{"id":48157,"date":"2026-06-25T11:03:27","date_gmt":"2026-06-25T16:03:27","guid":{"rendered":"https:\/\/www.openintl.com\/utilities-should-evolve-reactive-collections-to-intelligent-revenue-operations\/"},"modified":"2026-06-25T12:22:09","modified_gmt":"2026-06-25T17:22:09","slug":"utilities-should-evolve-reactive-collections-to-intelligent-revenue-operations","status":"publish","type":"post","link":"https:\/\/www.openintl.com\/en-emea\/utilities-should-evolve-reactive-collections-to-intelligent-revenue-operations\/","title":{"rendered":"Why Utilities should evolve from reactive collections to Intelligent revenue operations"},"content":{"rendered":"\t\t
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\n\t\t\t\t\tUtilities are facing financial pressures that extend far beyond traditional delinquency. Technology fragmentation, reactive and low-empathy collections models, and errors caused by highly manual processes are eroding cash flow long before an invoice becomes overdue. In this environment, the transition to Intelligent Revenue Operations, combining advanced analytics, automation, and AI with financial empathy, is becoming a key differentiator between utilities that protect both customer relationships and revenue, and those that recover losses only after the damage has already occurred.<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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<\/span><\/b>The obsolescence of the reactive, Low-Empathy model\u00a0<\/h3>

The utility market navigates an environment of high volatility where geopolitical tensions and rising energy costs collide with a severe affordability crisis. In the United Kingdom,\u00a0for instance, the\u00a0domestic energy\u00a0total\u00a0debt climbed to a record\u00a0<\/span>\u00a34.55 billion<\/span><\/b>\u00a0by the end of 2025,\u00a0representing\u00a0an 18% year-on-year increase. From the onset of the energy crisis, average household electricity arrears rose by 35% to \u00a32,036, while average gas arrears surged by 44% to \u00a31,610 [1].\u00a0<\/span>\u00a0<\/span><\/p>

While corporate\u00a0debt\u00a0management strategies attempt to improve overall metrics, the\u00a0<\/span>days sales outstanding (DSO)<\/span><\/b>\u00a0has\u00a0steadily increased across the EU,\u00a01.8% over the past decade to an average of 50 days\u00a0[2]. Furthermore, Western Europe recorded a four-day surge in corporate Working Capital Requirements (WCR) for the third consecutive year [3]. This growing duration of delinquency forces utilities to adopt defensive\u00a0debt\u00a0management strategies to shield their balance sheets, which\u00a0ultimately inflates\u00a0the utility’s regulated revenue requirement. For instance, debt relief schemes that write off historic arrears often fund this relief by socializing costs across all\u00a0bill-payers, adding an annual surcharge that risks pushing more marginal consumers into delinquency [4].<\/span>\u00a0<\/span><\/p>

When faced with this panorama, it is\u00a0evident\u00a0that the traditional model is no longer sufficient. 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, this model shows a total disconnect from the user’s reality. By\u00a0failing to mix\u00a0data intelligence with empathy, organizations ignore the macroeconomic pressures facing their customers,\u00a0such as the 38% of Scottish households forced to ration heating [5]\u00a0and push them into delinquency instead of offering preventive solutions. The true problem escapes conventional indicators, as revenue leakage begins long before the customer reaches the collections stage.\u00a0<\/span>\u00a0<\/span><\/p>


<\/span><\/b>The\u00a0real\u00a0problem: Revenue is\u00a0lost\u00a0before\u00a0collections\u00a0<\/h3>

Most utilities approach revenue recovery through overdue accounts. However,\u00a0a significant portion\u00a0of revenue loss occurs much earlier in the commercial cycle through metering errors, tariff inconsistencies, delayed billing, reconciliation issues, and operational anomalies that\u00a0remain\u00a0undetected until it is too late.<\/span>\u00a0<\/span><\/p>

The financial scale of these pre-collection losses is massive. Across Europe, an average of 25% of all treated water is lost as non-revenue water (NRW) due to commercial and physical errors before it can generate revenue [6]. In the UK alone, leakage and measurement discrepancies account for the equivalent of 1,245 Olympic swimming pools of water lost every single day, severely draining potential cash flow [7]. What is\u00a0most concerning is that these losses rarely appear on standard collection reports. By the time the organization detects the problem, much of the potential revenue has already been diluted throughout the commercial cycle.<\/span>\u00a0<\/span><\/p>

All of that is happening without putting in the equation the constraints and realities of each household. When\u00a0systems\u00a0\u00a0can\u2019t\u00a0dynamically review demographic and socioeconomic variables, utilities lose the opportunity to act with empathy. True financial retention occurs when the system, prior to default, can proactively segment customers\u00a0based\u00a0on financial vulnerability profiles, for example. Utilizing data intelligence to automatically offer flexible payment plans, social tariff enrollments, or dunning deferrals to\u00a0vulnerable\u00a0customers\u00a0maintains\u00a0collection rates while protecting the customer relationship.\u00a0This can\u00a0prevent\u00a0families\u00a0from being pushed into uncollectible debt by the rigidity of the traditional model.<\/span>\u00a0<\/span><\/p>


<\/span><\/b>The\u00a0hidden\u00a0cost of\u00a0fragmented\u00a0architectures and\u00a0legacy\u00a0systems\u00a0<\/h3>

It is common to find utilities where billing, customer management, advanced metering, CX, and field work systems\u202foperate\u202findependently, 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\u202femerge\u202flike\u202funbilled consumption, tariff errors, payment application failures, delayed service orders, and commercial disputes that stall collections.\u202f<\/span>\u00a0<\/span><\/p>

This chain of failures is known as\u202f<\/span>revenue\u202fleakage<\/span><\/b>,\u202fthe economic value progressively lost throughout the commercial cycle before being detected by financial departments. The gaps in\u202fdebt\u202frecovery are directly tied to\u202f<\/span>critical<\/span><\/b>\u202f<\/span>technological deficiencies<\/span><\/b>. According to Gartner, traditional CIS platforms were built as monolithic, batch-processing engines\u202foptimized\u202ffor simple meter-to-cash cycles, and they lack the architectural flexibility needed to support complex data flows and dynamic pricing [8]. Smart meter data arrives late to commercial\u202fprocesses,\u202fconsumption anomalies are processed weeks later, and the result is a\u202f<\/span>growing DSO<\/span><\/b>, compressed margins, and a progressively\u202f<\/span>deteriorating customer experience<\/span><\/b>.\u202f<\/span>\u00a0<\/span><\/p>


<\/span><\/b>When Volume Exceeds Human Capacity\u202f\u00a0<\/h3>

The energy transition has exponentially multiplied the amount of data generated by advanced metering infrastructure.\u00a0A few years back, utilities had already installed over 120 million smart metering devices [9]. However, many utilities still rely heavily on manual exception queues and spreadsheet-based tracking to\u00a0identify\u00a0financial problems. The gap between the available data volume and the capacity to process it manually becomes increasingly difficult to close.\u00a0<\/span>\u00a0<\/span><\/p>

A recent industry case illustrates the\u00a0magnitude\u00a0of this challenge: a utility with approximately\u00a0<\/span>480,000 smart meters\u00a0<\/span><\/b>identified\u00a0more than\u00a0<\/span>95,000 leakage<\/span><\/b>\u00a0alerts in just 72 hours using advanced analytics and artificial intelligence [10]. That level of detection and exception management is simply not\u00a0viable\u00a0with manual processes. Meanwhile, when billing errors, estimated invoices, or confusing rate structures occur, contact centers are flooded with inquiries. Resolving these issues manually requires extensive call center staffing, driving up transaction handle times and operational overhead. Waiting until the end of the billing\u00a0cycle to\u00a0identify\u00a0anomalies means allowing losses to accumulate for weeks before\u00a0initiating\u00a0any corrective action.\u202f<\/span>\u00a0<\/span><\/p>


<\/span><\/b>The\u202fsolution: Intelligent\u202frevenue\u202foperations\u202f\u00a0<\/h3>

Faced with this landscape, more utilities are moving toward an\u202f<\/span>Intelligent revenue operations<\/span><\/b>\u202fmodel. Unlike traditional collections approaches, this strategy does not wait until revenue is lost before\u202ftaking action. Instead, it uses predictive analytics, automation, and artificial intelligence to\u202fidentify\u202fand address risks throughout the commercial cycle before they become financial losses. Moving to this model requires utilities to\u202frethink\u202fhow\u202fdata, customer operations, field activities, billing, customer experience, and\u202ffinancial management\u202fwork together across the organization.\u202f\u202f<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Open<\/span><\/b>\u202fenables this approach through\u202f<\/span>Smartflex<\/span><\/b>, a comprehensive platform built specifically for utilities.\u00a0Smartflex\u00a0brings together billing, customer service, field operations, and smart metering on a single data model. With shared data and automated workflows, utilities gain a clearer view of the revenue cycle and can respond more quickly to operational and financial issues as they\u202femerge.\u202f<\/span>\u00a0<\/span><\/p>

At the center of this capability is Alexandria, Open’s embedded AI engine. Alexandria analyzes operational, commercial, and financial data to\u202fidentify\u202frisk patterns, support autonomous processes, and help utilities make faster, more informed decisions across the revenue lifecycle.\u202f<\/span>\u00a0<\/span><\/p>


<\/span><\/b>From Reacting to Anticipating\u202f\u00a0<\/h3>

Revenue management in the utility industry can no longer rely on a reactive collections approach that begins only after an account becomes overdue. Replacing manual processes and fragmented architectures with\u202fa\u202funified operation not only helps prevent revenue loss and improve recovery outcomes, but also strengthens regulatory compliance, enhances\u202fthe customer\u202fexperience, and provides the visibility needed to\u202f<\/span>make smarter, more informed financial decisions<\/span><\/b>.\u202f<\/span>\u00a0<\/span><\/p>

The question utility leaders must ask today is not whether revenue management needs to be modernized, but whether their current technology architecture has the connectivity, visibility, and analytical capabilities\u202frequired\u202fto\u202f<\/span>protect<\/span><\/b>\u202frevenue in an increasingly complex environment.\u202f<\/span>Intelligent revenue operations<\/span><\/b>\u202fare\u202fnot a future concept. It is the direction utilities are taking as they move from reacting to problems after they occur to\u202fanticipating\u202fand addressing them before they\u202fimpact\u202ffinancial performance. Combining the power of analytics with financial empathy, utilities can protect revenue while better supporting customers through financial challenges, strengthening trust, and building long-term loyalty.\u202f<\/span>\u00a0<\/span><\/p>



References<\/span><\/b>\u00a0<\/span><\/p>

[1]\u00a0StepChange.\u00a0<\/span>Energy Debt. Perfect Storm. Ofgem Data.<\/span><\/i>\u00a0<\/span>https:\/\/www.stepchange.org\/media-centre\/press-releases\/energy-perfect-storm.aspx<\/span><\/a>\u00a0<\/span><\/p>

[2]\u00a0Working Capital Study 25\/26 – PwC UK<\/span>.<\/span><\/i>\u00a0<\/span>https:\/\/www.pwc.co.uk\/services\/value-creation\/insights\/working-capital-study.html<\/span><\/a>\u00a0<\/span><\/p>

[3] Allianz Trade.\u00a0<\/span>WCR and DSO report 2025.<\/span><\/i>\u00a0<\/span>https:\/\/www.allianz-trade.com\/en_global\/news-insights\/news\/wcr-dso-report-2025.html<\/span><\/a>\u00a0<\/span><\/p>

[4] Parliament UK.\u00a0<\/span>Tackling the energy cost crisis: Ofgem Response.<\/span><\/i>\u00a0<\/span>https:\/\/publications.parliament.uk\/pa\/cm5901\/cmselect\/cmesnz\/1789\/report.html<\/span><\/a>\u00a0<\/span><\/p>

[5] Consumer Scotland.\u00a0<\/span>Energy debt at record levels as Ofgem announces\u00a013% hike in prices.<\/span><\/i>\u00a0<\/span>https:\/\/consumer.scot\/news\/energy-debt-at-record-levels-as-ofgem-announces-13-hike-in-prices\/<\/span><\/a>\u00a0<\/span><\/p>

[6] IWA Publishing.\u00a0<\/span>Water loss management in Europe:\u00a0perceptions, drivers, responses\/strategies, and results.<\/span><\/i>\u00a0<\/span>https:\/\/iwaponline.com\/wpt\/article\/20\/9\/1921\/109252\/Water-loss-management-in-Europe-perceptions<\/span><\/a>\u00a0<\/span><\/p>

[7] Water UK.\u00a0<\/span>A Leakage\u00a0Routemap\u00a0to 2050.<\/span><\/i>\u00a0<\/span>https:\/\/www.water.org.uk\/sites\/default\/files\/wp\/2022\/03\/Water-UK-A-leakage-Routemap-to-2050.pdf<\/span><\/a>\u00a0<\/span><\/p>

[8] Gartner.\u00a0<\/span>Market Guide for Utility Customer Information Systems.<\/span><\/i>\u00a0<\/span>https:\/\/www.gartner.com\/en\/documents\/5487595<\/span><\/a>\u00a0<\/span><\/p>

[9]\u00a0Netmore\u00a0Group.\u00a0<\/span>SMART METERING WITH LORAWAN POV WHITEPAPER.<\/span><\/i>\u00a0<\/span>https:\/\/netmoregroup.com\/wp-content\/uploads\/2023\/06\/Netmore-Smart-Metering-With-LoRaWAN-Whitepaper-2022_.pdf<\/span><\/a>\u00a0<\/span><\/p>

[10] AI vs Invisible Revenue Losses.\u00a0<\/span>Deep Dive into Proactive Leakage Detection in Utilities.<\/span><\/i>\u00a0<\/span>https:\/\/www.linkedin.com\/pulse\/ai-vs-invisible-revenue-losses-deep-dive-proactive-leakage-abufadda-ekblf\/<\/span><\/a>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Utilities are moving beyond reactive collections toward intelligent revenue operations, combining AI, analytics, and automation to prevent revenue loss, improve efficiency, and deliver more customer-centric financial management.<\/p>\n","protected":false},"author":9,"featured_media":48142,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[60],"tags":[],"class_list":["post-48157","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry-articles","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-33"],"acf":[],"yoast_head":"\nIntelligent Revenue Operations for Utilities | Open Intelligence<\/title>\n<meta name=\"description\" content=\"Discover how intelligent revenue operations help utilities reduce revenue leakage, improve collections, and protect customers with AI-driven insights.\" \/>\n<meta name=\"robots\" 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