Case Study 1: Forecasted Meter Read Workload for mid sized power distribution utility

Problem

A mid-sized power distribution utility faced a significant challenge with the anticipated failure of its next-generation advanced metering infrastructure. The failure risk posed a direct threat to reliable customer billing and compliance with regulatory standards.

Solution

Initially, this utility had deployed the first generation of smart meters in the mid-2000s. However, these meters began to experience accelerated deterioration, particularly in their communication modules. After securing regulatory approval, the utility prepared to upgrade to next-generation meters. During field testing, it became apparent that these new meters were experiencing registration delays, taking over 30 days to connect to the network—a situation that could disrupt billing cycles.

To address this, the utility engaged our services to create a robust forecast of field workforce requirements under several worst-case scenarios. Utilizing raw data across multiple Excel worksheets detailing service territories and meter statuses by billing cycle, we applied Power BI tools to craft detailed visualizations of daily workloads, with particular attention to peak periods at the end of each billing cycle.

This analytical approach helped the utility understand the maximum meter read (MR) workload for each cycle. To ensure compliance and uninterrupted service, the utility proactively recruited and trained seasonal workers to manually read meters until they were fully registered in the network. For example, analysis for the month of June showed a peak need of 3,534 meter reads on the 10th, indicating the necessity to hire 35 seasonal workers in advance of this peak.

Result

Our analysis detailed daily meter read (MR) unit counts across different regions within the utility’s service area, organized by scheduled meter read dates. The visualizations provided a clear monthly view, exemplified by June 2024's data, showing day-by-day MR unit counts. This allowed the utility to strategically allocate the necessary workforce, prioritizing areas with the highest daily counts to ensure efficient, regulatory-compliant meter readings.

By effectively forecasting the impact of the registration delay, the utility not only maintained regulatory compliance but also ensured that customer billing remained accurate and uninterrupted during the transition to new technology. This strategic workforce management approach allowed the utility to navigate a potential crisis, turning a technical challenge into a demonstration of proactive, data-driven decision-making.