Utilities must move from reactive, siloed operations to a centralized wildfire management model. By integrating real-time risk modeling with a continuous improvement framework, utilities can better anticipate threats, prioritize infrastructure hardening, and reduce the likelihood of catastrophic ignitions.
Learn how utilities can transition to a centralized, data-driven wildfire mitigation model to improve grid resiliency and manage compounding climate risks.
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Standard metrics like SAIDI and SAIFI measure grid reliability under normal conditions but fail to capture the catastrophic, non-linear nature of wildfire events. Because they focus on outage duration and frequency rather than predictive risk, they do not account for the potential for cascading failures during extreme weather.
The biggest hurdle is organizational inertia caused by siloed departments, such as vegetation management and grid engineering, working in isolation. Bridging these gaps requires a unified governance structure where data is shared across teams and KPIs are aligned toward a single, organization-wide goal of wildfire risk reduction.
The PDCA (Plan-Do-Check-Act) cycle allows utilities to treat wildfire mitigation as an iterative, data-driven process. By continuously checking the effectiveness of hardening measures against real-world performance and acting to refine strategies, utilities can ensure their investments remain effective despite changing climate and weather patterns.
Utilities should shift from age-based replacement models to risk-based investment strategies. This involves overlaying wildfire hazard maps with grid asset data to identify high-consequence segments, allowing resources to be allocated toward infrastructure that presents the highest risk of ignition during extreme weather.
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