Bridging the data gap: towards predictive maintenance cultures in public infrastructure

Municipal utilities manage extensive underground networks that are difficult to monitor and maintain. Predictive maintenance offers a way to improve reliability, but many organisations face a gap between available data and actionable insight. This briefing describes how the City of Sugar Land strengthened decision making across water, wastewater and stormwater systems by combining consequence-based risk analysis with practical predictive approaches. A three-level data-readiness maturity model was used to guide improvement, and a new consequence-driven framework was developed to prioritise stormwater assets where condition data are limited. The framework applied probabilistic degradation modelling and structured staff workshops to translate operational knowledge into consistent risk scores. The case demonstrates that organisational culture and governance can be critical enabling factors, particularly where predictive methods depend on staff knowledge, consistent data ownership, and cross-functional validation. The programme was delivered in 3 months using existing staff and open-source geographic information system tools, demonstrating that meaningful progress is possible without major expenditure. Treating data as an infrastructure asset enables more transparent, risk-informed decisions and provides a sustainable foundation for municipal utility systems.