The AI Act: postponed, not cancelled
Since late July 2026 the Digital Omnibus has been in force, pushing the deadline for high-risk AI systems from August 2026 to December 2027. This includes the systems HR relies on for recruitment, selection, performance reviews and other employment decisions. So, if you’ve set this aside over summer, you’ve just gained sixteen months.
With a clear structure, you don’t have to search for things yourself
In many models I come across, measures are scattered across the tables in which they were created. Total Revenue is in the Sales table, Customer Count is in the Customer table, and Avg Order Value is in the Orders table. At the time of creation, this makes perfect sense, but two months later nobody can remember where anything is.
“Off course this number is correct, just don’t ask me why”
Two reports on the same revenue, two different numbers. You open both and notice that one applies a filter the other does not know about. The filter does not live in the data model, but in a Power Query step halfway through the report…
Your contact procedure is in the work regulations. Now what?
Since 1 January 2026, every Belgian employer must include a structured contact procedure for sick employees in their work regulations. By this point, the following should already be in place: who makes contact, when it happens, how it is documented and how reintegration is followed up. With this, the easy part is already behind you. You must also be able to demonstrate that you are complying with your own procedure.
Your data model is the first thing a colleague sees
Open the Model View of a report you have not touched in a while, and you know straight away how much work is coming. Tables sit scattered across the canvas, relationship lines cross each other, and there’s no clear distinction between facts and dimensions. Tidying up, however, costs almost no time.
Ready for pay transparency? Your data probably isn’t.
The EU Pay Transparency Directive requires employers to be open about pay and objectively demonstrate that their pay policies are gender-neutral. Many organizations treat this as an HR or legal task. The real bottleneck sits elsewhere: in your data.
Nobody uses your beautiful dashboard?
You invest in a central data platform, build clean dashboards, and yet after a few months everyone reaches for their own Excel again. Sounds familiar? The problem is rarely technical, it’s a matter of business involvement.
Setting your filters again every morning?
Many Power BI users lose a few minutes every day to deal with the same problem: open the report and set everything up again. There is a simpler way, using a feature you likely already have but rarely use.
Different departments, different numbers?
Why do three departments report three different revenue figures? Fragmented reporting, and the separate definitions each department uses, causes more misery than solutions. How to fix it, you will read below.