De Goudse
Making roof collapse risk measurable
A collapsing roof can endanger people, damage property and bring business operations to a standstill. The problem was that this risk was difficult to measure, while roofs were rarely insured. De Goudse needed a reliable way to assess that risk and make it visible enough to support insurance and prevention decisions.
How might we measure the risk of roof collapse and present it clearly enough to support better insurance and prevention decisions?
Inform
When risk is difficult to measure
Insurance depends on measurable risk. Without reliable data, insurers cannot determine which buildings can be covered or assess the likelihood of future damage. Because roofs were rarely insured, there had been little reason to invest in measuring their risk of collapse. De Goudse needed a way to calculate that risk within a given period and communicate the outcome clearly to employees, customers and other stakeholders. A reliable assessment could help identify suitable customers for roof insurance and alert building owners when preventative action might be needed.
Analyse
Turning roof data into a risk assessment
We combined LiDAR technology with a semi-public database of roof measurements and other relevant information. LiDAR made it possible to analyse the shape and depth of a roof to the nearest centimetre. Using this data, the model assessed whether the incline of a roof could affect its structural integrity over time. Alongside the model, we designed an application that presented the most important risk information clearly and made the outcome easier to use in practice.
Activate
Testing the model against a real collapse
We tested the model retrospectively on a De Goudse customer whose uninsured roof had collapsed. The test indicated that the risk could have been identified earlier, potentially enabling preventative action and avoiding considerable costs. The final application brought the model and its data together in a usable interface. It created a foundation for assessing potential roof-insurance customers and informing building owners when their roof showed an elevated risk of collapse.
Results
- Predictive roof collapse model validated against historical data
- Structural integrity analysed to the nearest centimetre
- New roof insurance proposition made possible
“I don't think there's an industry that can benefit as much from all technology has to offer.”
“At the end of the day, you're only going to insure what you can measure. If you don't have data, you're not going to insure it.”
“What Bit does best — after finding a concrete problem — is coming up with innovative solutions.”