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Top 8 RPA Use Cases in Utilities in 2024

Agility in the utilities and energy sector is important. 94% of energy providers to be inept at responding to challenges (Figure 1). One reason is that utility companies have to deal with a large number of incidents regularly, and at times simultaneously.

Figure 1: 94% of energy providers claim they can’t respond to changes quickly. Image source: EY

Digital transformation in utilities, such as adopting an RPA tool, can increase agility. can increase energy companies’ agility, with RPA being one of the tools. RPA in utilities uses software bots for automating time-consuming tasks. This allows energy companies to respond quickly to operational changes.

There are things that utilities company can do better. In this article, we cover 10 use cases where RPA can help.

1. Billing

The average leading utility provider in the U.S. has ∼3,0001 customers’ bills to process (Figure 2). Increased possibility of errors, such as:

  • Misspelling customers’ names
  • Inputting an inaccurate invoice amount
  • Over/underreporting energy usage
A leading electric utilities in the US has almost 3,000 customers on average. One of the RPA use cases in utilities is automated billing at scale.
Figure 2: The average number of customers a leading US electric company has is 3,000. Source: Statista

[…] can lead to wrong billing, decreased customer satisfaction, and undermine the business’ operational efficiency. RPA can automate the billing process by:

  • Extracting usage data from smart sensors,
  • Validating and cross-checking against the customer’s data,
  • And inputting it on the bill.

Delegating billing to software robots reduces the likelihood of human error leading to an incorrect bill.

2. Meter readings

Automated meter readings allow RPA bots to input the proper usage amount on the correct customer’s bill. This is  a repetitive task that is best delegated to robots.

RPA bots can also turn meter readings into usage reports. The usage data can then be fed into predictive analytics models to detect patterns  and predict future consumption levels.

Moreover, meter readings can also be used to offer a personalized service. Energy companies could incentivize users to lower their consumption by providing  a discount on next month’s bill.

Keeping a data-driven record of areas with the most power consumption helps utility companies better manage peak-season usage.

3. Customer support

RPA bots can quickly extract customers’ data from multiple systems and present them to the customer rep. This allows the rep to focus on solving the customer’s issue instead of manually pulling up disparate data from different legacy systems.

In addition, AI-enabled chatbot can also be leveraged to improve customer experience. Chatbots can tend to some the customer inquiries automatically, such as:

Lowering the workload of contact centers allows human employees to focus on higher-value tasks

4. Predictive maintenance

Predictive maintenance is used in manufacturing, restaurants, and other industries. It allows technicians to tend to the equipment preemptively before the issue worsens and results in a breakdown.

RPA can analyze the data from cell towers, servers, and communication centers. It can then transform those unstructured data into easily-readable insights. Bots can also send notifications to technicians, and schedule maintenance, whenever an equipment’s check-up time is about to approach.

Given that malfunctions in the utilities sector often have serious consequences (Figure 3), being notified of power outages, component failures, or other such issues can circumvent them.
Figure 3: California’s 2018 wildfires. Image source: BBC

Monitoring equipment by robotic process automation can also reduce operating costs, as inefficiencies are quickly fixed. This increases the company’s competitive advantage.

5. Complaints management

Utility companies receive their fair share of customer complaints. In the UK, for instance, there were a total of ∼10,0002 complaints in Q4 2021 (Figure 4).
Figure 4: Customer complaints that UK energy suppliers receive has remained constantly noticeable. Source: Statista

Artificial intelligence-enabled chatbots can at least partially automate complaints resolution:

  • They’d receive the complaint,
  • Read, understand, and categorize it via OCR, NLP, and sentiment analysis capabilities
  • And create a support ticket for each.

If the complaints fall within the bots’ capabilities, they could access their knowledge bases or carry out rules-based steps to resolve them. If not, they can send the support ticket to whomever it concerns.

6. Financial processes

Utility companies, like other businesses, have financial processes in the back-office that can be automated to ensure accuracy and reduce costs with minimal human intervention.

EDF Energy3 , for instance, had a “substantial” number of journals that needed to be created and amended at month’s end. EDF Energy had to delegate two FTEs to finish this weekly task, which took 70 hours. The RPA bot now receives each journal entry, validates it, and inputs it into the ERP system.

EDF Energy further automated 8 other financial processes, tax calculations and accounts payable processing. RPA technology helped the energy giant “save £100,000 in software and development costs.”

These core processes can be automated by RPA bots, which allows them to be done with minimal effort by the financial department.

7. Regulatory compliance

There is potential for energy and utility companies to improve their compliance, for they are frequently involved in scandals. See:

  • PG&E’s 2021 manslaughter charge

RPA bots can extract the info pertaining to safety checks, operational costs, KPIs, and more, from multiple sources. Utility providers have to maintain and show these to public authorities periodically. For instance, automation of ESG reporting leaves a visible, transparent footprint for compliance officers to assess.

8. Contract management

RPA technology can automate energy and utility companies’ contract management. These enterprises have a large number of customers and vendors. And it can be difficult to manually:

Intelligent automation solutions leverage robotic process automation technology to monitor the contract’s important data (such as expiry date) and terms. Automated notifications can then be sent to the sales or legal teams whenever an issue arises.

Moreover, contract automation allows for RPA bots to quickly pick the appropriate contract template, fill in the blanks with the counter-party’s info, and send it to them for signature. 

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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