Executive Summary: Addressing Customers with the Highest Number of Outages

This session is covered under the First Quartile Consulting Confidentiality Agreement.

The discussion centered on how utilities are shifting from relying primarily on system averages (SAIDI/SAIFI) to more targeted, customer-based reliability metrics to identify and correct repeat outage exposure. While overall system performance may be acceptable, several participants acknowledged that there are “pockets” of customers experiencing repeated interruptions that are masked by averages. To address this, utilities are increasingly using CEIMI-based triggers to drive action.

Examples shared included using CEIMI 2 for tree-related causes to initiate vegetation follow-up and CEIMI 4 (all causes) to trigger reliability review, patrol, and corrective action. These triggers are used both in real time (e.g., multiple interruptions within a defined period) and through rolling 12-month analysis to identify worst-performing areas for focused maintenance and capital investment. The emphasis is on moving from reactive restoration to proactive correction of chronic problem locations.

A second major theme was the treatment of momentary interruptions. Utilities noted that while traditional reliability reporting focuses on sustained outages, customers experience repeated short-duration “blinks” as a significant service issue. Some organizations are leveraging AMI data to quantify interruptions under 30 seconds to better understand the customer impact, determine whether issues are isolated or feeder-based, and establish reasonable thresholds for action. The goal is not to eliminate protective device operations that are functioning as designed, but to define when repeated momentaries indicate an underlying issue that warrants field investigation.

Participants also emphasized the operational challenge of managing increasing data volumes. CEIMI reporting and device-path analysis can become highly manual as the year progresses. There is strong interest in automating analysis to reduce administrative burden and allow teams to focus resources on field execution.

Key Takeaways

• Customer-focused reliability metrics are driving decision-making. Utilities are using CEIMI triggers to identify repeat exposure rather than relying solely on system averages.

• Tiered response structures are common:

  • Real-time triggers (e.g., 2 interruptions in 24 hours, CEIMI 2 tree-related) prompt immediate patrol or quick corrective action.

  • Rolling 12-month thresholds (e.g., CEIMI 4 or 6+ interruptions) drive structured maintenance or capital programs.

• Cause-based thresholds improve prioritization. Tree-related repeat outages often have lower intervention triggers than all-cause repeat interruptions.

• Targeted mitigation strategies include:

  • Vegetation follow-up beyond cycle trimming

  • Animal guards and wildlife protection

  • Sectionalizing and additional protective devices

  • Reconfiguration to address overloads

  • Conductor and equipment replacement

  • Spacers and automation enhancements

  • Strategic undergrounding of limited spans where safety or chronic exposure justifies the investment

• Strategic undergrounding is being used selectively, primarily where safety concerns, restricted right-of-way access, or recurring line-down risk make overhead maintenance unsustainable.

• Customer density can distort rankings. Utilities are reviewing both customer-minutes and frequency per customer to avoid overlooking small circuits with high repeat frequency.

• Storm vs. non-storm analysis remains important. Even in storm events, teams are asking whether sectionalizing, vegetation practices, or prior mitigation could have reduced impact.

• Momentary interruption management is gaining attention.

  • AMI data is being used to differentiate isolated service issues from feeder-level problems.

  • Utilities are evaluating acceptable thresholds for repeated blinks.

  • Protection philosophy (fuse-saving vs. fuse-blowing) remains a design consideration, but customer impact must be factored into the decision.

• Automation of CEIMI analysis is a priority. Manual tracking of feeder/device changes and interruption counts is resource-intensive and limits scalability.

For more information contact Rob Earle at 315.944.7610