How the EU Pay Transparency Directive Changes Compensation Decision Making

What is the EU Pay Transparency Directive?

Formally called Directive (EU) 2023/970, the purpose of the EU Pay Transparency Directive (EUPTD) is to “strengthen the application of the principle of equal pay for equal work or work of equal value between men and women …”. That summary already makes an important point: The purpose of the EUPTD is not necessarily to improve compensation decision making, but to address the gender pay gap. The means to achieve that, however, is increased pay transparency, which ultimately forces companies to be more open, deliberate, and analytical when it comes to employee pay.

Who should care about the EUPTD? 

Obviously, organizations with employees in the EU should care about the EUPTD, but employers in the U.S. and Canada should at least pay attention. The regulatory pressures may be different here (and depending on your state, more strict or more lenient), but the trend toward pay transparency is global. Pay transparency makes employees more aware of the fairness of their pay relative to colleagues and employees doing similar work in other organizations.

What are the requirements of the EUPTD?

The key requirements in the EUPTD make a lot of sense if you approach them from the perspective of a large regulatory body that tries to address the gender pay gap. 

First, there are requirements that force employers to share pay ranges in job postings and no longer hamper employees’ ability to share their pay information with each other. The idea being: If employees have more information, they are more able to assess the fairness of their pay. 

Second, there are requirements to report gender pay gaps to the government and share them with labor unions or works councils. There are also requirements to share pay information by gender—upon employee request—for the employees’ job category. The point here: Reporting and awareness alone can drive change even in the absence of direct regulations that forces employers to manage or reduce gaps. 

With that said, and third, the EU does set a threshold for an acceptable gender pay gap at 5%. Specifically, if the reports shared with the government and the labor union indicate that the gender pay gap is larger than 5%, organizations must analyze the data to see if legitimate business reasons explain enough of it to bring it below that threshold. If that fails, they have to make pay adjustments. 

This summarizes the key provisions: To address the gender pay gap, employers in the EU have to share pay ranges as well as details about their pay policies, file gender pay gap reports, conduct statistical analyses to compute an unadjusted/adjusted gender pay gap, and provide targeted pay adjustments if the adjusted pay gap is larger than 5%.

Preparing Your Business for the EUPTD

The Directive still needs to be transposed into national laws, and the deadline for that is June 7, 2026. At Syndio, we recommend to clients to not wait that long and start by analyzing their data now. Yes, the first reports are not due until June 2027 for the calendar year of 2026. However, this means that the year 2025 is in fact the last year when you can analyze and fix gender pay equity issues without involving the labor union. In addition: if you find gender pay gaps for 2026 in 2027 you have to also fix them retroactively for the whole year 2026.

Preparation is not just about analyzing your data and filing reports. Some clients are learning, for example, that their job architecture is not good enough to make pay comparisons for “work of equal value”. Clients with a global leveling or grading system that cuts across job functions have an advantage here, as do clients who already performed a point-based job evaluation. Importantly, regulators don’t favor a methodology! Though, they do require a job structure that helps you identify a group of jobs for comparison purposes that have the equivalent value based on characteristics such as skills required, working conditions, responsibilities, effort, and educational attainment.

Changing Your Compensation Decision Making

Beyond the mechanics of being prepared, most clients also understand that the EUPTD and pay transparency will drive a rather profound change when it comes to compensation decision making. This begins with pay negotiations. 

In the past, the employer was able to ask candidates what their historical pay used to be, and they were able to withhold information on their own pay ranges. The power of information was with the employer. By June 2026, the situation will be reversed in the EU in that employees have the right to know about the pay scale for their potential job with the new employer, and they don’t have to share information about their own pay. 

As a result, employers have to rethink starting pay negotiations—and as mentioned above—similar requirements exist in several regions in North America. Let’s add to that the potential for uncomfortable conversations with incumbent employees who learn that their pay falls below the pay range you share in job postings. Also, some employees might learn that the new hire they just trained makes more than they do.

Pay transparency requires a lot of communication and change management. Executives, managers, and employees must become more knowledgeable about compensation decision making. Recruiters and hiring managers need to be retrained on pay negotiations. Organizations have to review their pay policies and check whether they actually pay for the things they say they are paying for. Twenty years of analyzing pay data for hundreds of clients teaches me that many of the things we are telling our employees about pay (e.g., “we pay for performance”, “tenure doesn’t matter when it comes to pay”) turn out to be myths. 

The Impact of AI on Pay Transparency

The most profound change is created by the perfect storm that brings together regulations like the EUPTD, pay transparency, vast amounts of pay data, and AI. At Syndio, we have been riding that storm for a while and decided to tackle this head-on with our clients. Recruiters and compensation leaders today deal with multiple sources of data, including compensation survey data, external job offer data, internal job offer data, and internal incumbent pay data, to name a few. It will no longer be good enough to combine all these data sources “in your head” when making pay decisions. 

Yes, the human decision maker will still set the rules and remain in the loop when it comes to making the final pay decision. Yet, we AI-based algorithms will increasingly be used to compute the most effective pay given business priorities. For critical jobs, a pay offer might maximize the likelihood of a job acceptance. For jobs in labor markets that are quickly changing, the offer might put a bigger weight on recent pay offers or information from job postings. For jobs with existing internal staff relations issues, the offer might emphasize consistency with incumbent pay. 

AI can also provide algorithms that suggest the right job level and job family based on an analysis of the job description and required pay level. AI used this way can increase decision speed, consistency, and transparency while optimizing compensation budgets.

When talking about this to clients, I typically admit that this sounds like science fiction. However, the AI wave is coming, and we can either ride it or be swept away by it. Twenty years ago, it was hard to find the data for analytics-based compensation decision making. Ten years ago, we developed the analytics but didn’t have the tools to integrate the results into the hiring process. Now, AI brings it all together.

‍