In a manual working environment, this process entails transferring customers from one department to the next, or from one partner to the next while a human worker checks the accounting and billing systems to identify the discrepancy. It gets even more complicated if a customer requests a change or cancellation of their services. The request goes through several layers of people and partners and like a game of telephone, the message can get lost in translation, leaving the customer to incur additional costs.
This is a problem that the RPA Robots are extremely suited for. RPA works hand in hand with Optical Character Recognition (OCR) software and Document Processing Automation (DPA) systems that automate the billing and invoice processes. The robots are given specific instructions and they don’t make mistakes so discrepancies are revealed much faster. Furthermore, the robots work 24 hours a day, 7 days a week and they never get tired, so they can process invoices at record speeds. They process transactions between any number of legacy technology systems without having to invest in expensive APIs, ERPs or integration software. They also leave a complete digital footprint of all activities. With this detailed audit trail, the bots can identify which services the customers has subscribed to, any upgrades and changes to their service. The robots take all of that information, consolidate it and send it to a human worker who can intervene if needed, resolve the discrepancy, and serve the customer quickly and accurately.
This scenario puts pressure on the network and operations teams who are investigating network alerts, which may be false positives but nonetheless, need to be addressed. At the same time, they are receiving inquiries and feedback from the service center who need help diagnosing issues so that they can better manage the customers. They need to know the root cause of the problems, the right department needs to be notified and the customer needs to know when they can expect their service to be restored. The network and operations teams have to prioritize dozens of requests and identify the quickest and most efficient way to avoid further outages and restore exiting outages.
This kind of chaos is where the RPA robots thrive and can help in several different ways. Using attended RPA automation, the robots can receive the alerts and work hand in hand, in real-time, with the network diagnostics software and human team, and based on pre-determined criteria, either disqualify the alert or generate a service ticket. This weeds out the lower priority alerts and moves the more critical alerts to the top of the queue.
Beyond this, RPA can run diagnostic tests using a business rule engine to determine whether a ticket can be eliminated or if it needs to be passed on to the operations team. Combining RPA with AI can help to increase accuracy even further by basing rules on historical patterns so the robots can provide even more accurate next best actions. This means most inquiries can be handled by the call agent, rather than the operations team, which reduces the “time to resolution,” increases quality assurance, optimizes efficiencies and above all, improves customer service, all while minimizing pressure on the operations teams.
With 5G around the corner, network planning is critical to ensure operators get the most favorable ROI. However, data is spread across CSPs’ infrastructure in silos, creating a challenge for the network planners seeking a holistic picture of the results and implications of their decisions. Making these choices without the help of automation is prohibitively time-consuming, extremely complex and an inexact science. Analysts must look at current and historical data on a range of areas such as predicting whether consumption is likely to increase, analyzing customer profiles to determine profitability based on location, assessing current quality of service and predicting whether there could be an increase in market penetration.
Robotic Automation Processing platforms can auto-recommend the shortest, most cost-effective path to lay a cable. Artificial Intelligence (AI) capabilities can also help network planners understand the density of population, so they can accurately predict future opportunities and recommend next best actions.
The RPA robots can turn that model on its head and transform the traditional “cost” call center into a potential “revenue” center. Using attended robot ‘helpers’, RPA can automatically aggregate and harmonize customer data from multiple sources into a single 360-degree view of the customer, allowing them to answer a query fast than ever before, improving the customer experience and elevating the productivity of the call center staff.
Because RPA means less complex inquiries can be addressed faster, the customer service workers will have more time to execute up-selling strategies and generate more revenue for the company. This method of aggregating data can also support AI-driven responses. AI can be used to ‘learn’ from customer scenarios and suggest next best action decisions instantly – this improves customer experience, as well as creating cost reductions for businesses.
Collate data for revenue forecasting, decision making, planning, and strategy.
Ensure invoices are executed accurately and efficiently to improve billing processes.
Manage, qualify and prioritize alerts to increase speed and improve efficiency.
Easy access and visibility into a 360-degree view of the customer to provide better service
High employee engagement with more time to focus on higher-value tasks improves morale.
To exacerbate this complex environment, due to rising competition, CSPs are losing market share as well as traditional pre-paid contractual revenue. They need to identify and capture new sources of revenue beyond television, wi-fi, fixed and mobile services. And they are still working within a highly regulated environment, a complex eco-system and demanding customers.
In order to remain competitive, CSPs are deploying innovative strategies to consolidate and harness data, streamline processes, increase efficiencies and better serve customers. They are finding ways to integrate and monetize smart city technologies, blockchain and data analytics to streamline fleet management, predictive maintenance and extended customer value chains to improve customer acquisition, growth and retention programs.
The robots can help telecommunication companies and CSPs by executing repetitive, manual tasks. The robots perform these mundane activities and will alert the employees only if there are any discrepancies or issues, so the day-to-day simpler tasks can be taken care of in a fraction of the time without distracting the employees. Robotic Processing Automations work between a variety of computer systems without having to deploy expensive APIs or integration systems. It can be used for accounting, network issues and planning as well as customer service. The robots work 24/7/365. They never make mistakes and they have demonstrated immediate and quick returns on investment.
RPA multiplies the work capacity of the human employees by augmenting their abilities to process mundane tasks. This allows CSPs to reduce costs, increase accuracy and quality, improve efficiency and deliver a better customer experience. Specifically for telecommunication specialists, RPA enables network teams to identify faults, maintaining full quality service, collect and compile data for strategic planning and customer upgrades and provides a 360-degree view of the customer to support the customer service team. The robots help the operations team by managing and qualifying alerts, and helps the CSP’s financial and accounting staff by ensuring bills and customer invoices are processed quickly and accurately, all of which improves customer service and eliminates backlogs.
Optelcon is in the business of making companies more profitable by reducing & containing costs, improving efficiency and sourcing more effectively. Through our strategic partners, Optelcon is vendor-neutral, RPA integrator. With over 50 RPA developers and process engineers, we use best practices to help select the best software for the job, document, program, integrate, and update the bots when processes change. We make sure it gets done right.