Breaking Ground in Workforce Analyitcs

Dura Vermeer is a 171-year-old Dutch family-owned construction company with annual revenue of nearly €3 billion. The company is active in the development, construction, renovation, and maintenance of residential and commercial buildings(including iconic architectural works); the construction, replacement, and maintenance of infrastructure (including roads, civil structures, railways, ports and industrial facilities); and technical installations. It is one of the top five players in the Dutch construction industry. 

For an organization with such a long history and this scale of operations, it is noteworthy that Dura Vermeer has created a dedicated role focused on HR data, innovation, automation, and analytics. This demonstrates the company’s strong commitment to its people and to employee development. Steven Hölscher was appointed to fulfill this role, and one of the first priorities he put on the agenda was making better use of workforce data. 

The challenge

Where did the ‘Why’ go?

With around 3,800 employees, Dura Vermeer lacked no workforce data. Headcount, absence, gender diversity are all tracked and reported, but given the static nature of Power BI dashboards, it’s difficult to break down, impossible to explore without technical support, and never fast enough to answer a business question in the room it was asked.

Power BI did what it was designed to do, with KPI dashboards on topics like sick-related absence, headcount, or gender diversity all accurate and well-built. But that was precisely the limit. The moment anyone needed to go deeper—to understand why a number looked the way it did, how it varied across divisions, what was driving it—HR hit a wall.

When we looked into our gender diversity, for example, Power BI would give us a number, say, 24.7%, but it couldn’t help us break that down easily across divisions, function groups, or specific segments. That deep-dive capability is what helps us answer the why. And once you know the why, you can start connecting it to remedies and solutions. That’s the exploratory side of people analytics.

Getting to that level of breakdown meant manual work, dependency on internal BI specialists with other priorities, and an HR function that could not move at the pace the business needed.

And that mattered, because the most important thing is being able to respond to a business question. Our business has a people question it needs to resolve. We want to be agile, look at different data pieces, see what’s happening, see why it’s happening, and use that in a potential solution. For that, you need an analytics tool that is easy to use, fast, and adaptable.

The decision

Choosing the right starting point

Rather than going straight to vendors, the Dura Vermeer team took the time to build a proper view of what they needed. As for the new solution’s feature requirements, they came directly from the people who would use the platform day to day: HR Business Partners, HR Managers, and HR Advisors.

They also brought together a sounding board of around ten people from across the business, including Finance, sought out peer references, and had conversations with similar organisations that had already chosen and implemented Crunchr.

When it came to what mattered most, Steven was precise.

The platform had to be system agnostic—”not tied into any HR core system. You don’t want something which only works with Workday or SAP.”

It had to be proven—”something which has been proven to work out of the box. We didn’t want to reinvent the wheel, or take a system which isn’t meant for people analytics and try to make that work.”

And above all, it had to be easy to use—”by everyone, from the people analytics expert right through to the line manager who works with a big team and needs to understand what’s happening within it.

That last point carries the most weight, given that Steven has spent nearly a decade building analytics tools and implementations prior to joining the Dura Vermeer team.

He knew what happens when platforms are built for specialists and handed to everyone else. The goal was a tool that HR and the wider business could pick up and use without needing to be data experts first.

Implementation

How a small team drives fast implementation

Implementation kicked off in October 2025, right before Dura Vermeer’s peak operational season, with reward cycles, performance reviews, and organizational changes running from November to February. On top of it all, a team member was assigned elsewhere mid-project. And yet, both Dura Vermeer and Crunchr adapted and kept the project going.

The rollout was treated as a minimum viable product. A sounding board of HR stakeholders was involved from the start—not just informed, but shaping decisions on what got built and in what order.

When the platform was roughly 90% functional, it opened to the broader HR audience, with the clear message that this was a starting point, and that fine-tuning would happen together.

Steven’s team are, by his own description, data people, with flair for complexity. And yet the release was kept deliberately simple.

Me and the rest of my team at Dura Vermeer are really data-oriented—we like a lot of data, the more complex, the better. But when you take the broader business along, you have to adapt to two things. First, make sure it answers the business questions. Second, keep it simple. If a chart isn’t directly understandable to end users, and if it doesn’t answer a business question, people will just be lost. That was really important in how we approached the release.

Early wins

The room erupted

In February, Dura Vermeer held its first major HR community session. Before the official demo, the team ran a short teaser—Ask Crunchr AI, the ability to type a plain-language question and get an answer directly from the data.

The room reacted immediately.

That’s what sparked everyone’s imagination: ‘I can just type a question and Crunchr answers it.’ That’s where you see that making things very simple really helps. Different audiences respond to different features.

For Steven’s team, the Stories feature landed—the ability to build clear, readable workforce narratives without design support or technical overhead. For the broader HR community, the natural language interface was the unlock. Same platform, different entry points—and both useful on day one.

The more significant shift is quieter, though. It is what has changed in the ordinary conversations—the informal check-ins where a Business Partner asks a people question and used to expect to wait days for an answer.

The conversation has changed because you have something on the table which you both can work with, which everyone has access to, and which is easy to use in a discussion. Any graph, any drill-down, we can now do it ourselves. The only limit is our own capabilities.

Before, HR was a data retrieval service. A question came in, data was collected, something assembled manually, an answer came back—hopefully before the decision had already been made on gut feel. Now the question and the answer live in the same room.

Instead of saying ‘this is going to take time’, or ‘we don’t have the data’, or ‘it’s complex’—we can now have a much better discussion on the people data.

On the data side, the foundations are already expanding. HR core data is in. eNPS is connected—not technically complex, but meaningful as a first. And the roadmap is now being shaped as much by the business as by the analytics team.

That’s actually what we’re now hearing from the business: ‘Now that we can do this, can we connect our recruitment data? Can we connect our L&D or recruitment data?’ That appetite is already there.

A look ahead

What comes next

As of April 2026, the rollout is still in its early weeks, but Steven’s view on where this needs to go is clear.

The platform should support our business on all people-related questions—quickly getting numbers together to answer them. What I’d really like is for questions that are currently answered by gut instinct—because our business partners genuinely know the business well—to be easily connected to data. Day-to-day use of data in HR needs to become far more mainstream.

The longer-term ambition goes further. Steven talks about workforce shaping, a tactical and strategic picture built on skills, sentiment and capacity data, connected to real predictions about how the organisation needs to evolve.

What I’d really like to see in three to four years is a genuine shift to workforce shaping — a tactical and strategic view on the workforce, and how to shape it based on skills, sentiments and capacities, all connected to data.

He is honest about the distance between here and there.

First, you need to get the basics right.

Coming from someone with his background, that carries weight. Dura Vermeer is doing the deliberate work of building a foundation, with clean data, structured metrics, a growing culture inside HR of reaching for the data before reaching for instinct. The business is already asking for more and the conversations are already different.

Ready to lay the foundation?

We’re happy to take a look together. Explore how teams like Dura Vermeer are building the foundation for people analytics—and see whether Crunchr fits where your organisation is today.