Founded in 1949 as a technical trading company, Vanderlande grew into a global player in automated logistics systems. With solutions for airport baggage handling, warehouse automation and parcel logistics, Vanderlande supports customers such as Amsterdam Airport Schiphol, Albert Heijn and DHL. During Data Expo 2025, Sander will provide valuable insights into how to set up and deploy a modern data platform in a complex, international organization.
Data-driven work is not new
Like many other organizations, Vanderlande has been working data-driven for years. That is not a recent development. The big difference from five years ago? Data is now connected much more broadly and intelligently - across applications. "Data used to be analyzed mainly within the boundaries of a single system, such as ERP, CRM or ticketing. Reports often remained silo-based," Kerstens says.
About 10 years ago, Vanderlande was already taking steps to bundle data from key applications into a central data warehouse. "IT managed and defined the logic, which led to valuable but static insights. With the adoption of our data platform, that has changed. The focus is now on flexible, domain-centric collaboration and dynamic data models that work across applications. That makes data not only more accessible, but also much more powerful as a strategic tool," adds Kerstens.
Data that thinks ahead
Whereas five years ago it was mainly about insights from the "Big Five" such as ERP, HR and planning, the playing field is now much broader. Today, companies work with data from dozens of systems, sometimes as many as 50. That broadening requires a different approach. "Instead of one central data warehouse focused on fixed use cases such as financial reports or workforce management, we now work with a modular data platform. This allows us to switch faster, report more flexibly and answer ad hoc questions. Also outside the traditional frameworks," Kerstens said. And with the arrival of AI, Vanderlande is taking the next step.
Whereas before we only answered known questions, now we can also proactively generate insights based on patterns we didn't know ourselves yet. That's the real difference between then and now: data that doesn't just look back, but thinks ahead."
The realization that change is necessary
Moving from a traditional data warehouse to a modern data platform starts with one crucial insight: your current setup is no longer adequate. "Within Vanderlande, the ambition grew to become truly data-driven. Faster, smarter, and insight-driven. But our existing data warehouse could no longer keep up with those ambitions," Kerstens says. So how do you proceed?
Step 1: Realize that you need to change.
That realization prompted a strategic data initiative within the company.
Step 2: Design a vision as well as a route.
"What specifically does it mean to be a data-driven organization? How do you set up governance? What will be your operating model? What value do we want to deliver?" Those questions were central to the program that followed.
Step 3: From vision to practice.
Kerstens: "Then you have an impressive strategic program on paper. But eventually you have to start implementing. And then it really begins. Use-case by use-case the platform was built, and the strategic ambition became business as usual."
Learning by doing
"Over the past 4.5 years, we have found that some ideas turn out differently in practice than they were conceived on paper," Kerstens says. "At the time, for example, the data mesh philosophy was on the rise. That really captured our imagination. But, translating the philosophy into practice is a quest." He finds that very experience valuable. "We are now at the point where we dare to reconsider choices made back then. Things we held on to for a long time, we are letting go in the interest of scalability and practicality. And that's where simplicity and effectiveness come together."
A nice challenge
Building a modern data platform requires hefty investments: in people, cloud, licensing, governance and tooling. But how do you make that value tangible? "Investments in data are difficult to link to business results, and the lead time is also relatively long. Those are nice challenges," Kerstens says. "Strategic programs last an average of a year with us. After that, something has to become business-as-usual. But in that time so much can happen, how do you keep the data program relevant, and how do you keep stakeholders involved and enthusiastic?"
Two tracks, long term
So why does such a journey take a long time? Because it's basically two development paths running in parallel. On the one hand, you work on the platform itself - the basic functions. "For example, we have added Natural Language Processing (NLP)-based functionality to the platform. This allows users to interact with data products in plain language. That suddenly makes the platform much more widely accessible," Kerstens explains.
At the same time, you unlock more data sources step by step. Kerstens: "In the beginning you don't have anything yet. So you choose five applications that are strategically important, for example, for supply chain planning or financial consolidation. That will keep you busy for the first two years, with fifteen to twenty applications. Only after that can you focus on new areas, such as learning analytics or sales forecasting."
And then there is the reality of constant change. "We're acquiring new applications at the same rate we're unlocking the old ones," Kerstens says. "Then another ESG tool comes along, or a company acquisition brings 25 new apps. It's never finished."
A never-ending journey
What is cutting edge today may be obsolete tomorrow. Vanderlande also experiences this reality on its data journey. "Four years ago, we weren't doing AI at all," Kerstens says. "AIOps felt like something from another world. By now it is an integral part of what we do. You're constantly learning to adjust."
You build something and a year later you're already phasing it out. Kill your darlings, because the world changes at lightning speed."
That speed requires agility. "We have learned to distinguish between what is core and what is not. The core must be robust and reliable. But around it, you want to stay flexible, so you can move quickly with it. Think analysis techniques, AI models or visualization tools. That's the dynamic part."
At the same time, security, privacy and compliance are becoming increasingly important and complex. The organization is also growing with that. It really is a never-ending journey. "We now have a solid, future-proof foundation in place - something we will reap the benefits of within Vanderlande for a long time to come. A wonderful result that we have achieved together," Kerstens concludes.
Discover at Data Expo how simplicity became key in Vanderlande's journey to a powerful enterprise data platform. Sander Kerstens, Director Data & Analytics, will speak on Thursday, September 11, from 11:45 a.m. to 12:15 p.m. in lecture hall 3. Be there and order your free tickets here.
