Description
In this insightful episode of The Curiosity Current, host Stephanie sits down with Subhasish Nanda, Director of Customer Insights and Analytics at Verizon, to explore the evolving landscape of data-driven customer retention. Discover how AI and analytics are revolutionizing customer experience, why traditional loyalty programs are being reimagined, and what really drives customer decisions beyond price. Whether you're a business leader, analytics professional, or curious about the future of customer engagement, this conversation offers valuable insights into how major telecom companies are leveraging data to build stronger customer relationships. Tune in to learn why understanding your product and customers remains paramount even in an AI-driven world.
Transcript
Subhasish - 00:00:01:
So if you are building dispute with one of these or big safety companies, that can be handled, right? What they can compromise is the availability of the network, right? We'll pay off it. And we know, like, hands down, there is one network in this country that, like, trumps all of them when it comes to reliability of it. And that's where we kind of are. And what does network slicing truly offers is with just a product revolution on top of it, I think is the key. Objectivity, to some extent, we are all human, we are, like, subjective to our thoughts and biases. But being objective, trusting the data a bit more. However, when I joined around eight years ago, we used to have a, we have to go to our central offices just to see how the cable is laid out, how the machines are. So you are not looking at a product in a spreadsheet or somewhere. You know actually how the product works.
Stephanie - 00:00:58:
Hello, fellow insight seekers. Welcome to The Curiosity Current, a podcast that's all about navigating the exciting world of market research. I'm Stephanie Vance.
Matt - 00:01:08:
And I'm Matt Mahan. Join us as we explore the ever-shifting landscape of consumer behavior and what it means for brands like yours.
Stephanie - 00:01:15:
Each episode will get swept up in the trends and challenges facing researchers today, riding the current of curiosity towards new discoveries and deeper understanding.
Matt - 00:01:26:
Along the way, we'll tap into the brains of industry leaders, decode real-world data, and explore the tech that's shaping the future of research.
Stephanie - 00:01:33:
So whether you're a seasoned pro or just getting your feet wet, we're excited to have you on board.
Matt - 00:01:38:
So with that, let's jump right in.
Stephanie - 00:01:42:
Welcome to The Curiosity Current. Today, we're thrilled to be joined by Subhasish Nanda, Director of Customer insights and Analytics at Verizon. With a wealth of experience in leveraging big data, Marketing Analytics, and machine learning, Subha has led groundbreaking customer retention strategies at one of the largest telecom companies in the world. Subha's career spans various leadership roles in strategy, business transformation, and marketing science, where he's been at the forefront of Verizon's evolution and delivering exceptional customer experiences. In today's conversation, we'll dive into how technology and insights come together to drive customer retention and loyalty, and how brands can stay ahead in this ever-evolving landscape. Subha, welcome to The Curiosity Current.
Subhasish - 00:02:27:
Oh, thank you, Stephanie. Thank you for having me.
Stephanie - 00:02:29:
Yeah, we're excited to chat with you. So just jumping right in, if I can, in your role leading customer insights and analytics at Verizon, how has the intersection of data science and customer insights evolved over the years?
Subhasish - 00:02:44:
Well, I've been in this space for close to seven years now. And we could see oftentimes in past. When I say in past, not even like five years ago. Data science and analytics used to be a team in marketing. It's just as a team. Right now, they're the driver of marketing operations. So we can focus on retention, but there is both side of it too. But in both the cases where marketing was mostly driving the operation ago, we had the traditional marketing managers, strategists. They usually believe on certain kinds of programs and then come back to and tell the data guys to tell what they're looking for. Whereas it has completely pivoted to a point where we start with analytics, understand the market space and standard customers, what you're looking for. And then most of the time, even the strategies are driven by this. So we probably over the next few questions, interactions, we'll go over and set in definite cases. But the head of our marketing operation at this point is the person who actually drives the analytics main site. So it's data being most of the strategy, most of the operation even is being driven by the insights. Rather than insights being playing as just a hitting block.
Stephanie - 00:04:05:
Got it. So almost bringing that bottom-up approach to what the strategy should be, rather than taking that top-down a priori, like, we have an idea, right?
Subhasish - 00:04:15:
We move from more anecdotally thinking, anytime we have a question, I feel like no customers are looking for this. We move from there to let the data speak what our customers are truly feeling, right? Both from predictive side and analytics, right? So more, both on analysis going back three years, four years and trying to understand how our customer behaving to what we think this particular scenario or this particular customer will behave.
Stephanie - 00:04:44:
Got it. Can you talk a little bit about, you've talked about how AI and machine learning are sort of, you know, part of the world that you work in. How do you use these technologies in your day-to-day work or these approaches?
Subhasish - 00:04:58:
I don't want to really mix data analytics or data science with AI. AI, more you are looking at taking certain actions. But the big part that existed and even without the generative AI was the data analytics space. And that evolved first, right? And that's what I usually work on is very focused on the data analytics or data science side. And again, we have evolved in terms of how advanced algorithms have become, how advanced our processing has become, right? So if you are running data models in an old, like a data suite, you have limited capabilities. Versus if you are running it on GCP or AWS, depending on what you prefer, you get more access to newer technologies, newer platforms, newer more complex algorithms, actually coming up with your predictive models. Same thing on analysis side, right? So traditionally, we have gone with, say, Tableau or PowerScale, or PowerPoint different visualization analytics tools that historically has been used but moving from that to something like Looker or something like AI-powered analytics where you have the data more of a horizontal data sets that were built out very denormalized sets and you can ask independent questions rather than having built a Tableau view and looking at that static set you can actually create your what do we have Tableau Reports right on the analytics side we have a Tableau report so that we can look for anomalies we can look for trends and things like that whereas we have now tools available to us where they will do the anomaly detection for us because we get limited by what we can see or how we synthesize the report right we are often our ceiling is to the point we can analyze that particular reporter that we're looking at whereas there are AI models who can scan through the data scan through the report and give us the insight that the questions that we might not might not have been asking I think that's the key distinction between just the P, P or, as I said, like two stages. One was just processing the volume of data and the complex ways of processing the data. Then on the analytics side, the new tools that we have more on interpreting those data to more, what do you call, systemic way. Rather than, you know, depending on a particular leader's interpretation of the data.
Stephanie - 00:07:28:
Definitely. So I'm curious, especially with that, like you said, with generative AI being used more to like interpret or to spot those trends and see those trends maybe before you. What does that free you up to do then with your time? Like how have you, what does that level you up to do?
Subhasish - 00:07:45:
Oh, first of all, it's not just freeing up the time, it's actually doing a much better job than-
Stephanie - 00:07:50:
Job. Yeah. Great point.
Subhasish - 00:07:52:
Yeah. No matter how objective we want to become, by the just human nature, we have certain beliefs or certain... I'm missing the word for it. But preconcept, preconcept knows-
Stephanie - 00:08:05:
Like, I see. Yeah.
Subhasish - 00:08:07:
I'm looking at a report. I'm trying to find something that I know is there, even though it might not be there. But whereas the AI platforms are doing a better job doing that synthesis with the true objectivity, right? That's a better job that they're bringing in the first place. Second, I can then focus on what does it mean?
Stephanie - 00:08:26:
Yeah.
Subhasish - 00:08:27:
The part of it is, okay, we have a trend in certain customer segment who either know higher churn or higher growth. What particular data points, that's the trend the AI engine tells me. And now I can focus on a couple of things. How do I communicate that upstairs, right? To put it in the hand of the real decision makers. And second, I contextualize them, right? And hand it over to my marketing partners who can come up with ideas on how to address them. But now I take advantage of it, depending on what you're talking about. So that's like the true value addition on top.
Stephanie - 00:09:00:
Yeah, that makes a ton of sense. To switch gears a little bit, Verizon has made significant strides with its customer-first strategy. I think it's pretty well known, especially like with the introduction of the groundbreaking initiatives like three-year price lock and free phone guarantee. How do customer insights drive the creation of these types of offerings? And what impact have they had on loyalty and long-term retention for Verizon?
Subhasish - 00:09:25:
Those couple of programs that you mentioned, they were driven by certain insights and looking at going from two years to three years. What does it mean? But it also had some strategic ideas behind it, right? So you look for not just, you know, why you are. And let me give an example for two years versus three years. There was a time when Apple, every new version of Apple, has this huge drive from people. People used to like stand in queue for two days, three days to get a new iPhone, right? And Samsung or other Android devices were like far behind in terms of the technology. And they were, even when they evolved, devices used to last for like a year, two years before they become obsolete. That's no longer is the trend, right? People hold on to their devices longer for a couple of reasons. It's almost, I want to say that plateaued in terms of the, like, we have maximized to the point. Like, right now, all our phone delivers us Ultra HD screening, right? All the stain qualities and all that. Even if they increase that by a bit much tomorrow, eyes and mind able to interpret the difference? Probably not. Like, we have reached the diminishing return of investment in terms of the investment into the devices themselves. So, for one reason, that they're actually much better, like, durable. If you can look at the screen, the construct, the physical construct of the phones are much better today than they were, say, five, six years ago. And software and technology-wise, they have kind of reached the point of low marginal return on investment, right? When you are seeing those two trends, and we identified that a few years ago, so people are holding on to their devices. Why two-year device law was there before? Because every two years, people used to upgrade their devices.
Stephanie - 00:11:13:
Yeah.
Subhasish - 00:11:14:
So, instead of two years, if you give it three years now, you know, you get it. It works out well for everybody because, again, you are not looking to upgrade your device in two years. Can hold on to a device, you get a better price for it, right? And it's actually financially works better for us too, because again, devices are expensive for carriers. So that's like one of our bigger cost base, right? So if we can extend the device for the customer, we get them for three years and then customers pay much less for it, right? And we can build on, or probably we'll get to it, like how phone line itself has become kind of a commoditized. So you look for services on top of it. So the longer duration you are with the customer, you understand them a bit better, and you can tell them what this customer is truly looking for. Phone is mean to their need, and their need could be much more than just having a telephone line.
Stephanie - 00:12:08:
Yeah, absolutely. It's so interesting to hear you talk through that. I worked in telecom. I actually worked for a mobile manufacturer. It's been about 10 years. And at that time, it's so different than what you're talking about now. You're right that like every year, just the iterations that were happening were large and big and would take your phone so much further. And so even waiting those two years could be kind of brutal, but it doesn't feel like that anymore at all. So it totally makes sense.
Subhasish - 00:12:37:
The simplest way I think about is like I often try to put myself like what I used to do, like early 2010s, 2012s, 2014s. I was upgrading my device almost every day.
Stephanie - 00:12:48:
Yes, yeah.
Subhasish - 00:12:49:
Yeah. That's how much I use my phone versus, you know. The same thing we'll talk about maybe network technologies, right? The change, the way it applies to certain fields, varies, right? So where is it like... I don't want to go from like 4G LTE to 5G, 5G C-band to ultra-wideband. Just for a pure consumer's use of the phone does not change as much. Again, we work in B2B space. There are like thousands of use cases for 5G ultra-wideband in business, B2B, large-scale corporate, right? Public sector. But for consumer, LTE is many times more than enough for their mobile browser.
Stephanie - 00:13:34:
Yeah, that makes sense. So customer expectations, this is one thing we wanted to chat with you about, are, you know, and it's relevant to the conversation we're having now. Maybe not for phones, but expectations are constantly shifting, especially in industries like telecom. How does Verizon ensure that its retention strategies remain ahead of evolving demands? And do you use predictive analytics? I heard you talk about them a little bit earlier to kind of anticipate what these future behaviors are going to look like.
Subhasish - 00:14:06:
To some extent. I wish we do a better job of this. Oftentimes with any large corporation with P&L goals, quarter to quarter, month to month, you get both down on how can I meet my target for the month? How can I meet my target for the quarter? One of my personal push has been to our marketing and sales leader, especially in small business, is to look at least six to nine months ahead so that we don't get into this vicious cycle almost every two weeks. But yes, there are parts of our team who are focused on looking for trends more on a longer term. So can I look at a customer, nine months ahead, and tell what this customer could potentially do when their next contract renewal is coming up? Or when that device plan, the loan payoff ends? Or when the company or the customer is going to go through that? Some middle-sized companies and definitely all the big companies, they do this periodic rebalancing of their accounts. So when they go through those cycles, what are they going to make those decisions? So we use a lot of past data, some market indicators, some fields we are better in predicting, some places are not. At least in public sector, this year has been tough, right? Federal government with a lot of things and all that.
Stephanie - 00:15:30:
Yeah.
Subhasish - 00:15:30:
Those unpredictable indicators, we can't use them.
Stephanie - 00:15:33:
Makes sense.
Subhasish - 00:15:34:
There are some macroeconomic factors, we can't take them. And maybe we'll go to a point where I don't know how to frame this, but we try to. We try to put customers in segment and try to behave, like predict what they can do. That's the challenge with business, B2B business, right? So I often say consumer, our Verizon consumer business, they're like five times bigger than us in terms of the revenue. 70, 80 times bigger than us in terms of customer base.
Stephanie - 00:16:02:
Yeah.
Subhasish - 00:16:04:
But we are probably 100 times more complex than that.
Stephanie - 00:16:06:
100%, yes.
Subhasish - 00:16:08:
As the, building a true predictive model for a complex business, and I'm not talking about mom and pop stores, because many of them do behave very similarly. So that small business segment, where we can use, some predictive behaviors we do. And they kind of behave close to consumers, and we do use their past performance as similar, like similarity analysis we do, those to predict what they could do when the my those milestones come. Right? I said contract expiration date is a milestone, loan pay after it is a milestone. We'll go through those low, you believe it or not like tax return is kind of-
Stephanie - 00:16:47:
Interesting. Yeah, yeah, yeah.
Subhasish - 00:16:48:
We look at those milestones and try to predict for these accounts, these customers should behave. But when it comes to anybody I'm talking, like 50 plus lines customers, we very account best focused at that point. Because they're kind of looking for, they're kind of unique in their own way. So we can't really start putting them into buckets. There are certain drivers that will impact, right? We start looking at competitors. What's our blue guys and purple guys are doing, right? So we have to look at that doing. And some of their indicators will drive them. But most of inside, looking at our own existing customer base, it has to be a little more hands-on for all the larger guys.
Stephanie - 00:17:29:
That totally, that makes sense. And I have to say, I have that same experience too with, you know, I work on the supplier side with larger clients in a B2B environment. So I know exactly what you mean. They're all different in their own ways. I'm curious, what do you think, you know, being so close to like customer analytics and, you know, especially B2B customers and the way you think about them, what are the biggest myths that people have, whether either in your industry or just kind of across the board about customer behavior that you feel like companies hold on to that you might challenge? Does anything come to mind for you? I like that.
Subhasish - 00:18:09:
We need it right now, like there is this idea that all customers are price sensitive and all they're looking for is price. All they're looking for, give them a discount, they'll stick around. Or no, they are moving to our competitors because they're offering better price. Most of the time it's not. Some of them are, but most of the times they're not. Customers do look for value and value is an object much larger than just the price time, right? So Verizon's people stick with Verizon for value, like their perceived value. And I say perception is reality. Many times I can give you a small example. We see certain segments, certain customers start disconnecting, right? And they're disconnecting, they're disconnecting, they're joining and they're putting out the lines to our competitors who are giving this device buy-by, loan pay-off programs. You owe Verizon $800 on your devices.
Stephanie - 00:19:01:
Yeah.
Subhasish - 00:19:02:
We pay $100 for you, join, put your lines to us, right? We pay $100 for you, join, put your lines to us, right? Your knee jerk reaction to that would be, oh, if we can pay off their loan, give them an early upgrade, they will probably stick with us. Right? Wrong. Because they're not putting out because, you know, they got $800 free dollars or they want to upgrade their device. As we just talked in the beginning, nobody is in a hurry to upgrade their devices. They love their devices. They want to hang on to it. Right? So they're not in a hurry to upgrade their device. They're not in a hurry to move to a different carrier. What their hurry of is getting out of Verizon. Why? In many times we found because of certain customer experience. Many experiences even go back to when they first joined or first added these lines. Many times that first impression is everlasting. We had issues in customer onboarding. We had issues in bill gaps and understanding the bill. The first bill, you see the discount, don't see the discount and all that. Sometimes the promos that got applied. A lot of miscommunication in the customer experience when they join, when they go through some of the milestones in the customer lifecycle with us. And hold on to those. When they get piled down, they hold on to those. And all they're looking for is somebody to free them off their contract. And they would have ported out after the loan payoff happened. Then somebody came and said, I'm going to pay off your loan. And they said, okay, sign me up. That customer experience piece is the key driver for many of the customers. So that conception that, okay, if I give them promo, if I give them discount, they will stay. I think our customers are smarter than that. Most of the times, if you make their life simple, we're talking about small business owners. We're talking about people who are making thousands of decisions every day. If we can make them make one less decision. Like porting out a carrier is not an easy thing. It's a hassle.
Stephanie - 00:21:03:
Right.
Subhasish - 00:21:04:
Along with everything they are going through. So we can make their life easy by, I often talk like there are three ways of looking at it. First, we'll study the customers who left us and go back. look like since the day of that inception, study their journey and what could have triggered. Right. And then you look for those triggers. Could we have addressed them? Then what we have started doing is we have identified those infraction points and have programs with our digital engagement, with our customer service organization. Start engaging with the customers and solving that problem in time. Then the most strategy is looking at fundamentally what is the problem. With our tech stack is the problem. With our business process is a problem. Our product pricing is a problem. Whatever it is, right, look at strategic changes to make those. So those are like three stages. You have to look at these problems and not just look. My team manages all the loyalty offers and all the discounts and all that. And we see there. It doesn't make a marginal defect if we give 20%, 30% discounts to the customers. Those who are going to leave, they're going to leave.
Stephanie - 00:22:17:
That's such an important learning. I mean, because it sounds like when you do the root cause analysis that, like you said, it's not about the price at all. It's about some unhappiness in their experience that needs to be addressed directly rather than through a discount. Right. And then you leave your money on the table on top of it.
Subhasish - 00:22:36:
More importantly, that's always has been Verizon's brand. Right. We don't do it. We are a premium service provider for a reason. For the quality of service we provide, for the kind of network we have.
Stephanie - 00:22:47:
Yeah.
Subhasish - 00:22:48:
So you don't, as our brand, protecting our brand, we don't want to get into that care.
Stephanie - 00:22:53:
No, yeah.
Subhasish - 00:22:55:
With that kind of competitive.
Stephanie - 00:22:57:
Totally makes sense. Well, you mentioned some segments a little bit before talking about, you know, the uniquenesses that come with like larger enterprises. I'm curious about another audience that you serve. And I'm thinking about the introduction of Verizon's Frontline Network slides for first responders. It seems like it really exemplifies how Verizon has advanced its tech offerings with customer centricity in mind. How do you approach customer retention in these highly specialized markets like public safety, where service needs and expectations are really different from like general consumer behavior?
Subhasish - 00:23:34:
If we do the market sizing today, like market share, Verizon is like hands down, leads when it comes to public safety, both in Fed Draven. And public safety in general. But it's, as I said, it's a lot of wide-globe approach. But even going down to, if you're talking about public safety, their customer service is paramount always, but their trust in the technology and trust in the network is even more important.
Stephanie - 00:24:04:
Sure.
Subhasish - 00:24:05:
We do, I'm not saying, I'm not belittling, you know, if we have bill disputes or if we have credit disputes with a police service, you know, New York City. I'm giving just example, right? Hypotheticals, yeah. So if you have billing disputes with one of these, you know, public safety companies, that can be handled, right? What they can't compromise is the availability of the network-
Stephanie - 00:24:29:
Sure.
Subhasish - 00:24:30:
Of it. And we know, like hands down, there is one network in this country that like trumps all of them when it comes to, the reliability of it. And that's where we kind of, and with what does network slicing truly offers is, with just a product revolution on top of it. Right. So, you have pretty good network to start with, now you are prioritizing, you know, certain bandwidths, certain segments, for explicit use.
Stephanie - 00:24:57:
Yeah.
Subhasish- 00:24:57:
And again, all our competitors have started doing that too. But I think, we are far ahead in terms of implementing the network slicing, for public safety. And come our customers know that.
Stephanie - 00:25:10:
Yeah, yeah. Makes sense. I am curious about something. As we're entering this area where traditional concept of like loyalty programs and retention strategies. You know, that's the current world we live in, but we're approaching this world where AI and automation are really going to be at the forefront. Do you feel like in this sort of future state that we are rapidly heading towards that like loyalty programs and retention strategies are going to be far more personalized, like hyper personalized and individualized?
Subhasish - 00:25:44:
Yes, absolutely. Can get a little creepy. I think I'd be...
Stephanie - 00:25:49:
Oh, yes. Talk about that.
Subhasish - 00:25:51:
Just thinking of ideas, right? We're talking about customer flows and they're clicking on this button and we kind of anticipate that, okay, probably the customer is heading towards this way, right? And then start offering them certain, you know, experiences that we predict. Like the capabilities exist, but it's a fine balance between, we do that today. In a moment, you go and, if I can say this, but I think it's common, right? So if you are a subscriber on anything, I'm not talking Verizon phones, right?
Stephanie - 00:26:24:
Sure.
Subhasish - 00:26:24:
And you want to unsubscribe that particular service, what is the first thing you do? You go to the payment side and you sign off auto pay, right? If you have an auto pay, you want to turn off your auto pay and then go cancel the service, right? They might have charged you for last month or next month, but they won't charge you anymore because you have canceled the service and also just to be safe, you took yourself out of the auto pay. So we look for people who's, you know, you're browsing the auto pay button or you are doing the auto pay sign off. I say, okay, that's a trigger. Like, you know, we have AI kind of observing that and then say, okay, if this customer sign up on auto pay, go and study what its account looks like and what can we offer them. This might be a signal for them, you know, moving on.
Stephanie - 00:27:03:
Yeah.
Subhasish - 00:27:04:
You turn off a feature, right? If you're a price sensitive guy or your business is going to downturn and you bought tons load of an app, say you're a consumer, you're buying like Disney+ bundle, Netflix bundle and all that. You go to what as an accountant and start signing off those, disconnecting those bundles. If you're disconnecting those bundles, that should trigger that, oh, this customer might become price sensitive for some reason.
Stephanie - 00:27:26:
Yes.
Subhasish - 00:27:27:
Let's offer them some other price plans that might be better for them and it will pop up like as they're browsing.
Stephanie - 00:27:32:
Yeah.
Subhasish - 00:27:33:
To some extent, that's good. At some point, people are going to be like, are you going to, are you then watching my every step on what I'm doing?
Stephanie - 00:27:41:
Right, right, right. It's a fine line, right? Yeah. It's relevance without creepiness, right?
Subhasish - 00:27:49:
So we do talk about like whenever such an idea comes, we do have a thought group to kind of filter it down and say, okay, what does the customer look like, right? What's the customer experience is going to be so that it does not come to a point where a customer feels uncomfortable interacting with us.
Stephanie - 00:28:06:
Makes sense. Yeah. Well, Subha, to kind of wrap us up, there's a question that we always like to ask our guests. We have a lot of, you know, folks who are getting, you know, master's degrees in market research or just starting their careers in analytics. And so we always like to ask our guests who are typically have been in the field for a while. Looking back on your career, is there a piece of advice that you would offer to somebody who's just starting out in the field of, you know, either customer insights, customer analytics, something like that?
Subhasish - 00:28:37:
I don't know if I'm the ideal candidate for it because I accidentally landed in this row.
Stephanie - 00:28:41:
I think like that's true of 80% of us. So no, you're relevant still.
Subhasish - 00:28:46:
So at the same time, I think, who is that? Einstein or somebody said like, you know, curious mind, analytic. You just need to be, have that curiosity, I think is the key. Objectivity, to some extent, we are all human. We're like subjective to our thoughts and biases. But being objective, trusting the data a bit more. But more importantly, I think no matter, and that's probably it helped me because I came from, for a while I was in technology. So I understand how platforms and tech stacks work. And I was actually in CX, so like CRM solutions, development and all that. Then I worked quite a bit in business transformation. And that business transformation, but it was very aligned towards product, network, like understanding what we're selling, understanding who our customers are, does not require analytics, right? And if you're just, I have met a bunch of people like really exceptionally talented, very smart, comes with like PhDs. They can teach data science in MIT for all that matter. But it's a big, but it's understanding your customer, how they behave, understanding your business model, what you are selling, right? So the first thing I say, like if I'm working in this, especially in the business operation side, I need to know the product I'm selling. I need to know the people, my product too. No matter what operation I am in finance, I am in business transform, I am in a product, does not make what my role. And try to do that with my team is understand the products that we're selling, understand who you are selling to. Then comes the functional role, right? You can't, irrespective of you want to be a data analyst, you want to be a business analyst, you want to be an architect, you want to be a data scientist. Those are just tools. Those are mechanism, mechanics that are going to help you with the job. First thing comes is understand your product, understand your customers, and then see how your skill sets are going to fit in there.
Stephanie - 00:30:43:
No, that is excellent advice. And it also just reminds me, I'm sure you think about this a lot too, but just that you have to cultivate an orientation towards outcomes over like approaches, right?
Subhasish - 00:30:56:
So when I approached my SVP of this organization that I'm part of right now, I approached him five, six years ago on like, where do we move next? I was part of this central business transformation organization, which was a lot of ideas and understanding the product and coming up with concepts. He said, Subha, you need to spend some time in the operations because operations, the results are the key. Like you have a number, you have to hit that number. How am I going to hit that number? You are not coming up with three year project plans, right?
Stephanie - 00:31:29:
Yeah.
Subhasish - 00:31:29:
Like I was like, sometime I mentioned it. We are in a two weeks to one week cycle right now. We have weekly KPIs that we need to hit.
Stephanie - 00:31:37:
Wow.
Subhasish - 00:31:38:
What does the number look like? So sometimes it gets too granular, right? That, I like to dedicate at least six to nine months, not three years, but six to nine months.
Stephanie - 00:31:49:
Yeah.
Subhasish - 00:31:49:
But. Operations, I think it goes back to, as I said, knowing your product, knowing your customers. You have to work in operations so that you know, you get the hand, you know, pulse to understand how it's truly moving. How do we even sell things, right? We have this getting out to market operations. So we like I will visit a retail store here somewhere. I will see how they're using, what's the customer interaction will look like. Like visiting a field is kind of a mandatory write-up process for people in Verizon. You are in any kind of leadership role. You need to know the market. When I joined around eight years ago, we used to have to go to our central offices just to see how the cable is laid out, how the messes are. So you are not looking at a product in a spreadsheet or somewhere. You know actually how the product works.
Stephanie - 00:32:39:
It's not theoretical. Yeah, like you know. I love that.
Subhasish - 00:32:43:
Right. You know, when you talk somebody about network slicing, you at least know what is network slicing. It doesn't have to be smart, right? So, yeah, I think that's very much important. And I look at my SVP, who is like 25, 28 years in Verizon. He knows inside out.
Stephanie - 00:33:00:
Yeah.
Subhasish - 00:33:01:
Company. So that's what I think any young leaders would be aspiring for.
Stephanie - 00:33:06:
Makes a ton of sense. Well, Subha, I have to say, we appreciate your time so much today. It's been great to learn about what you're up to at Verizon. Clearly, a lot of good work happening there these days. It's been really fun conversations. So thank you so much for joining us.
Subhasish - 00:33:22:
Well, thank you very much, Stephanie, for having me, and I really enjoyed the time.
Stephanie - 00:33:28:
The Curiosity Current is brought to you by AYTM.
Matt - 00:33:32:
To find out how AYTM helps brands connect with consumers and bring insights to life, visit aytm.com.
Stephanie - 00:33:38:
And to make sure you never miss an episode, subscribe to The Curiosity Current in Apple, Spotify, or wherever you get your podcasts.
Matt - 00:33:47:
Thanks for joining us, and we'll see you next time.
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