Kevin Gray:
All right. Hi, my name is Kevin Gray, publisher over at Fierce Wireless and Fierce Telecom. And today I am with Arvind Rajagopalan, the global head of data engineering and products at Verizon. And I was thinking, Arvind, the best way to get us started here just so everybody in our audience knows everything about you. If you could just tell us a little bit about your current role at Verizon and your career journey and how you got here.
Arvind Rajagopalan:
Oh, absolutely. Glad to be here. Thank you, Kevin. My role at Verizon is focused on engineering, analytics and products, with a use of data and AI to drive outcomes such as growth and optimization. I manage a large globally dispersed team that focuses on designing and building data and analytics pipelines, products, and delivering insights. Over the last couple of years, we've been maturing our engineering practices as well. My team and I have focused on various vectors of growth for Verizon, including 5G, Fixed Wireless Access (FWA), Internet of Things (IoT), or Multi-access Edge Computing (MEC) by building data products that enable various functions such as sales, marketing, and operations. If you think of, or ask me question around the, how I kind of landed in the career. It's an interesting journey that I've taken. Growing up in high school, science and math were my favorite subjects.
Arvind Rajagopalan:
And the first time, interestingly enough, I touched a PC was in the senior year of my high school. And since then I've not looked back. I've always been curious about everything and trying to figure out how things work, especially using data experimentation. That's been the connecting wire tissue, if you will, across my entire career. I took the less traveled path of statistics. This is way before it used to be. It's kind of really cool now, but I took it way before it was actually cool. And I went on to do a masters in information technology. And I've been with Verizon since 2004, lucky enough to get exposure to the various areas, business units across the board. And since 2014, over the last eight or so years, I've been focusing on building data and AI teams that leverage data to drive all aspects of the business across Verizon.
Kevin Gray:
Great. So almost 20 years then, if I'm doing the correct math there. That's a long time to be over there at Verizon. It seems you've probably seen quite a bit over in that timeframe now. So, tell me about this then. Right? Where did data products fit within Verizon's current and offerings? A lot of those that you just mentioned, right? And what are the business outcomes that they're enabling.
Arvind Rajagopalan:
Oh, that's a wonderful question. Data products really bring the power of curated data and machine learning. For example, propensity scores, et cetera, to life. The reason why they're considered products is because they have a vision, a life cycle, and a roadmap, just like physical products that are being designed and created. So as we go through this, the data product journey, we also are looking at monetizing a lot of them, both internally and externally, and we do a phenomenal job at it. Reusability drives a single source of truth and democratization of data to maximize investment. That is another one of the key tenets of data products.
Arvind Rajagopalan:
The data products that we build are driving key business outcomes, such as growth, from a fixed wireless standpoint. One of the examples there. I'll give a couple more instances. One of the other data products that my team has launched, helps strategy and commercial teams decide on what and where to sell Fixed Wireless Access (FWA). In addition, it also helps about pricing decisions, as well as promos and offers. The same data products also help marketers create audiences and run campaigns effectively. And it just doesn't stop there. The product also helps various sales channels hone in on maximizing sales while helping operations keep call-in rates low. So, this is a great example of how a data product is reused across the board and is being used by multiple teams across Verizon.
Kevin Gray:
Great. So, those are a really good summary in the way that a lot of those data products are used. Right. But I was hoping maybe just to take a step back there as well and help just clarifying for our audience what those data products all are. Can you tell us a little bit more about the types of data products and the ones that you were working with?
Arvind Rajagopalan:
Oh, absolutely. We leverage billions of signals from the various customers, and the data and every touch point that we collect on, combining that with the various third party data attributes that we also bring. And we create bespoke data products. Focus being on creating data products to provide a holistic view of prospects, the market as such, customer journeys, network devices and promotions to name a few. These are good examples. In addition, we are also starting to leverage data products as a foundation to fuel our digital twins, among other use cases, which is extremely exciting in a way to answer some of the key business questions that are out there.
Kevin Gray:
Time for two more questions here. One that I wanted to make sure that we get to. I feel we live in this world now, where there's so much data that's out there, it probably presents quite a few challenges for you and your team as when it comes to all these specific data products that we're talking about here. What are some of the major challenges that you'd say you face in your current role in dealing with all this?
Arvind Rajagopalan:
Oh, you're right Kevin. We look at it as opportunities, how we can improve on. A couple of them. Legacy technical debt and a dynamic ecosystem are two of the major opportunities that our teams have taken head on. We have a sizable investment in modernizing the platforms, building industrial scale systems for data AI and all branches of AI. Machine learning, computer vision, NLP among others, as well as the engineering practices that go hand in hand. As we build modern platforms for the size and scale of Verizon, we are the largest provider, wireless provider in the US, and a global leader in connectivity services as you may recall. We are also addressing the technical debt as we go into taking the opportunity to build real-time systems, to solve the multitude of use cases that require data and to drive real time interventions with personalized experiences and offers. My team works on some of the cutting edge to drive outcomes for Verizon.
Kevin Gray:
And the last question that I have for you here, which will be a particular interest to our audiences continually looking for stuff on our site and everything like that. This is a really fast moving space right now. You mentioned things like AI, digital twins and everything like that, right? How do you keep up with all of this, and all the industry trends and just best practices for your team in general?
Arvind Rajagopalan:
Yeah. As I mentioned, I'm a curious cat. So, I'm ever curious to learn things about new things, new trends, unique ways other businesses are improving their processes using data and AI. So, I tap into the various technology resources, such as technical forums, advisory councils, and the partnerships we have in place. A growth mindset, in my opinion, is key to learning and staying humble. The teams are energized and empowered to experiment with key learnings from both successes and failures, which is very important. Verizon also provides a vast array of resources to learn from, such as training opportunities, partnership, and collaboration in tech forums, as well as this spirit to innovate which propel propels us forward every day.
Kevin Gray:
Great. And well, that is a great way wrap things up, I think. Arvind, thank you so much for your time today.
Arvind Rajagopalan:
Thank you for having me, Kevin. It's been a pleasure.
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