns about accuracy and fairness.
Job classification is a slightly more structured approach than ranking. It involves systematically categorising positions into grades based on predefined criteria.
Unlike job slotting's quick comparison approach, classification uses a more detailed analysis of job characteristics against established grade definitions.
The benefits of this approach include consistency across similar roles, the development of a clear organisational structure, and standardised pay ranges. This systematic approach makes it more defensible than job slotting.
However, it can be time-consuming to implement, and the potential rigidity in grade definition can make it difficult to accommodate unique roles. It’s also a system that can become outdated if classifications aren't regularly reviewed.
This is a quantitative job evaluation method that evaluates jobs by comparing them against factors or criteria (such as skill, effort, responsibility, and working conditions). Unlike job classification or slotting, it involves evaluating jobs on a factor-by-factor basis.
The main benefits of this approach are that it is highly analytical and that this more detailed job comparison approach better supports pay equity and transparency. This method is more effective than the ones previously described for unique jobs, as each role is considered individually.
The potential downsides to this approach are that it can be complex and time-consuming and that it requires significant expertise to implement. It can be expensive to maintain and may face internal resistance due to its complexity.
The point factor method is an evolution of the factor comparison method. It builds on factor comparison by assigning numerical points to factors. Each factor (such as skill, effort, responsibility) is broken down into levels, with specific points allocated to each level. A questionnaire is then developed so that points can be assigned to each factor for a job role.
These points are then totalled into a score, which is then matched against the levelling structure to determine the job level. Each level has a predefined score range, so the jobs are automatically sorted into levels via their total score.
The point factor method allows organisations to adjust the relationship between points and pay more easily. The structured nature of this method provides greater objectivity and consistency in evaluations. However, as with the factor comparison method, it still requires the investment of significant time in developing and maintaining the point system and factor definitions.
Documentation provided by the EU and International Labour Office suggest that the more analytical methods have the potential to be less discriminatory due to their systematic and complex approach, and therefore more appropriate for job evaluation when it comes to gender equality.
However, many organisations in the private sector have been moving away from very structured job evaluation approaches - they don’t always want to work with a rigid and complex point methodology and so opt for ranking/levelling or classification instead.
Indeed, the Deloitte/Empsight 2024 global job architecture practices survey report showed that 84% of companies use job evaluation, but only 18% of companies use point-factor job evaluation.
The EU Pay Transparency Directive talks about pay structures based on job evaluation and classification systems that use 'objective, gender-neutral criteria'.
However, the steer from the EU in terms of pay transparency is that a structured job evaluation is recommended, which means that many companies with employees in the EU may need to assess what they are doing in light of the EU Directive.
The challenge for organisations is to determine a job evaluation approach that meets the requirements of the legislation whilst still retaining the flexibility they require.
They also need to ensure that the criteria used in the job evaluation approach that they adopt uses factors or criteria that are in line with the recommendations in the EU Directive.
The main concerns around job evaluation are that it is time-consuming and that there are ways of ‘gaming’ the system. It tries to reduce jobs to a mathematical formula for comparison, but, as with all data, the inputs need to be accurate for the outputs to be correct.
Unconscious bias can creep in at any point, so it’s important to remember that, although it tries to be systematic and consistent, it is not scientific. Job evaluation works best when representatives from across the organisation are involved so that there is general agreement and buy-in.
It is also necessary to ensure that bias isn’t accidentally included when choosing the level and type of skills to include. The directive specifically states that ‘relevant soft skills shall not be undervalued.’ While the level of some skills can be determined by the length of time it took to acquire them, others need to be evaluated more holistically.
While the EU doesn’t prescribe a specific job evaluation method, it does give a strong steer towards a more analytical approach in its working document.
“The analytical job evaluation methods, being systematic and complex, have the potential of being less discriminatory than non-analytical methods and they are therefore considered to be most appropriate for job evaluation in a gender equality context.”
Methods of job evaluation for EU pay transparency should, therefore, be guided by this advice and the need to have a robust process in place.
On-demand webinar: Join RoleMapper CEO Sara Hill and Vicky Peakman, Director, Fair Pay Partners, as they talk through the EU Directive requirements, drill into the operational implications, and set out practical steps for preparation.
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