Success Stories
First Understand, Then Automate
- By Nidaros
“Robotic process automation only truly works when it’s embedded technically, organizationally, and in terms of data,” says Herzo van der Wal, project leader and senior data manager at the Data Management Center of Rijkswaterstaat (RWS). He is responsible for delivering, managing, and providing access to spatial and geographic information.
From infrastructure and water management to environmental and safety data — this information is centrally managed by RWS and made available to citizens and other government bodies.
Since 2007, the European INSPIRE Directive has required member states to make geographical data accessible in a uniform way. The goal: one integrated European data network where information can be exchanged seamlessly between countries. In practice, this means that RWS must supply datasets every month that meet strict European specifications.
Bottleneck
The theory was clear, but daily reality was more complex. Knowledge about the process mainly existed in the heads of employees. At the same time, manual steps, email exchanges, and after-the-fact corrections hindered the timely delivery of datasets. In short: RWS struggled to meet its monthly INSPIRE obligations.
Could Robotic Process Automation (RPA) provide a solution? To find out, RWS reached out to Nidaros.
“We were tasked with mapping the process clearly and creating a dedicated working environment for it,” explains Harry van der Werk, business analyst at Nidaros. “At the same time, we wanted to deliver a Proof of Concept (PoC) to test whether RWS could achieve the goals of the INSPIRE program with the help of RPA.”
For the project, one specific theme was chosen: waterway markers, such as the locations of buoys and traffic signs on Dutch waterways.
Approach
Before you automate, you must understand the process thoroughly. By asking the right questions to Herzo van der Wal and his team, implicit knowledge was made explicit.
What steps are taken? Where are the bottlenecks? Which software is used for the translation layers? Existing RWS documentation was also used. The analysis ultimately resulted in a detailed process description, including a working environment in which everything is documented.
“The analysis gave RWS many new insights,” Harry recalls. “Some process improvements were even implemented immediately. Then we looked at which steps could be automated and created a PoC around them.”
Result
The Proof of Concept has now been successfully developed and delivered.
The result: a robot that retrieves and checks geo-data daily.
Does the data meet INSPIRE requirements? Then it moves forward. If not, Herzo is notified immediately.
A shift from fixing afterward to preventing upfront.
The impact goes further. The solution is scalable and applicable to all INSPIRE themes within RWS.
And while the directive requires monthly delivery, datasets can now be supplied daily.
As a result, for example, ship captains continuously benefit from up-to-date navigation information.
Essence
Back to Herzo’s opening words: what does it truly mean that automation must be embedded technically, organizationally, and data-wise?
A flawlessly working robot is only the beginning. Without a deep understanding of processes and clearly defined responsibilities, automation remains a collection of isolated scripts. That’s why Nidaros delivered not just technology, but also business support — active monitoring to ensure that processes continue running smoothly. Moreover, data quality remains crucial: poor input data will always produce poor output, no matter how advanced your robot is. The real difference lies not in what you automate, but in how you do it.
