On this week’s episode of Fortune‘s Leadership Next podcast, co-hosts Alan Murray and Ellen McGirt talk with Tiger Tyagarajan, CEO of Genpact, about the lessons he learned working with GE CEO Jack Welch, why he thinks artificial intelligence is still in its infancy, and the current "nuanced" state of globalization.
Listen to the episode or read the full transcript below.
Transcript
Alan Murray: Leadership Next is powered by the folks at Deloitte, who, like me, are super focused on how CEOs can lead in the context of disruption and evolving societal expectations. Welcome to Leadership Next, the podcast about the changing rules of business leadership.
I'm Alan Murray, and I'm here with my amazing co-host, Ellen McGirt.
Ellen McGirt: Alan, Alan, it's so good to be with you.
Murray: And it's the second to last episode of the season, Ellen. I can't believe it. We made it through the year.
McGirt: I know. We did. I wasn't sure at some points that we were going to make it through but it has gone by so fast.
Murray: It's so much fun to be able to have this opportunity to talk to the people who are leading the most successful companies in the world about what they're seeing, what they're doing, where they're going. And today's episode was a great example of that. We talked to a CEO who may not be a household name. His name is by the way, Tiger Tyagarajan. He is CEO of Genpact. Genpact isn't probably top of mind for most people, but it's a professional services company that spun out of GE quite a long time ago and has become one of the world's leaders in in helping companies go through digital transformation.
McGirt: And he's a fascinating guy. He's been the CEO of Genpact since 2011, I believe, and he's done a lot during this time. But I'm going to ask him about what the company did during COVID. Because if there was ever a use case for caring about your employees, relentlessly caring about your customers and using technology to transform things, it's the kinds of work they were able to do making sure, for example, the vaccine was safe or that people had enough ventilators when they needed them.
Murray: You do that Ellen and I'm going to ask him about artificial intelligence, A.I., because over the course of the last five or six years, he's really been one of the people that I turn to get some guidance on how the great promise of these new technologies, how it's really been applied, and where it's really being applied in business and where it's falling short.
McGirt: So it's good to have friends who are in the know and we're going to hear more about his leadership journey and philosophy. He started out as a sales manager in Mumbai, India to become a CEO of a publicly traded company.
Murray: Yeah, good guy, great leader. Great story. Here's our conversation with Tiger Tyagarajan.
McGirt: Tiger, it is so good to be back with you again. I think we have to start with the most basic question here. What does Genpact do? Because when I really look at it on paper, it looks like you're everything to everyone everywhere and that can't possibly be true.
Tiger Tyagarajan: First of all, thank you, Ellen and Alan for inviting me into this conversation. And what an introduction. I'm going to bottle that up and keep it with me. So what do we do? It's actually a great question to ask because I would have answered the question very differently ten plus years back was today. So the best way to describe what we do is we partner with global 1000 companies, enterprises, across six industry verticals headquartered in typically developed economies of the world, and help them undertake change and transformation journeys using new technologies, data, analytics, and basically drive better outcomes for them, help them compete better in the marketplace. And anything that allows us to be able to do that with them and for them, is what we do.
Murray: You have over the last five, six, seven years, you have been sort of my tutor and my mentor on all things A.I. and how it's transforming business. And I wonder if you could give us an update. I mean, we know the potential for these technologies to transform business is huge. But the reality doesn't always keep up with the potential and you get to see this play out across so many different companies and industries. Where does it stand right now? Where is A.I. being used effectively? Where are you seeing really revolutionary changes in business as a result of it?
Tyagarajan: So Alan I’m glad you call me a tutor on A.I. because I think of myself as a student on A.I. Enterprises and leaders and we are still discovering the best and most effective way to leverage A.I. and machine learning. And a couple of things that people have learned is you know, you have to start with what is the outcome you're trying to deliver? That starts with making a few choices. You can't A.I. everything. So how do you make those choices? Go to those outcomes. Those outcomes could be customer outcomes, could be outcomes for your shareholders, could be outcomes for the community. You can pick the right stakeholder group, but big outcomes, and then say this is one of the technologies I'm going to leverage to deliver that outcome. Otherwise it becomes a hammer searching for a nail. The other learning that people have had is you can have a great technology that actually is able to produce great models using A.I. machine learning, but those models are pretty worthless unless the underlying data is good and clean and uncorrupt and so on. So, it goes back to data. And the other one is great, you built the model but if the people actually do not believe the model, do not want to use the model, bypass the model, then your model is not worth it anymore. Because A.I. has to constantly learn and only when people use it, they can learn. So lots of things to unpack there. But A.I. is still in its early days of infancy, but I think it's pretty clear what works and what doesn't work.
Murray: Yeah, that's fascinating: both the fact that it can't be a technology first approach that you have to focus on outcomes. You can't let it be a hammer that pounds down every nail and that it has to be people first. So with all of that as a background, where are you seeing in these early days, the most transformative applications of A.I.
Tyagarajan: The most important aspect that an A.I. delivers is prediction. And, you know, humans and the brains that all of us have and the minds that we have are constantly predicting outcomes, and therefore the decisions that we have to take. What an A.I. does is understand patterns and help me as the person who's trying to take a decision predict and gives me the prediction for me to finally act. A great example of that is a whole set of insurance applications are coming in and the enterprise, the insurance company, wants to decide which application to attack first, to take a decision. Now first, in first out is the typical way humans behave. The noisiest person gets acted upon first is the other way you can behave, so the broker who's noisy gets attention first. But the best way for an enterprise to behaviors, which is the customer that is going to be my long-term relationship that is coming through a channel, that is a broker that I really like, that is a good risk to take, that has good pricing and profitability that I can delight the customer with.
Murray: Good example. Can you give us one or two others?
Tyagarajan: Let's take a private label credit card of a bank. You know, we take the data from the private label credit card of all the people who have bought using that credit card off that retailer and we go back and say look, there are some people who are using the card a lot. There are others who are not. We figure out who they are and why. To do that I go back to the retailer and get information about the actual buying patterns of those customers, both on the card and outside the card. And lo and behold you find a whole set of customers who are big users of the card, and every time they shop in that retail, they use the card. But there's a whole set of other people who are actually big shoppers, both online and in the store, but they don't use that particular card. They use other cards or they write a check and you try to understand what is it that is making people not use the card? Because the whole idea is to make people use the card. So we worked with that financial services institution and the retailer to make it a win win win for everyone by identifying those customers who are behaving in a certain way and predicting the next time they come to shop, what is the nudge you give them to make them use the card?
Murray: Ellen, I'm just going to ask one more question about this and then we can leave A.I. behind but I'm so fascinated and I think there's so much ahead for us on this. One of the things when we first started talking about this five or six years ago, one of the great fears was A.I. was going to replace humans, but the examples you're giving, these are really not replacement functions, they are enhancing humans. Is that what you're finding?
Tyagarajan: The narrative out there had always been A.I. will destroy jobs. So what are we going to do? And you know many people including me had always said that A.I. will actually create jobs. Obviously they require some new skills, but they will create jobs. All technologies are always in the end creating jobs. We've always thought about A.I. as not artificial intelligence but augmented intelligence. The intelligence is still the human intelligence, it's augmentation of that. We’re seeing that play out. I mean, who would have thought that as digital transformation takes hold, unemployment is still not as high as typically one would find in a recession. So I believe that the value creation opportunity that the world has in all aspects, including things like the big topic of climate change, the big topic of social equality, A.I. can play a very big role and those are all enhancing, value creating and job enriching, and more jobs needed.
McGirt: I also want to get into the work that you all did during the pandemic, was your adverse event reporting work that you did with the U.K. government. I mean, to me, that kind of work was extraordinary. And I think if more people understood the true nuances around A.I., it would have changed the conversation about trust in the vaccine in some interesting ways. Can you tell that story, please.
Tyagarajan: That's one of the most gratifying and satisfying stories in actually my entire career. This is when any pharmaceutical company launches a new drug or actually has a drug that it sells, it constantly is listening for any adverse events that any user of medicine reports. And obviously these days you can report in 10,000 different ways. You can tweet, you can email, you can send a fax. Believe it or not, people send faxes. Or telephone a 1-800 number and basically say “I have a problem this morning. Because I had a tablet for a simple headache, and I don't feel good this morning.” That is an adverse event. And regulatorily every pharmaceutical company has to put that together and reporting after analyzing whether it's a false positive or that it’s really a problem. The reality is that it's possible that the bottle in which the medicine is sold has a label which says you're not supposed to have a glass of wine when you have a tablet. It actually says that. People like me don't read labels. We just pop the tablet and then we had a glass of wine. The next morning, I send them an adverse event complaint. In reality, there's nothing wrong with the medicine, it's all fine. But once in a while, the complaint is a real complaint, and that becomes a true adverse event. Now, here's the interesting thing, the speed with which you can pick out the needle in the haystack can make a difference to lives. You know the stories of the old medicines that are a problem. If people had detected it one week earlier, lives could have been saved. So you want to get the medicine out fast. At the same time, you want to catch every adverse event and make sure it's okay.
McGirt: And that's what you were able to do with the U.K. government during the during the Covid trials.
Tyagarajan: That's right. Basically we took all the data and passed it through to compare it to the medical dictionaries and language and so on and said, here's the one needle in the haystack. Look at this one first. And that makes a huge difference.
McGirt: That is such a good story. I want to continue on the subject of COVID because it was such a transformational and painful moment for everyone. But something extraordinary happened November 2020, where all of the work that you've been doing to build a culture that's maniacally focused on the customer is suddenly, a new purpose has come into view. Can you tell us about that time?
Tyagarajan: Again, Ellen, your memory is amazing of our story. So for many years, we hadn't defined a very explicit purpose for the company. In retrospect, I now realized that we had been living our purpose without ever defining it, which is which is fascinating. What happened during the pandemic, there was a realization that as we became much more virtual and continued to become global and hiring new people, we had to anchor people on a stated purpose. So we undertook a journey of identifying our purpose. We went to our employees, our customers, our stakeholders, we did a bunch of workshops, etc. And quickly narrowed down to the purpose that we ultimately honed in on. And what we realized is we had been living the purpose all along, we just hadn't put it on a piece of paper. The relentless pursuit of a world that works better for people. And, you know, whether it is the adverse event report story that you described, or it's the way our employees reacted to Covid making sure that they looked after each other and prevented, you know, really bad things happening to everyone around them. At the same time, we didn't want to drop the ball even for an hour on some of the things that we do for clients because of the realization that we work we do keeps the world going round. So you know that purpose is now rallying our people across the globe. And we really are thrilled with the fact that we can explicitly now describe it and anchor ourselves around it.
Murray: Fascinating. So your purpose revealed itself.
Tyagarajan: That’s right. Great. Phrase.
[Music]
Murray: I'm here with Joe Ucuzoglu, who is the CEO of Deloitte US and had the good sense to sponsor this podcast. Thanks for being with us and thanks for your support.
Joe Ucuzoglu: Thanks, Alan. Pleasure to be here.
Murray: So, Joe, this new wave of business technology, artificial intelligence, Internet of Things, the ability to make intelligence out of data, is creating huge opportunities for companies. But a lot of the CEOs I talk to feel daunted by it. It's like where do they get the imagination to rethink their entire corporation? How did they deal with that?
Ucuzoglu: The opportunities are immense, particularly when you look at not just any one of these technologies individually, but the convergence of all of them collectively creating the opportunity to truly transform business models. And I know it can seem daunting, but the reality is taking the first step in actually produces huge benefits. Because what we're finding is that many of the cutting-edge applications are not coming out of the corporate headquarters. They're coming out of putting the technology in the hands of our people on the front lines, they find new and innovative uses. We then funnel them back up and leverage them across the entire client base.
Murray: It really gets to the importance of a culture of innovation at the company.
Ucuzoglu: It is essential that our people feel empowered to take the latest and greatest and to find new and innovative ways to use it for productive purposes.
Murray: Thank you, Joe.
Ucuzoglu: Alan, it's a real pleasure.
[Music ends]
Murray: So I want to go back to Ellen's very first question, which is what is Genpact? Because old folks like me know that Genpact grew out of General Electric and you were a product of General Electric. And that really leads me to two questions that I think you're well positioned to talk about. One is what did you learn from Jack Welch and his leadership that is still valuable to you today? And the second question is, what's changed? What are the things about Jack that probably wouldn't work today the way they did 20 years ago?
Tyagarajan: Alan, I'm biased. I grew up in the GE in the early 90s and late 90s was all driven by Jack as the CEO. And he was a bigger than life CEO, as we all know, so I learned a lot. So I'll start with, you know, the candor and transparency within the company, across the company, in every corner of the company. We were a little business, meaning a fourth decimal point of revenue and market cap and so on for GE. I was this little person in that little corner of GE and he knew what we were doing. He talked about some of the things that we were doing, just based on a quick conversation in a car ride from the airport to the office on his one trip to GE to India for four days, where I hosted him for, originally planned 90 minutes turned out to be five hours, because he canceled a whole bunch of meetings because he fell in love with what we were doing. And that conversation in that car, then goes back and relates all the things we're doing to other people to look at is, etc. So there is something about the way he communicated across the length and breadth of half a million people across businesses that had no right to talk to each other—royalty payments for NBC Universal and credit cards and aircraft engines. What connection? Well Jack Welch and leadership connection. So that's one learning I had. The other one was, I mean, I'm a big believer that I drive myself every day with one word, which is curiosity. I live my life anchored on curiosity. I actually saw that live in action for the seminar eight years under his leadership every day. I mean, you would walk into the room and all you would have is question after question after question. I believe living a life asking questions is such a great way to live life and constantly learning from others.
Murray: And Tiger for for those of us who were journalists, I mean, that was what we loved about that as well, because he was the same way externally as he was internally. But you know, there been a couple of books, there's this sort of reappraisal going on now, that focuses on things like Jack was the consummate manager of quarterly earnings. You know, give the market exactly what you told them, they were going to get and even play some games, some of which didn't look so good in retrospect, to get there. And second there were these internal management processes like rank and yank, we're going to fire the bottom 10% or 20% of every year, that in today's world don't look like a particularly effective way to manage. So was he a just a product of his time? Or do you think the reappraisals are wrong? Or how do you view all that?
Tyagarajan: So I think the first statement I would make is, we must reappraise because reappraisal is asking questions. I love the fact that I worked in that era and I learned so much from Jack. But I do reappraise saying, I don't think that's going to work here because the world has changed. The ranking of people, I was a big believer. I used it. It worked. It doesn’t work now. It doesn't work with my son. He's 28 and it doesn’t work with him. So social norms change. Cultural norms change. Expectations change. Technology changes. The speed at which information flows has dramatically changed. Hierarchies is not the way enterprises work at all. The trick I think about leadership, is making sure that while I admire and respect everything I learned from Jack, I have absolutely no qualms and desire to hold on to everything that I learned at that time. If I know that it’s not going to work, I have to change and I have to adapt. And I would say I probably learned that from Jack as well because he used to say, if you can't get to number one, number two, move on, get to the next business. You know, you can take the good and then leave the bad behind is the way I would approach it.
McGirt: It sounds like an ability to manage a constantly changing world is going to be essential for the next generation of leaders coming up. What are you looking for in the next generation of leaders? And how can they signal that they are prepared to lead?
Tyagarajan: Ellen, one of the things that I have always been a believer in it's probably turning out to be more true than I had expected and probably faster than I'd expected, is what people know and the knowledge and experience they have and the skills they have are less important in what I look for and what my team looks for in people who are going to be successful in the long run. Because what they know and their experiences are probably not going to be relevant X months, years, quarters later. So the question that we explore is, are you constantly learning? Do you believe actually shedding old beliefs and bringing new beliefs in is a good thing to do? Or are you dogmatic in your beliefs? You're never going to change? Do you know how to learn? That starts with being humble. Do you reveal your ignorance? If you don't reveal your ignorance, I don't know how anyone can teach you because they don't know what to teach you because they don't know what you don't know. Do you learn from people who are much younger, much less experienced because they know that topic more than you ever would have imagined? And do you actually go to them and sit down and say teach me? Yes, I have 30 years experience but you know this topic more than I do. So, so finding such people and are passionate about this not passive, they seek learning. They are driven. They wear it on their sleeves, because when people wear things on their sleeves, they get a followership. You want people who are not only behave like this but behave like this visibly, because you want a thousand people to follow them and say I want to be like you. So then you have a followership on the topic of I want to learn, I want to excel, I want to constantly challenge my own beliefs and I want to surround myself with people who are diverse. Because if I surround myself with people who are not diverse, then what are the chances that their beliefs are my beliefs? So where is the challenge?
Murray: I want to ask you a big question here, Tiger. A question about the world because Genpact was a creature of the globalization of the 20th century and the whole move towards business processes outsourcing and saying, hey, we can you know there are all these really smart people in India that we can deploy to do this for us, let's let it happen over there. We're in a very different era right now. Geopolitics is different. Supply chain problems have just made people think very differently about this. And there's a whole process of friend shoring, reshoring people thinking about getting everything back home, as opposed to leaving it all over the world. What's your assessment of that? Where are we in the state of globalized business?
Tyagarajan: It's a great question, Alan, and I would say unfortunately, the answer is going to be heavily nuanced. So let's take a few things. So if you look at a manufacturing company that is predominantly dependent on China for its supply chain, pretty much end-to-end supply chain, then I would argue, irrespective of cost, there is a problem. Because there is a resilience problem that is obvious. Irrespective of trade wars, etc. there is a resilience problem that should be sorted. Does that sorting out of the resilience problem mean diversify the answer? Yes. Does that diversification mean bring it near shore? I don't know. After all, Apple decided that it needed to diversify manufacturing of the iPhone 14 out of China. In my mind, I was expecting it to happen at some point in time, the speed at which it happened is I think a reflection of the world we are in and now we are manufacturing that is happening for iPhone 14 in India as well.
Now that's globalization, but that's not so part of the answer to the question is, I think concentration of anything and swinging the pendulum too much to an extreme or anything is a problem. Having a balance that is distributed on lots of topics is the way I think the world is going to go. The world of digital and technology and information flow allows that to happen, because there are going to be some things that will be needed in cycle times that no supply chain can deliver. Those are best done really close to you. There are some things that can be done from far away, in which case don't distribute it to one place, distribute it to an ecosystem that has the ability to create resilience. We've had situations in the last 12 to 18 months, where a number of our new clients have come to us and said, I need you and I need you with your global footprint because my footprint is too concentrated in location x or location y. So I need to globalize more because I realize that because I'm not global, I've not been able to leverage that resiliency that some my competitors have.
Murray: So what does that meant to Genpact’s geographical footprint? I mean, you started out very much with an Indian workforce. What does it look like today?
Tyagarajan: From 1997 the first set of people we hired and trained and deployed were in India. In 2005, Jan. 1, when we spun off from GE, we had four countries we delivered services from India, China, Budapest and Hungary and Mexico. Today we have 34 countries we deliver services from. India is still the biggest, but it's only 70,000 people. Only 70,000 people out of 120,000 people. 50,000 people are in 33 other countries. And if I pick a country that I just came back from, Poland, as an example, we have four cities we deliver services from. We have 3000 people in polling. They're doing some amazing work in supply chain for Europe for a couple of very large consumer goods and manufacturing companies. They forecast demand. They line up supply. They build up resiliency in that supply. They then orchestrate transportation to try and reduce cost of transportation. But these days, they're also trying to reduce carbon footprint in transportation because the client itself is focused on ESG. So that ecosystem is all polling. And therefore, you know, when you think about resiliency, we have an India footprint for the U.S. for them. And then we have a Polish footprint for Europe. However, those teams are crosstrained and our ability to move talent back and forth our ability to move work back and forth as long as we have information flow and connectivity is where the world is.
Murray: So from where you sit the world of businesses is as globalized as ever or more than ever.
Tyagarajan: It is but as I said, it has nuances. So it's very, very important to be constantly listening more. And there times when it's very important to have a workforce that are very close to the client and actually encourage them to do that. So we now have close to 9,000 people in the U.S. in five operating centers in the U.S. and 10 years back that was not even 1,000. So it's grown 10 times and the work they do is sensitive, is regulated, is time sensitive, is customer sensitive, needs reaction time and response time. And it’s also culturally sensitive in the sense that we need to understand the local culture deeply and therefore it's best to be done out of Florida or Texas or Illinois or Pennsylvania, four of our big centers in the U.S.
McGirt: It sounds like you literally live inside a fully diverse ecosystem of inputs and ideas and business pressures and opportunities that's fully global. How do you take these inputs and these insights and this information and began to chart a path forward? I don't know if you use A.I. but I wouldn't be surprised if you did.
Tyagarajan: In my free time I listen to a lot of podcasts. I'm a big fan of that by the way, because I walk a lot and run a lot.
Murray: Leadership Next is no doubt at the top of the list.
Tyagarajan: It’s already on my list. However, most of the podcasts I listen to are not business podcasts, they are podcasts about the way the mind works and the way evolution has happened, etc. And one of the things that is obvious is that it's important for our kind of an ecosystem to be constantly listening. What does listening mean for us? It means that we need to have our tentacles out in the world. We need to be with our clients. Fortunately, our clients are very diverse, as you said, they're very global, they’re very distributed and they have all kinds of challenges. So if we have the ability as an organization to pick up those signals in advance, and to connect multiple signals that we pick up from Australia, from Japan, from Germany, from Poland, four countries I just visited in the last eight weeks, and then be able to come together and say, what does this all mean? What does this mean when people, when enterprises in Japan are really beginning to talk about China risk? I found that to be a fascinating conversation just five weeks back. I've been to Japan twice a year for the last 25 years other than the two years in between for the pandemic. I’ve never had a China risk conversation like I did this time. And it tells me that people are thinking about a world where maybe it is required to think that and therefore it's our job to figure out what does that mean for the future? I'm not a big believer in forecasting five years forward. I never was. I’ve become less of a believer these days. I'm a big believer in having continuous forecasts and updating through continuous listening. And as an organization, we have the luxury of being able to do that in a such a widespread way and then have the agility to change rapidly as you form patterns of I think this is going to happen. We recognized supply chain as a problem in 2017, well before the pandemic and thank God we did that because we doubled down and we did an acquisition and we built out capabilities. And then, boom, the pandemic happened and it took on a whole life of its own. So today supply chain, is one of our fastest growing services because of that.
McGirt: Is another way of saying what you just said is don’t fall in love with forecasts begin to get interested in really good likely scenarios and that gives you a chance more to fall in love with the problem that you’re trying to solve rather than the solution that you think you have?
Tyagarajan: Extremely well put. So scenarios is a word that has really raised its head a lot in the last six, nine months. Forecast is important but re-forecast in very fast cycles. If you used to do once a quarter do once a week.
Murray: Tiger this has, as always, been a fascinating conversation. Every conversation with you is. Thank you for taking the time to talk to the two of us. We've covered not just how A.I. is changing business but, but how listening and learning and scenario planning is all so critical to leading a business today. Great to be with you.
Tyagarajan: Alan and Ellen, thank you so much for inviting me to this conversation.
Murray: Leadership Next is edited by Nicole Vergalla, written by me, Alan Murray, along with my amazing colleagues, Ellen McGirt and Megan Arnold. Our theme is by Jason Snell. Executive producer is Megan Arnold. Leadership Next is a production of Fortune Media. Leadership Next episodes are produced by Fortune‘s editorial team.
The views and opinions expressed by podcast speakers and guests are solely their own and do not reflect the opinions of Deloitte or its personnel. Nor does Deloitte advocate or endorse any individuals or entities featured on the episodes.
