Context
CD22 manages a 1,100 km road network in Côtes-d’Armor. Data was spread across tools and local know-how, making annual investments hard to justify and prioritize. Oxand helped centralize the pavement inventory, model aging and risk, and simulate scenarios to forecast multi-year budgets and reduce maintenance backlog exposure.
Our solution
- 01 Collected and consolidated pavement data via questionnaires and workshops
- 02 Built functional breakdown and tailored aging & risk models for road sections
- 03 Parameterised maintenance actions and cost curves, then loaded data into Simeo
- 04 Ran scenario simulations to compare end-of-period risk and define budget envelopes
What Oxand delivered
Objective risk-based prioritisation
Objective prioritisation through scenario comparison on risk levels
Secured multi-year investment planning
Predictive, multi-year view to secure €12M/year investment planning
Watch the story
Feedback from the Côtes d'Armor department and its deployment of Infrasim: The Département des Côtes d'Armor talks about its policy of managing pavements and engineering structures using the SIMEO predictive solution. With the support of Oxand's teams, the Département des Côtes d'Armor has built up an overall vision of its assets, and benefits from a solution to arbitrate and prioritize its investments according to ageing and usage. We spoke to Franck Bourdais, Director of Infrastructures, about his experience in managing his facilities. The same methodology is applied to building assets (schools, sports facilities, culture and services). The useful data approach is anchored in the operational and strategic processes of the Côtes d'Armor department. The Conseil Départemental des Côtes d'Armor has a substantial road infrastructure heritage, with 4,600km of roads, 900 structures and 40km of canal to monitor and maintain in order to ensure their operation.
Questions about this reference
What did the Côtes-d'Armor department set out to do?
To prioritise pavement maintenance and investment across a 1,100 km road perimeter on objective, risk-based criteria, where the data had been spread across separate tools and local know-how.
How was pavement condition modelled?
Pavement data was collected through questionnaires and workshops, a functional breakdown was built for road sections with ageing and risk models fitted to them, maintenance actions and cost curves were parameterised, and the whole was loaded into Simeo.
What do the scenario simulations compare?
The level of risk carried at the end of the period under each strategy, against the budget envelope each one requires — which is what turns a prioritisation debate into a comparison.
Does the same method apply beyond roads?
Yes. The department applies the same methodology to its building assets — schools, sports facilities, culture and services — so roads and buildings are read on one approach rather than two.
Who carries the subject at the department?
Franck Bourdais, Director of Infrastructures, who describes the department's experience of managing its pavements and engineering structures with the predictive solution.