Why Utilities should evolve from reactive collections to Intelligent revenue operations

The obsolescence of the reactive, low-empathy model  

The utility market operates in an environment of high volatility, where rising energy costs collide with compounding household debt. Nearly 21.5 million U.S. households, roughly one in six, are currently behind on their energy bills, carrying a national arrears balance that exceeds $21 billion, up approximately 30% since the end of 2023 [1]. While companies implement cash management strategies aimed at improving overall days sales outstanding (DSO), the average days delinquent (ADD) continues to climb, reflecting that late-paying accounts are taking progressively longer to recover [2].  

This growing delinquency duration forces utilities to adopt increasingly defensive financial positions, inflating the regulated revenue requirement, and placing the cost of uncollectible debt on the broader customer base [3].  

When faced with this landscape, it’s clear that the traditional model is no longer enough. Managing debt only after its due date is a reactive measure that kicks in when the financial damage is already done. By applying rigid, mass collection strategies, which resulted in over 13.4 million electricity disconnections in 2024 alone [4][5], this approach reflects a complete disconnect from customers’ realities. Low-income households already spend an average of 8.6% of their income on energy [1] and pushing them toward disconnection rather than offering preventive solutions accelerates delinquency instead of resolving it. The deeper problem, however, escapes conventional indicators entirely: revenue leakage begins long before any customer reaches the collections stage. 
 

The real problem: Revenue is lost before collections  

Most utilities manage revenue recovery from the overdue debt. However, a significant portion of losses occur much earlier, during the commercial cycle itself, in the form of measurement errors, tariff inconsistencies, withheld billing, delayed reconciliations, highly manual processes and operational anomalies that go undetected until it is too late.  

The financial scale of these pre-collection losses is substantial. Non-revenue water alone costs U.S. utilities more than $6.4 billion annually, with nearly one in five gallons of treated drinking water lost before it reaches customers or is improperly billed due to system errors [6]. These losses rarely surface in standard collection reports. By the time the organization detects the problem, much of the potential revenue has already been diluted throughout the commercial cycle.  

Added to this is the operational disconnect from customers’ financial realities. Without systems capable of dynamically reviewing demographic and socioeconomic variables, utilities miss the opportunity to act with empathy. True financial retention happens when the system, before a default occurs. For instances, it can proactively offer arrearage management programs (AMPs) paired with percentage-of-income payment plans (PIPPs), programs that cap current bills at a manageable share of household income and have been shown to improve bill coverage ratios by approximately 50% [3], preventing customers from being pushed into uncollectible debt by the rigidity of the traditional model. 
 

The hidden cost of fragmented architectures and legacy systems  

It is common to find utilities where billing, customer management, advanced metering, CX, and field work systems operate independently, forcing teams to work with scattered information and manual processes. When measurement, consumption, billing, and payment data are not synchronized in real time, concrete problems emerge like unbilled consumption, tariff errors, payment application failures, delayed service orders, and commercial disputes that stall collections.  

This chain of failures is known as revenue leakage, the economic value progressively lost throughout the commercial cycle before being detected by financial departments. The gaps in debt recovery are directly tied to critical technological deficiencies. According to Gartner, traditional CIS platforms were built as monolithic, batch-processing engines optimized for simple meter-to-cash cycles, and they lack the architectural flexibility needed to support complex data flows and dynamic pricing [7][8]. Smart meter data arrives late to commercial processes, consumption anomalies are processed weeks later, and the result is a growing DSO, compressed margins, and a progressively deteriorating customer experience. 
 

When Volume Exceeds Human Capacity  

The digitalization of the electricity, gas, and water sectors has multiplied exponentially the volume of data generated by advanced metering infrastructure, but many utilities still rely on manual reviews to identify financial problems. The gap between available data and the capacity to process it manually is becoming increasingly difficult to close.  

A recent industry case illustrates the magnitude of this challenge: a utility with approximately 480,000 smart meters identified more than 95,000 leakage alerts in just 72 hours using advanced analytics and artificial intelligence [9]. That level of detection and exception management are simply not viable with manual processes. Meanwhile, high-bill inquiries continue to surge as customers struggle to decode complex rates and seasonal adjustments, absorbing significant staff hours and settlement costs across billing cycles [2][10]. Waiting until the end of the billing cycle to identify anomalies means allowing losses to accumulate for weeks before any corrective action begins. 
 

The solution: Intelligent revenue operations  

Faced with this landscape, more utilities are moving toward an Intelligent revenue operations model. Unlike traditional collections approaches, this strategy does not wait until revenue is lost before taking action. Instead, it uses predictive analytics, automation, and artificial intelligence to identify and address risks throughout the commercial cycle before they become financial losses. Moving to this model requires utilities to rethink how data, customer operations, field activities, billing, customer experience, and financial management work together across the organization.