Driven by the Internet of Things (IoT), 5G, and edge computing, the utilization of telecom services is exploding. This surging demand presents significant revenue opportunities for communications service providers (CSPs), but it also poses substantial challenges. With large numbers of users sending massive amounts of data through their networks, telecom companies have found even basic organizational functions like customer support and order fulfillment are growing increasingly complicated.
To meet these challenges, telecom service providers are turning to automation. In fact, telecom is one of the industries with the broadest adoption levels of robotic process automation (RPA).
What is RPA?
According to IRPA AI Senior Contributor, Chris Surdak, “In 2020, intelligent automation and RPA were ‘optional’ like PCs were ‘optional’ in the 1990s, websites were ‘optional’ in the 2000s, and social media was ‘optional’ in the 2010s. In the 2020s, intelligent automation is critical, and RPA is an essential tool.” RPA is a method of automation that uses software robots to carry out simple, structured, and repetitive business processes, like data entry. When deploying RPA technology, users author bots and program them to mimic the specific steps a human employee would perform to do the same task.
For example, many telecom companies use RPA to streamline invoice processing. In that case, the bot would follow a script like this:
- Copy data from an incoming invoice.
- Paste it into the company’s accounting software.
- Forward the invoice to the appropriate authority for payment approval.
Other widespread examples of RPA implementation in telecom include processing new orders, adding new customer data to a CRM, and generating automated bills for subscribers.
But these uses only scratch the surface of RPA’s potential. When combined with artificial intelligence (AI) processing, low-code authoring tools, concurrent bot execution, and comprehensive automation solutions, RPA allows CSPs to radically transform their technology ecosystems for the better.
How RPA transforms telecom
As telecom technology has advanced, so have the public’s expectations. Individual consumers and enterprise customers all rely on high-speed, high-powered communication and computing capabilities to process the growing amounts of data they use daily.
Telecom companies need to transform their operations to keep up with demand in the age of 5G and IoT. They need to stop thinking of themselves as simple providers of networks and reinvent themselves as hybrid cloud platforms that can scale to support growing volumes of data, voice, and multimedia services. Or as Chris Surdak puts it, “The scale, scope, and speed of contemporary business dictates that humans get out of our processes and get over them instead: monitoring, guiding, and interpreting.”
Telecom companies face two imperatives in this journey:
- They must modernize their businesses to enhance agility.
- They must provide more compelling and personalized experiences to customers.
RPA is central to meeting both imperatives, and below, we lay out eight ways RPA is helping the industry transform.
Modernizing business operations for enhanced agility
Telecom is a tightly regulated industry, yet telecom companies must move quickly to keep up with the latest advances in technology and customer demand. RPA can help telecom companies grow more agile and stay compliant. Here’s how:
1. Streamline applications and infrastructure
Telecom companies rely on a mix of systems and software solutions to maintain the integrity of their networks and the efficiency of their services. They might map networks in Microsoft Visio, mine those networks for process data with IBM Process Mining, and use a numeric computing platform like MATLAB to dive even deeper into the insights generated by process mining.
Getting all these disparate systems to share data with one another can feel daunting, but RPA makes it easy. That’s because RPA provides a universal point of integration. The IT team doesn’t need to write special code or construct new APIs to facilitate system connection. Instead, bots can be programmed to follow the same steps a human worker would take to transfer data from a network-mapping tool to a process-mining solution to a numeric computing platform. As a bonus, bots are also much less likely to make errors when moving data between systems.
RPA bots also have nearly infinite scalability. If a CSP chooses an RPA solution with concurrent execution built-in, teams can run multiple bots at once on a single machine. This allows for multiple data transfers between multiple systems simultaneously, accelerating the speed of automated processes.
2. Automate network management
Network traffic grows by 40-50% every 12-16 months, and CSPs must ensure their infrastructure can handle it. Every time a network slows down or disconnects, it’s a potential loss of customers and revenue.
RPA, combined with AI processing, can help automate network optimization so faults are addressed in real time with minimal human intervention. This ensures the user experience remains consistently excellent.
For example, a company could use machine learning and AI algorithms to analyze network usage data. This analysis might identify particular metrics that signal potential network problems, such as the number of concurrent users or signal strength. A business rules management system can be used to outline proper workflow steps when these metrics hit critical thresholds. When those thresholds are met, AI can alert an RPA bot to take action based on the established business rules. The RPA bot might pull the network data, plug it into a report, and send that report to network technicians, so they can intervene to mitigate the potential fault.
3. Maintain compliance
The Federal Communications Commission (FCC) subjects the telecom industry to heavy regulation, including antitrust, licensing, and pricing laws. Staying compliant with regulatory mandates can be time-consuming and labor-intensive, but RPA can make it less of an administrative burden.
All a company must do is schedule a group of unattended bots to regularly collect relevant compliance data from specified systems and compile it all in a central spreadsheet. The organization will always have access to updated compliance information when it’s needed. The data will also likely be more accurate than it would be if a human employee were collecting it — as RPA bots don’t make transcription errors.
4. Manage metadata
Telecom and media companies are increasingly converging as each relies on the other to realize the total value of its offerings. As a result, more telecom companies are branching out into content and media services to diversify their revenue streams.
RPA can help telecom companies manage content offerings more intelligently. For example, with the help of optical character recognition (OCR) and AI processing, RPA can extract unstructured data from content and enter it into a content management system (CMS), such as Salesforce, where the data can be used for tagging and categorizing purposes. This categorization then makes it easier to serve tailored content and advertising suggestions to users.
5. Unleash more innovation
Contemporary RPA solutions, like IBM RPA, offer low-code bot authoring tools that allow every team member to create effective software bots regardless of their level of technical knowledge. When anyone can automate, the door to increased innovation is opened.
For example, customer service reps would have firsthand insight into which steps of the customer journey could most benefit from automation. Field techs might have ideas about how to streamline service scheduling. When telecom companies make RPA software accessible to everyone, they empower every employee to help accelerate business transformation.
Creating a more compelling customer experience
Customer satisfaction drops by 30% if it takes more than a day to resolve an issue with a telecom provider — and issue resolution in telecom takes an average of 4.1 days.
The telecom customer experience could use some work — which means there’s plenty of opportunity here for organizations committed to delivering better service. RPA can play a key role in attracting and retaining more customers by creating more compelling and personalized customer experiences.
6. Facilitate more convenient order management and provisioning
RPA excels in so-called “swivel-seat activities” (i.e., moving data between systems). So, RPA is well-positioned to facilitate faster order turnaround. Consider this scenario: A customer places an order through an AI-enabled chatbot, also known as an “intelligent virtual agent” (IVA). The chatbot relays the order to an RPA bot, which enters the customer’s order data into the inventory management system as soon as it’s placed, kicking order fulfillment off immediately.
RPA can also speed up the process of provisioning services to users while enabling customer service reps to deliver a more personal touch. For example, if a customer calls to place an order for new internet service to be established at their business, the customer service rep can run an RPA bot in the background to put the order details into a dispatching or fleet management system, such as Verizon Connect, while the customer is on the phone. There’s no need to put the customer on hold, and the customer service rep can continue to answer the customer’s questions as RPA processes their order.
RPA can be put to similar use in-store. For example, when a customer purchases a new smartphone and needs to set up service with the provider, a salesperson could have RPA input the customer’s data into the billing system while they walk the customer through the new phone’s features.
In each case, RPA supports a higher level of customer care and makes it significantly more likely that customer requests will be fulfilled within a day.
7. Support personalized engagement
Customers want a speedy resolution to their requests, but they don’t want customer service to feel mechanical. Automation can quickly become off-putting unless combined with a human touch. The good news is that RPA can support a more personalized approach to customer engagement.
The order and provisioning management examples above illustrate scenarios in which RPA allows customer service reps to deliver more engaging service without sacrificing efficiency. But combining RPA with AI can ensure automation doesn’t seem overly robotic and cold — even when human employees aren’t involved.
For example, you can use AI and machine learning functionalities to analyze customer habits and create tailored offers and promotions. RPA can then communicate these offers via chatbot or text message and even launch automated email campaigns through a marketing solution like HubSpot.
8. Gather competitor and customer data
Keeping track of what competitors and customers are doing is vital business intelligence, and RPA can help by collecting and aggregating high volumes of data.
For example, a company could script RPA bots to check competitor websites, collect price data displayed there, and enter it into a centralized spreadsheet. By scheduling unattended bots to do this regularly, the company will always have up-to-date reports on competitor activities.
Understanding patterns in consumer data usage can help telecom companies plan for infrastructure updates to better meet customer demands. RPA makes it easier to leverage this data by collecting it from a network performance management system, such as Riverbed, and aggregating it in a centralized spreadsheet where relevant team members can easily access it.
The benefits of RPA in telecom
Telecom companies are investing more and more in infrastructure and networks to keep up with increasing customer demands and evolving technology. But these necessary upgrades can quickly eat into revenue, and McKinsey is predicting the total cost of network ownership could double by 2025.
Telecom companies must maximize their returns on these technology investments by ensuring the technology works at optimal levels and driving down their operational costs. RPA is essential to achieving both goals.
RPA can automate basic tasks like updating customer records. Combined with AI processing, it can also help automate more advanced functions like network management. In both cases, RPA powers a more effective delivery of services by automating typically manual processes, which leads to more customer satisfaction, more new subscribers, and more retained revenue. Meanwhile, employees can spend more time on high-value tasks like innovating processes and products and solving complex customer problems.
Additionally, automation makes it easier to monitor network performance, plan for infrastructure expansion, and optimize as necessary. That means telecom companies spend less time and money on maintenance and more time reaping the rewards of an efficient network.
To learn more about the cost savings and other business benefits of RPA, read the IBM RPA Total Economic Impact™ study from Forrester Research.