From 20,000 risk trees to data-driven priorities

The annual VTA inspection revealed that the number of risk trees significantly exceeded what the maintenance budget could handle. Although managers had been doing their best for years to set the right priorities, there was no objective method to explain to the council and residents why some trees needed immediate attention while others could wait.

The numbers were clear: 20.000 identified risk trees, but budget for only {count2}. Which half takes priority — and how do you explain that?0 identified risk trees, but budget for only 10.000. Which half takes priority — and how do you explain that?0. Which half takes priority — and how do you explain that?

With IDA's Smart Risk Prioritization module, the municipality got a clear picture of the actual risks in their tree inventory for the first time. Existing VTA data was enriched with a risk prioritization score that gave each tree one transparent risk score.

Each tree received a score based on: tree height and fall zone, location and surroundings, traffic density, potential consequential damage, and the probability that something would actually be hit if it failed.

Those risk scores proved to be a breakthrough. Instead of working from intuition, the municipality could align maintenance with the available budget. By setting a risk threshold, only trees that fit within the budget and delivered the greatest risk reduction were automatically selected.

From this selection, a complete project was created with just a few clicks, including a map view of the relevant locations. The green contractor seamlessly took over execution — in IDA, they could see exactly which trees needed treatment and what measure was required for each tree.

The effect of this approach was immediately noticeable. Where there used to be much discussion about priorities, there was now peace and trust thanks to the substantiated choices that IDA made visible.

The maintenance budget was fully utilized, risky situations were demonstrably addressed faster, and the municipality could clearly explain to the council and residents why certain streets received maintenance this year and others would follow next year.

After completion, the entire tree inventory was automatically up to date in the system — ready for the next cycle.