by Thor Olavsrud

Verizon CIO Shankar Arumugavelu on putting emerging technologies to work

Nov 15, 20217 mins
Artificial IntelligenceEmerging TechnologyMachine Learning

Verizon is transforming its business with NLP, machine learning, digital twin, and augmented reality.

shankar arumugavelu global cio verizon
Credit: Verizon

Shankar Arumugavelu is what you might call a Verizon lifer. He was a director at telecom GTE when Bell Atlantic acquired it in 2000 to form Verizon. Today he’s SVP and global CIO of Verizon, where he’s helping to drive the company’s adoption of emerging technologies like AI and machine learning in service of creating competitive advantage and improving customer experience.

“As we look at emerging technologies, AI is a big area of focus,” Arumugavelu says. “You have disciplines within AI as well, whether it’s NLP or computer vision, robotic process automation, cognitive decisioning, etc. We have work going on across every single one of those disciplines to see how we can leverage that to drive a competitive advantage.”

Arumugavelu and his team evaluate technologies based on multiple criteria, but the ability to drive operational efficiency and to deliver a differentiated customer experience are two of the most important factors.

“When we talk AI and machine learning, these are technologies that have been there for many, many years. It’s just that now the time has come,” he says.

Data is the raw material that powers all these technologies, and Arumugavelu says Verizon has “no paucity” of it. Along with the growing volumes of data, there’s been a steady decrease in the cost of compute, greater accessibility of AI and machine learning research and algorithms, and increasing availability of tools to help democratize data.

“The four factors put together are giving us an opportune moment to really capitalize on these emerging technologies,” Arumugavelu says.

NLP streamlines customer connections

Natural language processing (NLP) is a key example of an emerging technology whose time has come.

 In 2016, Verizon decided to add an NLP-based chatbot to its mobile app. The company had already successfully experimented with an internal chatbot service for its techs called IVAPP Buddy, which gave it the experience it needed to tackle a customer-facing app.

The first version of the chatbot for the My Verizon app was relatively rudimentary. Customers could ask a question and the chatbot would come back with an answer, based on a list of frequently asked questions. The customer response showed promise and the team decided it couldn’t stop there.

“The technology had matured to the point where our goal now has to be to have this virtual assistant support multi-minute conversation completely in an automated manner,” Arumugavelu says. “That’s only possible if the bot is going to be able to maintain the context of the conversation. For instance, if the customer is asking question after question, and a new question relates to something that was asked several steps before, the bot should still be able to understand the context of that conversation.”

From there, the team has continued to iterate on the bot’s capabilities. They were satisfied the virtual assistant could successfully help customers and resolve most issues, but they also saw potential in a secondary role for the chatbot: to assist a live chat agent if a customer decides the virtual assistant can’t address their issue. The next iteration was building a conversational user interface based on voice, an interactive voice response (IVR) system

“Ultimately, you have the same corpus that’s driving this multimodal experience for customers, irrespective of whether they’re coming through a chat or through the IVR,” Arumugavelu says. “It gave us an opportunity to reflect our brand and persona across all the customer touch points and deliver that consistent experience to our customers.”

Arumugavelu explains that customer satisfaction has been good, and the technology has also been successful in containing incoming calls and chats within the automated platform.

“I’m using the term ‘containment’ deliberately, because for a long time, the efficacy of these tools was just measured in terms of call deflections,” he says. “But deflecting is not the point here. If a customer comes to interact with the channel, how are we giving the customers the kind of experience that enables them to complete whatever they wanted to do in that channel without having to go anywhere else?”

The lesson here is to measure the right things. Arumugavelu says that’s the key to understanding the real impact of emerging technologies on your business.

“Look at it from the customer perspective: Were they able to get the things done that they came here to do in an automated manner? It’s not that they hung up from that session, but we also did not see a call back or the customer going to some other assistant channel to ask the same question and get clarification.”

Digital twins boost network reliability

Emerging technologies also have a role to play in helping Verizon plan, build, and maintain its network of wireless towers and global wireline network. The company is using digital twins, which serve as a bridge between the physical and digital domains, providing a real-time virtual representation of physical objects and processes, to gain new visibility and insight into those networks.

“When you plan a network, you engineer the network, you go construct it in the physical world, and then you have to figure out if the engineered view and the as-built view are really one and the same,” Arumugavelu says. “How many antennas do I have? What is the tilt. There are hundreds and thousands of different parameters that go with each of these cell towers.”

Verizon is leveraging drone imagery and computer vision to understand the configuration of its cell sites and then comparing the results with the engineered view to determine whether the two are in sync. If there’s variation, Verizon can make changes at the cell site to bring it back in line. That’s critical, he says, because it can be difficult for a human to analyze all the data from a particular site if it starts experiencing problems.

“This is another area where machine learning is applied to be able to predict, analyze the network performance data, the alerts, and also predict what the alert’s impact would be and figure out the root cause for the incident in the first place,” Arumugavelu says. “If we don’t get that right at the beginning, the second order or third order effects of that are big.”

The digital twins also help Verizon optimize its network performance and preventative maintenance schedule. Any time a change is made to its network, it can see the downstream effects.

“We are taking action before something goes wrong, and that ultimately translates to the reliability of our network,” Arumugavelu says. “That’s a really big priority for us. It’s our crown jewel. Customers come to us for our network reliability, and this plays a big part in ensuring that we are able to deliver on the promise.”

Solving the business problem  

As a CIO, the million-dollar question comes down to which transformative project you should focus on. Arumugavelu says that he always starts with understanding the business and its needs.

“Are we solving the right kind of problems for the business versus a bunch of science experiments? It starts with that,” he says.

Even then, he says prioritizing the use cases is key. Sit with business stakeholders, understand their needs, and help them see the art of the possible with technology.

By way of example, Arumugavelu notes that at the beginning of the COVID-19 pandemic, as many people started working from home and schools went virtual, the reliability of its broadband connectivity became essential to many of its customers. It added many technicians to aid with installs, repairs, and so forth. But the business was wrestling with an important issue: How could it maintain employee and customer safety in those circumstances? Could it do most of the required work without a technician ever stepping foot in a customer home?

“That led to the idea of using augmented reality to provide remote visual assistance to our customers without necessarily having the technician go into the customer’s home and put himself or herself, and also the customer, in jeopardy as well,” Arumugavelu says.

The technician could connect with the customer via mobile app and the customer could use the rear-view camera on their smart phone to allow the technician to see the customer’s equipment. Verizon has since brought that capability into its call centers, so agents can now help many customers solve their problems without sending out a truck.

“It’s a win-win both from a company and a customer perspective,” Arumugavelu says.