Why 70% of service inquires at energy utilities could be automated.

Many energy utilities already invest in new systems like CRM platforms, self-service portals, or ticketing tools. Yet customer service often remains surprisingly manual. Incoming emails are read, requests are categorized, information is gathered from multiple systems, and responses are written. The real problem rarely lies in the technology itself, but in the process logic behind it. While the interface appears digital, fragmented, rule-based, and manual workflows often continue to run in the background. This is precisely where a significant economic lever exists.

Practical analyses, including projects conducted with epilot, show that around 85% of service inquiries follow clear patterns and fixed decision rules. This means they could fundamentally be automated or at least significantly accelerated. For a typical energy company handling around 150,000 service cases per year, this results in a realistic savings potential of €250,000–€350,000 annually, without reducing service quality.

The key is not another tool, but intelligent automation across the entire customer journey, starting with the inbox.

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The Challenge

Pressure on energy utilities

Volatile procurement prices, rising switching rates, and growing regulatory requirements are significantly increasing the economic pressure on energy providers. At the same time, customer expectations are changing. Service experiences are no longer compared only with other energy suppliers, but increasingly with leading digital platform companies and technology providers from other industries.

For many service organizations, this creates a dual challenge. On the one hand, the volume of incoming customer contacts is continuously increasing. On the other hand, customer inquiries are becoming more complex, as they often involve multiple systems, tariffs, or technical questions. At the same time, the shortage of skilled workers is intensifying the situation in many service centers, while the cost-to-serve continues to rise.

These developments are placing increasing pressure on customer service departments. A growing number of inquiries must be handled with limited personnel resources, while customers simultaneously expect fast, precise, and consistent responses.

Despite this dynamic, customer service remains one of the least automated areas within many energy companies. While sales, billing, and market communication have been heavily digitalized in recent years, many service processes are still largely manual. Incoming emails are read, requests are categorized manually, and responses are formulated individually. Under current conditions, this approach is increasingly reaching its limits.

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The operational reality in customer service

Let us consider a typical energy company with around 100,000 residential customers. At this scale, very similar service metrics can often be observed. Approximately 150,000 service cases occur each year, with an average handling time of about ten minutes per request. To manage this volume, many utilities employ up to 24 service agents, resulting in personnel costs of around €1.2 million per year.

At first glance, this structure appears reasonable: increasing contact volumes require corresponding staffing capacity in customer service. The real surprise, however, becomes apparent when analyzing the structure of incoming requests more closely. A significant share of customer inquiries follows clear rules and recurring patterns. Many requests concern similar topics, as the graphic below illustrates. This is precisely where a largely underestimated automation potential lies.

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These processes rarely require individual consultation. They mainly consist of checking, validating, and documenting.

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How large the automation potential really is

Industry analyses show that a substantial portion of service inquiries in energy companies has a high automation potential. Estimates suggest that around 70 to 80 percent of routine requests are fundamentally automatable, as they follow clear rules and are based on recurring information patterns.

By implementing appropriate automation solutions, organizations can not only standardize processes but also achieve significant efficiency gains. In many projects, handling times can be reduced by up to 50 percent because inquiries are categorized faster, relevant information is automatically consolidated, and responses are prepared in a structured way.

At the same time, this leads to clear economic effects. Service costs frequently decrease by 30 to 50 percent because a large share of routine work no longer needs to be handled manually.

The scale of these effects can be illustrated through a conservative example calculation.

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Why many digitalization projects change little

In recent years, many energy companies have made significant investments in new systems. CRM platforms have been introduced, customer portals have been built, ticketing systems have been implemented, and digital forms have been deployed. At first glance, customer service therefore appears far more modern and technologically advanced than it did only a few years ago.

However, despite these investments, the fundamental process logic within many organizations has remained largely unchanged. The new systems may digitalize individual interfaces and touchpoints, but they rarely transform the underlying service process itself.

In practice, this means that a large share of the work steps continues to be carried out manually. Incoming requests are read, categorized, information is gathered from different systems, and responses are formulated individually. As a result, the workflow in many service centers still follows a process logic that is heavily dependent on human handling.

The typical process therefore still looks roughly as follows:

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The interface is digital. The process remains manual.

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The Solution

The real lever lies in the inbox

In many energy companies, the inbox is the starting point for nearly all service processes. It determines how quickly a request is recognized and correctly classified, which relevant information is available for processing, who ultimately handles the case, and how much manual work arises during the subsequent steps.

In this initial stage, the key parameters for efficiency, processing quality, and response speed are already set. Nevertheless, this process step is only minimally automated in many organizations. Incoming emails are often still reviewed manually, classified, and then forwarded to the responsible teams or agents.

Paradoxically, the greatest efficiency losses within the entire service process arise precisely at this point. When requests must first be manually identified, sorted, and prepared, not only do processing times increase, but valuable service team capacity is tied up with tasks that could fundamentally be automated.

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A new approach: operational intelligence in the inbox

Instead of adding new tools on top of existing systems, the process can be re-imagined.

AI can analyze and structure incoming requests the moment they arrive.

Modern systems can:

• automatically identify customers
  
• categorize requests
  
• set priorities
  
• prepare responses
  
• document cases directly in the CRM
  
  

This creates an operational intelligence layer within the existing system landscape. Service teams continue working in their familiar tools, just much more efficiently.

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Pluz Solutions: Ori.on

How Ori.on operationally structures the inbox

If you would like to understand in more detail how a concrete service process can be automated directly at the inbox level, how such an architecture can be seamlessly integrated into existing systems, and which operational effects can realistically be achieved, we have summarized the key aspects in a short briefing.

You can access the briefing via the image below.

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