Suresh Sreeramulu is the Senior Director at Cognizant Technology Solutions. Suresh has been with cognizant for over 15 years and received his MBA from the Sam M. Walton College of Business in 2019. In addition to his 20+ years of experience in building platforms, Suresh is skilled in setting and driving IT strategy, financial management, and more.
00:09 Matt Waller: Hi, I'm Matt Waller, dean of the Sam M. Walton College of Business. Welcome to Be EPIC, the podcast where we explore excellence, professionalism, innovation and collegiality and what those values mean in business education and your life today. I have today with me, Suresh Sreeramulu, and he is a leader in Cognizant in the retail area and he's in our Executive MBA program, in the second year, and he is an expert in many things around information technology but in particular, he's an expert on AI or artificial intelligence. I remember when Cognizant came to Northwest Arkansas, and you've got more than one location here?
01:00 Suresh Sreeramulu: We do.
01:02 Matt Waller: This is the first time I've been in this particular location in Bentonville, but it's a pretty good sized office. And I know, over the years, I've known a number of employees from here because they've been students and all, but you do tend to hire some really sharp individuals, and I know that's a challenge in and of itself.
01:26 Suresh Sreeramulu: It is, it is, yeah. So we hire a lot of talent locally here and as you know Mr. Waller, we also hire students from U of A as well. The last few years, we have been very successful in attracting talent from University of Arkansas and as well as we go to other schools in and around this region. The freshers, they've always been pretty successful and we integrate them really well with the rest of the teams. In terms of the overall, the teams, again the teams that we have here in Northwest Arkansas, these are folks who have been here for many, many years and they love this place, and I don't see any challenge in persuading people to move to Northwest Arkansas. It used to be a challenge 10 years back, but not anymore. People love it here.
02:23 Matt Waller: Well and especially being up here in Bentonville I could see, I remember it wasn't that long ago that there were very few decent restaurants up here for example, and now there's lots of decent restaurants and more and more ethnic food as well.
02:39 Suresh Sreeramulu: It is. It is. A lot of good restaurants and so it was an interesting experience for me. My daughter when, this was a few years back when she was looking for colleges, we actually went to New York, she was visiting Columbia and she lived in New York before. And before we moved to Arkansas, we lived in New Jersey and so she knows the city well. But after a few years living in Bentonville, she went there and she was like, "Maybe I'll come for college here, but I'm not going to settle here. I love Bentonville. I love Northwest Arkansas. So Northwest Arkansas spoils you because the quality of life is, it's pretty good here.
3:18 Matt Waller: It is.
3:19 Suresh Sreeramulu: There's nothing to complain about.
03:21 Matt Waller: No, no. And before we get into the AI material, how have you enjoyed the executive MBA program in Walton College?
03:33 Suresh Sreeramulu: I've been wanting to do my MBA for many, many years now. I've been in the industry for 20 plus years now. And it's been, doing MBA is one of the things in my bucket list. The critical skill for any knowledge worker now is doing deep work, as well as learning how to learn. I think that's one of the critical skill for any knowledge worker. This is something we taught to our teams and MBA, of course, was an opportunity for me to go back to school, have formal education and train some of those, the learning muscles back, it's been a huge help from that perspective. It's a good distraction because someone like me, think about work 24 by 7, when you go back home, and when you have to do some of these projects and assignments, it takes your mind off from day to day work, and I really enjoy doing it. I mean, of course, you need to manage your time well and... But I enjoy doing it.
04:37 Matt Waller: Now Cognizant has really become a thought leader in many areas of information technology and of course, one that we're talking about today is artificial intelligence, and I've gone to the website and seen a number of articles that you all have created in intelligence. Now, artificial intelligence is one of those areas, I used to really think of it more as being a part of computer science than anything, but it seems like nowadays... Yeah, computer science is a necessary component of it, I suppose, but more and more the real challenges are around usage and application, but what are some of the big challenges you see with artificial intelligence?
05:30 Suresh Sreeramulu: I think the skills are a big challenge, I would say, there's a huge demand. And everyone seem to be hunting for talent. So what we are trying to do is one is, we're trying to bring in lot of external talent, so some of these kids that we hired from college, they have been helping us in a big way. But what... Other than that, I think what we are trying to do is also train our internal talent as well because these are folks who have been doing this technology for many years. So to move into this digital transformation we need a lot of folks who are internal talent, who understand the domain, who understand the clients, who understand the business and if they also acquired this new skill, it makes it easy for us to solve these big problems.
06:22 Suresh Sreeramulu: So yeah, like the Innovation Lab that you see here, this is one of the ideas that we have where people come in, sit here and work on some of the proof of concepts and ideas and stuff like that. And we do a lot of tech talk kind of sessions. We do hackathons. That's a way we're kind of encouraging our folks in order to acquire the skill. So one is understanding the technology, working on these special projects, working on this proof of concepts. The other thing where, at least I'm focused on, is that is, I didn't find the right opportunities as well. To introduce some of these algorithms is something quite interesting and quite fascinating as well. Like for example, when an email client, like an Outlook email client, auto search, auto word correction or completing the word, this is a common usage that you would see in an email Outlook client. But recommending the invitee is based on the history. As soon as you pick one invitee, it automatically populates, like Outlook client in IOS suggests that. I mean, first time when I saw that, "Wow, this is really helpful."
07:40 Suresh Sreeramulu: That's a... It's not a big deal, it's a recommendation engine, but then applying that idea in an Outlook client, at least to me, it sounded quite fascinating. So what we are trying to do is look at those kind of unique areas where your business customers are not looking at it whereas we as a technology team can bring in those ideas and applying those ML solutions.
08:05 Matt Waller: Well, I know... I noticed, here we are in your Innovation Lab, but I know that you've got something called Digital Works where you use an accelerator methodology to IDA prototype and take ideas to enterprise scale at a cost and risk-controlled way. That's very entrepreneurial. So, Cognizant is a big company and your clients, many of them are quite large and yet you're bringing an entrepreneurial kind of approach to your business with your large clients. I would think that would be very challenging.
08:47 Suresh Sreeramulu: Yeah, it is, I think many times, when we talk some of these problem statements, it won't be clear the first time when you have these conversations. So, what we do in this kind of collaboratory kind of set up is that as we bring in our designers, we bring in our, what we call as Cognizant Business Consulting teams, these are folks who understand the domain, who understand these functional areas, and then we bring in the technologies. We bring in all these different teams, sitting with your business customers and technology customers, and do a white boarding on the problem and as well as solutions as well. And when you leave the room, you're clear in terms of what you're trying to solve, but again, until you build a proof of concept, until you go through an ideation phase, you're not really sure you're validated what you're trying to solve or how you're going to solve, right? So that's when it goes into the ideation phase. And again, we come back and sit with the teams, understand, "Hey this is what you're trying to do." So from there, it goes into a mainstream program, so that's how we use this collaboratory space.
10:07 Matt Waller: I think that so many large companies now are being disrupted. You've got clients, you've got lots of clients around the world, but you've got some really large clients that are being disrupted by technology, new technologies. And I know they look to you all to help them in terms of dealing with disruption, technological disruption. But big companies, by their very nature, the bigger a company gets, the more processes that have to be put into place. And the more processes that are put into place and checks, the more bureaucratic it becomes, and therefore, the harder it is to change on a dime. And so, companies now are trying to put into place processes to actually help them pivot and morph as things occur, but I would think your teams that work with clients must have to have a lot of training in how to communicate this and deal with that kind of change.
11:16 Suresh Sreeramulu: See, one of the things which is going on with the whole AI, ML spaces that is, there's a lot of bias that goes in building the models. So when a model is built, there are two things which goes in: One is the data, the other one is the definition of success. The data is based on your past history. And the success definition is, what is the outcome that you are expecting? And this is where the trust and transparency comes into the picture, when people talk about ethical AI. When you talk about data, people often talk about this example, which is this predictive policing. See, when the cops have to monitor say, two different neighborhoods, one is a poor neighborhood, other one is a rich neighborhood. So the data suggests that the poor neighborhood is more prone to crime. That's what the data suggests to you. Then what you do is you do more policing in that space, then every crime activity gets reported, there are actions taken and then it goes back into the feedback loop, into the data again, saying that, "Hey, between these two neighborhoods, this is a neighborhood in which there are more crimes."
12:36 Suresh Sreeramulu: So it's like a reinforcement that happens and that's where the data sometimes could be biased because you keep taking those actions and which reinforces, even if it is not true, it reinforces that point again and again. To summarize this data and the outcome, those bias that exist in some of the models that goes in. And the last one is of course, transparency. You want to go beyond the black box, you want to look at some of the models, you want to look at some of the factors that goes in. If you are a consumer and your bank loan is rejected, you want to know why your bank loan is rejected. So there's a lot of transparency also needs to be in there. And of course, people talk about these old college rankings and how people game the system. This whole US news and report college ranking system. So again, the balance is that there are some problems where the end consumers need to know what goes into the model, but there are certain use cases where it's better kept off as a black box.
13:48 Matt Waller: Well, Suresh, thank you for taking time to do this podcast with me, I really appreciate it.
13:54 Suresh Sreeramulu: Thank you. And thanks for coming down here and it's a great pleasure talking to you.
14:00 Matt Waller: Thanks for listening to today's episode of the Be EPIC podcast from the Walton College. You can find us on Google, SoundCloud, iTunes, or look for us wherever you find your podcasts. Be sure to subscribe and rate us. You can find current and past episodes by searching "beepicpodcast", one word, that's B-E E-P-I-C podcast. And now, Be EPIC.