RPA plays a pivotal role in the digital transformation of modern enterprises, and unsurprisingly, the global RPA market is predicted to expand at a compound annual growth rate (CAGR) of 37.9% by 2032.
However, while RPA has proven its potential to reduce costs, improve efficiency, minimize errors, and help drive a plethora business goals forward, its success depends on the effectiveness of its deployment, implementation, and governence. And having a portfolio of industry-specific use cases, such as RPA use cases in telecom, help enterprises increase the likelihood of their deployment’s success.
In this article, we will discuss the importance of an industry-specific approach to RPA deployment in the telecom industry, which relies heavily on relevant use cases, before exploring five RPA use cases in telecom with proven business potential.
The importance of industry-specific RPA use cases in Telecom
Many RPA use cases are relevant to specific business functions, like HR or customer service, making them industry-agnostic. However, tapping into industry-specific use cases can help telcos quickly secure internal buy-in, reduce deployment times, mitigate risks and prioritize processes to automate.
Since business functions operate similarly within an industry, and share common systems, industry-specific use cases save telcos from long process-discovery cycles. Additionally, leaders can rapidly secure internal buy-in by accurately showcasing RPA’s business value with tailored use cases. Rather than making generic estimates pertaining to RPA’s potential, you can estimate the time or cost savings, error reduction, etc., of deploying a specific use case within a telco. For example, you can estimate the reduction in average handling time (AHT) by deploying RPA use cases in the contact center.
Naturally, there is also merit in partnering with a managed service provider (MSP) with industry-specific RPA use cases. Instead of having to explain every process to your MSP, their developers will have a pre-existing appreciation of them, reducing deployment times. It’s akin to having your own internal RPA team.
RPA use cases in Telecom
M.M has partnered with the Telecom Intelligent Automation Council (TIAC) and put together a telco-specific use case guide that covers a wide variety of automation related solutions. Here, we highlight several different use cases that demonstrate how RPA is being utilized in the telecom sector.
1. Customer Service Status Retrieval
The majority of call center agents need training on various different systems, and they have to frequently switch between them, which can have a negative impact on the customer’s call experience, the length of the call as a whole, and accuracy since data is frequently copied and pasted between applications and systems.
Attended RPA bots are now being deployed to:
• Gather pertinent data about customers and products from several systems and show it in a single form.
• File the information to the dependent systems with a simple press of a button.
This has resulted in a 60% decrease in average handling time and a whopping 90% error reduction.
2. Automated Network Inventory Reconciliation
It is crucial for digital service providers to maintain an accurate inventory of assets and services. However, Digital Service Providers (DSPs) face several challenges when it comes to maintaining inventory data accuracy and completeness.
Previously, field technicians updated network-side modifications with customer service representatives (CSRs) and simultaneously collaborated with the provisioning & activation team to complete orders.
These manual tasks require a lot of time, are prone to mistakes, and it takes several hours or days for the BSS Inventory to reflect these changes. Data integrity problems are frequently caused by network changes that aren’t updated in inventory management systems.
RPA bots can keep track of updates to Network Inventory (Master Data) and instantly update the downstream systems. An RPA Bot can also check for any discrepancies in the data by comparing them with the CPE monitor system’s data.
Outcomes observed in this specific case study included a 60% FTE reduction, as well as a 70% drop in cessation request errors.
3. Repeated Calls
Sometimes, it takes the help of various different agents to effectively resolve a customer’s issue. A customer may have to repeat their concern multiple times to several agents, and this repetition can result in the customer getting frustrated. This can in turn hinder the rapport created with the customer owing to high turn around times and average call durations.
RPA bots can help monitor any headway being made on a specific issue, and integrate various systems, so that agents do not have to keep track of all applications simultaneously. This may result in significant error reduction, as agents need only focus on one task at a time, while the bot takes care of the rest.
During calls, RPA bots can spotlight the latest customer exchange and pull up information instantaneously. With such a system in place, the agent does not need to repeat the verification process and ask repetitive questions.
By deploying RPA in various contexts, average call time decreased by half, and there was a staggering 90% improvement in customer experience.
4. NOC/SOC Monitoring
A NOC (Network Operation Center) was seeking to automate a monitoring process. The monitoring process in question includes sending alerts via emails, WhatsApp, and robocalls to concerned predefined POCs for issue resolution in the event that a variable count exceeds a predetermined, dynamic threshold value.
When an issue cannot be resolved at the initial stage of escalation, whether it be because the issue persists or because of the response from the concerned POC to whom the alert was initially sent, the procedure will also include sending the alert to the next level.
The NOC team’s goal is to divert employees’ attention away from the widgets so that they can be used for more productive duties and to cut down on average handling time.
However, there were several challenges that the automation process had to address:
• ELK, Nagios, Solar Wind, PMM, OEM Ericsson (OpenNMS & Grafana), and Xflush are all continuously monitored as part of the NOC Monitoring & Incident Management’s manual procedure.
• In the event that any threshold on the services distributed on these tools is breached, extensive escalations are done.
• System ability to conduct level 1 inquiry.
• Frequent follow-ups with relevant POCs
• Possibilities of human oversight.
It is expected that after successful automation, several key benefits will be observed. The manual handling time of the NOC’s constant tracking procedure will be drastically reduced by a bot. The bot will compare data from various systems to determine what prompted a threshold violation. Aside from follow-ups, it is anticipated that the turn-around time (TAT) for each increase will be lowered to 20 to 25 seconds, with an estimated 90% decrease in errors.
5. HR Onboarding/Offboarding Process (R2R)
The onboarding process often takes several weeks because HR must complete a number of repetitive tasks, including giving new hires access to the company’s data systems that they require to do their jobs. This access is given in accordance with a job description for the particular role. The onboarding process is often prone to human error, due to the large amount of information that must be handled at the same time. Moreover, while communication between different departments (such as finance, HR and IT) is crucial during this time, it can often be a lengthy and tedious process.
These processes are made exponentially simpler with the leveraging of RPA bots. The entire onboarding procedure, from sending an offer letter to conducting orientation, can be programmed into an RPA bot. The bot can automatically send an email containing an offer letter, a welcome message, and onboarding and policy documents once it has been decided to employ the applicant. The RPA bot can review the forms, look for any missing information, and email the applicant as necessary after the candidate has accepted the offer and submitted the necessary data. RPA bots scan documents, extract data, and digitally record everything. Bots can prompt employees to fill out any information that is lacking during the onboarding process to make it more interactive. Then, to prevent data duplication, all staff data is kept in a centralized location.
Conversational AI Bots and RPA Bots can also:
• Configure and Provide Access to Company Data Systems Based on Roles
• Create header and line data that CRM will approve
• Create staff requests for outside services
• Create offer letters; ( Official Number, Salary, Account)
With the implementation of RPA in these scenarios, average handling time was cut down by nearly 90%, and there was a 50% reduction in FTE.
Conclusion
Every business has to create a strategy that outlines how their product or services will generate revenue and provide value to their clients. In this regard, use cases are valuable because they aid in describing how the system is intended to perform and, in the process, aid in generating recommendations for potential problems.
Therefore, use cases are only helpful when they are able to adequately demonstrate how a certain stakeholder’s needs are being met by a product or service. So while RPA has great potential to aid innovation, cut costs and reduce errors, its true capability is best seen when viewed through an industry-focused lens.
