Announcer:
From the Library of the New York Stock Exchange at the corner of Wall and Broad Streets in New York City, you're Inside the ICE House, our podcast from Intercontinental Exchange on markets, leadership, and vision and global business, the dream drivers that have made the NYSE an indispensable institution of global growth for over 225 years. Each week, we feature stories of those who hatch plans, create jobs, and harness the engine of capitalism right here, right now at the NYSE and at ICE's 12 exchanges and six clearing houses around the world. And, now, welcome Inside the ICE House. Here's your host, Josh King of Intercontinental Exchange.
Josh King:
We feature a lot of stories here in the ICE House of businesses and organizations emerging through a process of transformation. In a recent episode, Levi Strauss & Company's CFO, Harmit Singh, joined us just minutes after his brand listed on the NYSE. It culminated an impressive turnaround journey under Harmit and CEO, Chip Bergh, an underlying theme of our talk, how the 166-year-old company leveraged technology to improve their business, find new markets, lower cost, and become more dynamic. He described the process as going from using technology to run the existing train to deploying technology to build a better vehicle. Levi's set out on a path that ran counter to how their company became an iconic brand. Chip and Harmit were asking the board, employees, and consumers of Levi's to trust the process.
Josh King:
Trust the process, a phrase originally from business that has become the buzzword in sports to describe what fans would do when the team embarks on a long rebuilding plan. We're at the beginning of the 2019 Major League Baseball season. Around the league, there are six new managers, of the Reds, the Rangers, Blue Jays, Angels, Twins, and Orioles. Will any of them win the World Series? We'll see. The skipper of my hometown team, Alex Cora of the Boston Red Sox, did it last year, and all of this year's new managers, David Bell, Chris Woodward, Charlie Montoyo, Brad Ausmus, Rocco Baldelli, and Brandon Hyde are imploring their players, fans, and media to trust the process.
Josh King:
How does that work in the C-suite of global businesses? I recently had my eyes opened when I heard our guest today, Genpact CEO NV Tyagarajan, who goes by Tiger, use the phrase instinctive enterprise to describe the ability for companies to adapt in real time. Tiger has led Genpact, once a division of General Electric, on the path to becoming independent itself, a global leader in professional services, by helping companies trust the process even if that process is being performed by artificial intelligence. Our conversation with Tiger Tyagarajan on changing the narrative around AI, connecting ecosystems, and how the future of business success will depend on instinctive enterprise, that's right after this.
Speaker 3:
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Josh King:
Our guest today, NV Tyagarajan, was named president and CEO of Genpact in June 2011 but has a history with the company that goes back to the 1990s, when Genpact was known as GE Capital International Services, a part of General Electric. That's NYSE ticker symbol GE. Before joining GE, Tiger began his career in India, working for Unilever, that's NYSE ticker symbol UN, and in Citibank's consumer financial services, which is part of Citigroup, and that can be found at NYSE ticker symbol C. Tiger joined GE Capital in 1994 as head of risk in India and spent 11 years in a variety of roles, including as CEO of the division that would become Genpact. Tiger went back to Genpact shortly after it became an independent entity, where he helped bring the company public in 2007 and now oversees over 87,000 employees around the globe. Welcome to the ICE House, tiger.
Tiger Tyagarajan:
Thank you, Josh. Great to be here.
Josh King:
What's your first memory of being in this building, the New York Stock Exchange?
Tiger Tyagarajan:
Oh, my first memory was coming here as a tourist, this was pre-9/11, and watching trading going on. It was so fascinating. It was also fascinating to see people exchanging pieces of paper and all the ticker flying around. So it was great.
Josh King:
Very different than what you see today and different probably from the day of your IPO. What was that like for you?
Tiger Tyagarajan:
So, first of all, I didn't know that I would come back in the way I came back in August of 2007, so it was really nostalgic and wonderful. No, parts of it felt the same, parts very different, and that's the way the world feels. There are things that you got to hold onto, which are near and dear, that really work well, should never give them up, but there are things that you should constantly look for and change.
Josh King:
So let's start by going all the way back to 1994. I was working in the White House. India was just becoming, at least from my perspective, a major global player in the area of business process outsourcing. A leading evangelist of that was none other than the legendary GE chairman, Jack Welch. You were a young man, and you read Mr. Welch's book Control Your Destiny or Someone Else Will. How did you control your destiny?
Tiger Tyagarajan:
That actually brings back so many memories. I read that on a weekend. It was a hot summer's weekend in Delhi. I came to Citibank, where I was working at that time and decided, "Time for me to move on." GE had just announced that they would bring their financial services businesses to India. I fell in love with the book. I fell in love with the thought. I fell in love with Control Your Destiny and all of the thoughts that Jack had written, and that was the beginning of my journey with GE.
Josh King:
Was that a tactic you would usually do, like you read in the news that GE was coming to India, you go to the bookstore, and find a book by Welch?
Tiger Tyagarajan:
No. I just thought because I'd picked up enough information... Those days we didn't have the net. I actually don't know how I did it, but I ran into a bunch of probably articles that said, "You must read Control Your Destiny and you must read Jack and the way he thinks about business and leadership." So I did that. I didn't realize at the end of that book I would love to join the company.
Josh King:
So trace Genpact's evolution from there. It started as a service organization within what was then known as GE Capital.
Tiger Tyagarajan:
Yeah. So the genesis of the business goes back to the times in the late '90s, this was '97, '98, when the US economy was growing like gangbusters. Interest rates were very low. There was a big refi boom, and GE Capital was growing faster than even the market. I remember being part of a meeting where people around the room in different businesses in the US were saying, "It's so difficult to hire fast enough for the work that we have to do because we are growing so much." I was running a little business in the consumer finance world of GE Capital in India, and I looked at them and said, "We can hire a lot of people. We have access to a billion people. 100 people, no problem. We'll get them, and we'll be able to do some work for your businesses." That's how it started.
Josh King:
On your own path, Tiger, you're an engineer by training and education, but you never became a practicing engineer. After graduating from IIT, you gravitated to marketing and sales, first with Unilever and then with Citi. Did you disappoint your parents by putting away the slide rule?
Tiger Tyagarajan:
No. I still have to explain to my mom exactly what my business does. That's a different problem. Because we're in the professional services business, et cetera, it's tough to explain, unlike a McDonald's or a Dunkin' Donuts or whatever. But I would say, over the last 30 years of my career, I think I've used my engineering training significantly in the way I think about problems, in the way one would approach a problem, dissect it into its little component parts, find solutions for them, and then put them all back together. I think that's the way my mind operates. That's the way an engineer's mind operates. So I guess that education has really helped me well.
Josh King:
You said you might struggle to explain what Genpact does to your mother. My mother is a frequent listener to this show, so for our listeners who are like my mom, how would you explain Genpact?
Tiger Tyagarajan:
Oh my God. Okay. We are a business that help our clients, Global 1000 companies, a number of them listed and public, most of them actually listed and public, really undertake significant change and transformation journeys to become more competitive in the marketplace. So how do I leverage new technologies? How do I do a bunch of things better to grow faster, to generate more cash, to reduce working capital, to increase margins, to drive customer satisfaction and customer experience? All of those we do at the backend, meaning we work with information and processes to run them better for our clients, allow them to generate better outcomes, and basically use new technologies to be able to do that better.
Tiger Tyagarajan:
So when a consumer applies for a credit card, how do they get an answer very quickly? We help do that. When a consumer walks into a Walmart, who we recently announced as one of our significant client relationships, and searches for a shampoo, how do you make sure, how does Walmart make sure that that shampoo's available in the exact SKU and the size and the brand that they want? All of that requires planning of order management, fulfillment, logistics, supply chain. A lot of that work at the backend we do for clients such as Walmart.
Josh King:
Talking about shampoo and talking about the customer satisfaction and customer experience, I've been a lifelong Ivory soap guy, and my wife laughs at me for that, but I'm loyal to the brand and how it makes me feel. You helped grow Pond's across India. How did you do that?
Tiger Tyagarajan:
Wow, that takes me back many, many years. It was sales and distribution and the expansion of that across many, many cities, towns, and villages in India. As you know, India is a large population that is very, very distributed with not great infrastructure, even today, and this is 30 years back. So, therefore, it all boiled down to being able to manage a very distributed sales team, motivating them to work day in and day out and convince the mom and pop retailer, because there are no Walmarts there, to actually stock the products that at that time Pond's produced as compared to other products. If the mom and pop retailer stocked product A and did not stock product B, then product A is sold.
Josh King:
You once said, Tiger, about General Electric, "I think I can build a 30-year career in this company and, therefore, will be in 20 different businesses over 30 years without ever quitting." And while the ticker symbol has changed, how close has that prophecy turned out to being true for you?
Tiger Tyagarajan:
I have not made my resume since May 1st, 1994. That was the day I joined GE, and I spent many years at GE, great years because I learned so much, and then when we spun off, I didn't have to make my resume. I just spun off with the company, and I've been there since the day we spun off, which was January 1, 2005.
Josh King:
Another thread in your thoughts early on was about the leadership vision that you worked under. Reading Welch's book, you said, "This is the kind of leader I'd like to be led by." We know some of GE's story from there, the Immelt years, the Flannery year, the Culp half-year so far. You've now been CEO of Genpact since 2011, so that's eight years and counting. How much of Welch's influence and staying power is still with you as you lead this organization?
Tiger Tyagarajan:
So I would say I grew up in GE. A significant portion of my career inside GE was when Jack Welch was the CEO, and those were formative years for me, so I did learn a lot. An example that still we use is edge, execution, and energy. We think those are important qualities in leaders. They've always been important. I would actually argue they're even more important today than they used to be. The bedrock of integrity, again, learned a lot being part of the varied businesses of GE. The passion that you bring and you wear on your sleeve every day is something that I really think is important when you lead global workforces, when you lead Millennials, a bunch of those types of things. Then all our underpinning of our business around Lean and Six Sigma and Process Excellence goes back to the days of the mid-'90s, when Jack launched Six Sigma in a big way inside GE. We as a business at that time grabbed onto it, and it's still with us.
Josh King:
So Six Sigma is as prominent in Genpact as it was back in the Welch years?
Tiger Tyagarajan:
It's even more prominent today than it has ever been, and it's one of the underpinnings of our business.
Josh King:
I touched on one sport, baseball, in the introduction, but Genpact recently announced a strategic partnership with the Envision Virgin Racing, the Formula E team, to not only develop more efficient drivers but also improve the ability for fans to interact with the team, which in the sport is actually a way to gain competitive edge. We've had stock car racers on this show, and they've talked extensively about teamwork involved and also the fan interaction that is so important to building that sport. With the Envision Virgin Racing team now tied for first place in Formula E, would you say your mission is accomplished?
Tiger Tyagarajan:
No, it was just the beginning of this mission. The mission is accomplished when we not just win the race but we learn so much that we get ready for the next season and win it again. This is a continuing, ongoing journey, just as it's in business. But the fascinating thing, Josh, about this particular competitive sport is that you win not just because of driver skill, which is incredibly important, and the mechanics of the car, which is also very important, but it's actually a lot of data and crunching of data because the difference between this racing and Formula One racing, which I love, is the fact that actually you have to conserve battery energy. You got to use it up to the last lap. You got to find a way to get your fans to actually boost your energy for that little bit of burst. All of that is data and the science of the engine, and it's sometimes real time, it's IOT. That's what makes this really fascinating.
Josh King:
I remember when Formula E was just coming into prominence, and I remember some of the names that were associated with it. You said you're a Formula One fan. How do you decide that Formula E is something that you can really bond with?
Tiger Tyagarajan:
I think our ability to work with that ecosystem to use data to make a difference versus in the Formula One race, it's a little different. It's what I would call a much more evolved sport. This one is changing every day. The technology is changing every day. It's a lot of new technology. It's the way we describe our business. It's also a lot of... The demographics of the people who follow Formula E is significantly different from the demographics of the people who follow... So we kind of like those demographics. It's much more global. It's much more diverse. 45% of them are actually women. It's a younger population. So we think that it's the future, and we just wanted to find a way to partner with the future and actually make a difference there.
Josh King:
How has the sport grown in Formula E since those early days?
Tiger Tyagarajan:
Well, I didn't know of its existence until a couple of years back, so to the extent that now a bunch of people inside our company, for example, know about it, I think it's growing as one would expect a new sport like that. It takes time for things to catch on. I would expect it to grow much faster than normal because of the way the ecosystem works these days with social media and the fact that, actually, that particular sport leverages off social media a lot. So I would expect it to grow pretty significantly. The one other interesting aspect that we liked about the race is that it goes to city centers or close to city centers, and that's great because we can get our leaders involved. We can get our clients involved. We can actually look at some of the data and debate about how improvements are happening. So it's much more engaging to be part of that race than something like the Formula One, which is obviously much bigger.
Josh King:
Right. And using technology to shave seconds off a lap or preserve that last two minutes of battery time can make a big difference in a Formula E race. But how does that translate into the workplace?
Tiger Tyagarajan:
Oh, so many, so many examples. Let's take the example I just talked about, which is consumer goods and retail because all of us can relate to it. Typically, if you place an order, if a retailer places an order for a set of goods, they get loaded onto a truck and the truck then gets out of the warehouse and then delivers to the retailer, depending on where the retailer is. One small mistake means that entire order, that entire truck, would have a problem in terms of it getting accepted by the retailer, in terms of the retailer then paying the consumer goods manufacturer. That whole supply chain, that whole management of cash, all that it took was for one little mistake. So instead of having a 99.5% accuracy, you are at 98.5, huge difference. Satisfaction of the retailer, satisfaction of the consumer goods manufacturer, satisfaction of the consumer, which is probably the most important thing, because the item is not available in the shelf, and all it took was that 1% difference.
Tiger Tyagarajan:
Another would be it takes seven days to process a small business lending transaction. Someone down the street here orders small equipment because they want to upgrade their coffee machine and they have a coffee shop here, and it's a $100,000 lease or loan that they want. If you find a way to have the bank process that in a day versus doing it in five days, it could make a big difference to the bank because the bank wins that business versus someone else who takes seven days. So how do you make that seven-day decision into a one-day decision? Well, if you can use AI to actually read a cashflow and a balance sheet very quickly and convert it and compare it to the risk parameters you have and then have a human being look at it and take a decision, so you're not taking the human being out of the decision, it's a human plus machine combined decision but you move from five or seven days to one day, you're delighting the customer and the coffee shop makes more money. If you actually abstract that to the US economy, you're talking about small businesses, which is the bulk of the US economy. How different it would be if you can actually find that cycle time reduction.
Josh King:
So give me a real world example of one of these consumer goods companies that looks at their consumer satisfaction and says, "98%, but if we can get that extra point to 99%, it equates to tens of millions of dollars in the bottom line."
Tiger Tyagarajan:
So I won't take name of the consumer goods company because we have pretty significant confidentiality requirements in many of those cases. In the case of Walmart, we announced a formal relationship, so that one is out in the public domain recently. But pick one of the larger consumer goods companies, and we serve 17 of the top 20 companies in the consumer goods space in the world. Moving from that 98% or 99% for a typical 50 billion dollar large consumer goods global enterprise could mean improving that top line by 250-odd million dollars for that one retailer that they serve. You then translate that into multiple retailers that they serve. You could talk about a billion dollar lift in revenue, which would be 2% of their revenue for the year, and these days a 2% organic growth lift is wow.
Josh King:
That's all that counts in some ways.
Tiger Tyagarajan:
That's all it is. That's a wow.
Josh King:
I mean, so if you go back to those early days for you at General Electric before it became Genpact, so much of these processes were human and manual. How does AI and other technology come together seamlessly to augment the human element enough so that decisions can be both instinctive, the way a human would react, but also data-driven?
Tiger Tyagarajan:
That's, Josh, the journey we are on with many of our clients, and I would call out and say these are still early days of that journey for many of our clients in leveraging new digital technologies. I would point out that AI and machine learning are just one of the many technologies, there are many, that I would consider that to be at the tip of that technology ecosystem. I'll start by saying that, interestingly, you have to bring in Lean and Six Sigma first to actually take out rework that typically happens in a process. Wait times. So in that seven-day process of approving a loan, actually, the time that is spent on actually doing the work is probably an hour and 15 minutes. All the other time in seven days is spent someone waiting for someone to do something. How do you remove wait time? Well, you apply Lean principles. It's what Toyota invented many, many years ago. You apply Kaizen and Lean principles. You figure out why things wait. You find a way to reorient and redesign the process.
Tiger Tyagarajan:
You also find out why some transactions go quickly and some don't. That's classic Six Sigma thinking. You compare the good and the bad. You figure out root cause analysis of the good versus the bad, and then you say, "Hey, if an application comes in the following way, then change the people who approve it, send it to this person." Once you clean out the process, standardize it using Lean and Six Sigma, then you bring in new technologies. One of them would be AI. The way we've brought AI into that arena is that AI can read unstructured documents and extract information. It extracts information in a manner and puts it in a structured format, let's say, an Excel spreadsheet, does cashflow analysis. It reads footnotes of balance sheets and then converts it into, "Hey, this depreciation that is there in this balance sheet is actually different than the way I would interpret it because if I read this footnote, I'm going to correct this depreciation."
Tiger Tyagarajan:
Ultimately, that lands up on the risk manager's table. The risk manager doesn't have to do all that calculation. The risk manager says, "I like what I see here. I think I like the particular industry that this customer belongs to. The amount of risk that we've taken so far and exposure we have still has some opportunity to lend more. So I'm going to go ahead and approve that transaction." So, again, I want to emphasize the machine is doing a lot of the data-crunching work. The ultimate decision actually still resides and should reside with the human. That's something that society and companies are trying to figure out because you really want decision-making still in the hands of people
Josh King:
With all of that automation to improving the decision, Tiger, this past year has seen vast improvements in AI technology. But it seems that even positive coverage always takes a negative turn. Let's listen to a report from last year.
Speaker 5:
At tech conferences in Silicon Valley, around every corner, startups are working with artificial intelligence. Centerscall uses AI to help these devices learn an elderly person's behavior to make sure they're safe. What the founder admits when it comes to mixing AI with robots as anxiety grows.
Speaker 6:
The robots can definitely overtake us because the minute it comes to movement and hurting human beings, it's a little different.
Speaker 5:
Tesla founder, Elon Musk, has called AI a greater risk than the DPRK and expressed fears that Google could accidentally produce AI robots capable of destroying mankind.
Josh King:
So Elon Musk always with that foreboding view of the future. How much credibility should he have?
Tiger Tyagarajan:
I think, one, he's an amazing leader and has amazingly innovated in so many areas. So, obviously, what he says is incredibly credible. The only thing I would argue is that there is a balance to that narrative. Every narrative must have a balance. I think a lot of the narrative around AI has gone in that direction of being incredibly negative, of being incredibly, "It's going to destroy us, it's harmful," et cetera. Let's talk about all kinds of technologies that humankind has invented. Let's pick nuclear. Isn't there a balance in that whole narrative? Nuclear has been amazing for us in so many arenas. At the same time, we know that nuclear is a real problem in many other arenas. It's a question of where does society take it? Where do governments take it? Where do human beings take it, and what regulatory environment, what narrative allows people to find the right path and control the bad users of that technology? Can AI be used for really bad things? Of course, no question. But is that the only way AI will be used? No.
Tiger Tyagarajan:
We actually believe that AI will be the solution for AI being the problem. So what does that mean? The fact that AI can create a problem, one of the ways to prevent that and watch that is to use AI to watch how AI is being used. AI is going to create jobs. How's that going to happen? Every time you tackle a problem and you reduce the cost of solving that problem, the number of people who can then have access to that potential solution dramatically increases. Just pick one metric. Two billion people in the world have very limited access to healthcare, have almost no access to education that is easy, and have no access to financial services that is cost-effective. Wouldn't it be wonderful to have the opportunity to tell someone in Africa or India or China, deep inside, who today doesn't have a bank account, saying, "You can open a bank account and deposit a cent a day, a cent a day." You can't do that today because it's too expensive. AI can allow that to happen.
Tiger Tyagarajan:
AI can allow a diagnostic to happen in a village where there is no access to doctors, but using an iPhone or any phone and AI, you can actually tell the villager that, "Your sugar level is beginning to rise so don't have your daily tea today." That's it. You've actually solved the person's diabetes problem for the day. I think AI can be so good to two billion people, and, therefore, it can be good to developed economies because who's going to produce those solutions? The US is going to produce a lot of those solutions. Now, I don't want to minimize the challenge of the transition from one world to another. Transitions always have a problem. Someone is going to get left behind. That is a problem. We all have to solve that problem.
Josh King:
With all those benefits and solutions, is one of AI's problems simply a branding problem? I mean, the phrase artificial intelligence seems to smack people as something that would replace human judgment. We had a guest here from the show Billions. The second episode of the season featured a Terminator-style robot that walked in a room and punched down a door and yet was made feeble by throwing a few pencils on the floor. Should we think about it in different terms than AI that might scare people?
Tiger Tyagarajan:
No. So, first of all, what a wonderful way to describe and create a similar example around the Billions example that you gave. It is so true that the story around AI must change, and it actually starts maybe with the term artificial intelligence itself. What we use in our business a lot is the phrase augmented intelligence. We consider almost every process must have a human in the loop. In the end, all processes are there to serve people. Therefore, empathy is critical. Understanding what the customer really wants is critical. Listening and collecting that feedback on a regular basis, almost real time, is critical. Can machines do that? Yeah. Is it easy? It's very difficult. Will one day the problem be solved? I'm sure it can be solved one day, but there'll be other problems to solve at that time.
Tiger Tyagarajan:
So the human in the loop is very important, which means you are augmenting humans. Many, many years ago, people thought computers would replace humans. Today, all of us almost think about computers as an extension of our brain and as extension of our arms. We can't let go of our fingers on a keyboard. I think AI is going to be very similar. It's already there. If any of us go to our iPhones, we use AI every moment when we use our iPhone. We don't know it. That's how AI's going to become. So it's a common truth. So augmented intelligence is the phrase I would use and really change the narrative to be a balance of positive and negative.
Josh King:
So Genpact recently released a study, AI 360: Insights from the Next Frontier of Business, which looked at several of the topics surrounding AI, including revealing the tide seems to be turning on consumer suspicions of AI. What are some of the findings that you found most surprising from the report?
Tiger Tyagarajan:
So I'll pick on one that I know is real, but what really surprised me was consumers are talking about it, which means it's out there in society, and this is around bias. The fact that AI ultimately learns from what humans do today means that if what we do today is not necessarily unbiased, then the machine will learn that same bias. We all know that a lot of society today has biases. Let's pick the most talked about one, which is gender bias. We all know that in decisions there's a lot of subconscious gender bias in many, many decision-making in enterprises.
Tiger Tyagarajan:
If all of that gets learned by the machine with no one correcting it, then the machine can be biased, and, therefore, the consumer talking about they're worried about bias, they're worried about bias and decision making by the machine and who ultimately calls the shots in that, I thought when the consumer talks about it, that's very interesting. A lot of companies are working on it. A lot of deep technologies are trying to solve that problem. It's a tough problem to solve, which is why we think that humans should always be in the loop. But I would pick that one was... That one was a surprise to me.
Josh King:
Another one, Tiger. For example, talking about bias, 86% of business executives believe customers would rather be served by a bot than a call center human by 2021, but only 15% of consumers felt the same. So there's obviously a difference of opinion, people who sit in the corner office versus people who are on the phone trying to get their printers to work.
Tiger Tyagarajan:
Yeah. I guess, as you know, technology often is overestimated in it's short-term impact and underestimated in its long-term impact. So I would say both are right. There is going to come a time when chat bots, et cetera, will be par for the course. Will they ever get to 86%? I would argue probably never. Are they going to be just 15%? Probably not. It's going to be higher. But I would also argue that as that journey goes from the current whatever percent, small single digit percent, to 15, 20%, the number of interactions is actually going to increase.
Tiger Tyagarajan:
This is my narrative back to, yes, a lot of automation is going to happen using chat bots. Let's say 25% gets chat botted. The reality is that maybe the number of times you and I call is going to double. Photography is a great example to look at. When all of us were using Kodak films and Fuji films, we were taking, I don't know, 400 photographs a year. I would argue today we take sometimes on our vacation 1000 photographs just on that one vacation. That has increased the amount of digital photography versus film-based photography. The other thing that's happened is we all use photography today not just for what we used to use it in the past, for new things. So new inventions are going to happen because of AI that today don't exist, and that's going to create new jobs.
Josh King:
And I was amazed by looking at my, I think, Google photo app the other day and seeing how many different ways that it had interpreted how I might like to see my photos sorted, either through my business needs or my friends or my pets. I mean, it knows how to distinguish between an animal and a human pretty easily, and that's just the tip of the iceberg.
Tiger Tyagarajan:
Yeah. Yeah. Actually, that reminded me. The one that I find most intriguing is you wake up in the morning on the 23rd of February and it tells you memories of 23rd of February and it's like, "Really?" It actually pulls out the 20 photographs dating back to the last 30 years and on the 23rd of February. Then you say, "Ah, yeah, I remember. I remember going there on that day."
Josh King:
So, Tiger, who is Cora, and how is Genpact helping companies convert some of the study's findings into actionable business processes?
Tiger Tyagarajan:
Who is Cora? Cora is a platform that sits on the cloud and brings together a range of technologies from the ability to read a document, just read the document, that's a particular technology, the ability to then interpret that document and use vision to actually electronically put it in a place, then applying computational linguistics, which basically means read language and extract knowledge from it. That's the AI computational linguistics, and if it has a few photographs and diagrams, then computer vision. All of that today is available as technologies on the cloud.
Tiger Tyagarajan:
What Cora does is actually pulls 12 of these technologies together. They're all open architecture. They all can communicate with each other and connect with each other with APIs. They also back into core technology platforms, ERPs that companies have, and legacy systems using API again, and, therefore, you can actually create a solution for a problem, the various problems and solutions we discussed, in a very agile fashion. You can do it in a 30, 60-day sprint. You can experiment in those short cycles and then keep improving as you go along. That's a very different world of technology than trying to bring a big technology that's a three-year project that has big dollars attached to it and big risk attached to it. That's what Cora is.
Josh King:
So balancing technology and risk, automation is always going to require some adjustments for the economy and for the workforce. The exact number is yet to be determined, according to the chairman of the Council of Economic Advisors, Kevin Hassett, on CNBC's Squawk Box last summer. Let's have a listen.
Kevin Hassett:
I think that what we're looking at is, between now and 2030, somewhere between 14 million and 60 million people are going to lose their jobs.
Speaker 8:
That's a lot. You could drive a truck through that.
Kevin Hassett:
Yeah, well-
Speaker 8:
Six-
Kevin Hassett:
But 14 is a lot and-
Speaker 8:
Will lose their jobs.
Kevin Hassett:
Will lose their jobs because of automation and AI, and the problem is that if you look at people of different skill levels, it's the people of middle and low skills that tend to lose their jobs to automation. So they really are going to have a reskilling challenge that's even bigger than what we're seeing right now, and that's why we put so much work into thinking about, well, what are we going to do to help workers prepare for that?
Speaker 8:
So you would-
Josh King:
So, at the beginning of our conversation, Tiger, you were talking about how AI is going to help create new jobs. From the first industrial revolution to today, each new technology has caused some jobs to become obsolete, like Hassett just said, and new professions to develop. How are some of Genpact's clients using AI to transform their businesses and actually create new working models?
Tiger Tyagarajan:
So, Josh, that is, I think, the fundamental challenge that society faces and companies face and individuals face, which is how do you get reskilled and retrained for this new world? As I said, often, the technology that is causing the problem is often the solution to the problem. So what we are doing, and we are a small company in a much bigger... But a lot of other companies are doing this. What we've launched is a pretty significant reskilling program in the company. As you said in the introduction, 87,000 people growing at about 10, 12% a year, so significant growth and, therefore, a lot of employees. Some of the jobs they're doing, we ourselves will automate, and our objective here is to reskill people so that they can then grab onto new, more complex jobs. How are we doing that? We're calling the program Genome, and it traces its roots back into changing the genetic code of people in what they know and what they learn.
Tiger Tyagarajan:
Our thesis is that actually knowledge resides today in people. Within the crowd of 87,000 people, we know there are some people who know more than others on some topics. How do I then get another 10,000 people to know that topic because it's important for them? These topics are not one-year courses. They are really bite-sized courses. So it's a specific question on a topic, and the answer is seven minutes of learning, five minutes of learning. So it's probably 10,000 courses, each five to seven minutes. We have a bunch of companies that do this and have built business models on this, Coursera being an example. What we are doing, therefore, is identifying, first of all, you as an individual, what are you really good at? So I personally, as a CEO, actually listed out a whole bunch of things that I think I'm really good at, I know really well. Then I listed out a whole bunch of things that I'd like to know. So you first collect all of that from 87,000 people.
Tiger Tyagarajan:
You feed that into an engine, and then you say, "I'm going to pair up these 1000 people who want to know the following things with these seven people in the company who are all distributed all across the world," and we are calling them gurus on these particular topics. Then we are using the platform in between, using video, using podcasts, which actually are great mediums because you learn much better, and connecting up the people who have the questions and the guru. The last thing I'll say is all of this works under one condition, culture. So I would go back. Do you have a culture where you drive learning as a deep desire in the company and in the people? Do you drive curiosity as a culture? Because if you do, then a lot of people would want to learn and a lot of people would want to contribute, and that's the culture we're trying to drive with. I think it's very important for everyone to drive that curiosity, learning-driven culture.
Josh King:
After the break, Tiger and I talk about how Genpact has partnered with clients to improve processes and how connected ecosystems will drive the future of business and solve some of these problems. That's right after this.
Speaker 9:
We are the most advanced form of respiratory technology in the world. We have the only mask-free form of non-invasive ventilation. It's very important for patients in respiratory distress. Our culture is focused on the patient and providing our clinicians with the very best tools, and we have the very best people in the medical technology industry, and I'm super proud of them all. The New York Stock Exchange, I love the commitment of the people who work here, the most liquid, efficient markets in the world. So excited that we're big enough that we can be part of this organization. Vapotherm, now listed on the New York Stock Exchange.
Josh King:
Welcome back. Before the break, Genpact CEO, Tiger Tyagarajan, and I were discussing how artificial intelligence will transform the workplace and the globe. Tiger, when Genpact became independent in 2004 and the company had 16,000 employees, today, that number has grown over five and a half times that. How have you been able to scale the company up without losing the effectiveness of Genpact's core competencies? We were talking about Jack Welch earlier. We know how he communicated to leaders at Croton-upon-Hudson. We know that his books served as guidelines to the executives that he was training. You've got to communicate to 87,000 people. How do you do it?
Tiger Tyagarajan:
So, actually, that's exactly what we do. We don't write books, but we communicate again and again and again, and a whole lot of our leaders typically do that systematically. We come together often virtually. Our leadership team is distributed across the globe. My own 15-member leadership team in the company are based in nine different cities across the globe. We get together physically probably three times a year, but, otherwise, we can get together virtually often. We use all the latest technologies to get together, video-conferencing a lot, so that we can actually have eye contact and pressure test each other and duke it out on topics. We then take that, cascade it down. We do global town halls. We do local town halls. Anytime any of our leaders visit any of our locations where we have even 50 people...
Tiger Tyagarajan:
An example would be a recent visit I did to Atlanta, where we have a significant population of 250-odd people focusing on three different sectors. One is a group that is focused on supply chain, that's a new acquisition that we did about four months back called Barkawi, supply chain consulting people, a group that is focused on insurance claims called BrightClaims, an acquisition that we did two years back, and a group of people who are consulting and technology who work with a number of clients in the Atlanta ecosystem.
Tiger Tyagarajan:
When any of our leaders or I visit there, I get the group together and spend about an hour and a half, first of all, talking to them about where the company's going, talking to them about the key messages that we are trying to drive, our strategy, talking to them some of the challenges we are facing and how we're trying to tackle them, and then really opening it up to a dialogue on what are they seeing in the marketplace, what problems are their customers facing? How are we trying to solve them, what help do they need from people like me and my team, and engaging in that dialogue, picking up those signals, then synthesizing it and creating solutions and taking it back in a continuous frequent fashion, almost nonstop, is the only way you drive that culture.
Tiger Tyagarajan:
The last thing I'll say is we've anchored ourselves on a few values that we think are very important and then we cascade it down. We call it the CI squared of our values. C for curiosity, no surprise. The second C is for courage. We think the world of today requires courage to take decisions, to experiment, to try new things. The third letter is I, and that's incisive. We have a deep belief that you got to be very sharp and incisive and granular and deep. It goes back to a Lean and six Sigma kind of culture. You got to be very specific. Don't be generic. The last one, no surprise, is a bedrock of in integrity. So it's show me behavior around curiosity, courage, and incisiveness on a bedrock of integrity.
Tiger Tyagarajan:
Once you get people engaged around what does that mean in terms of day-to-day behavior... Because, really, what you want is people, when they encounter situations, to all behave in the same way to try and find the answer. The last one is really collaborate with each other. We think knowledge gets created and problems get solved best when you collaborate, when you have diversity at the table, when you have five different voices and not necessarily all the voices are the same, and then you get a better solution.
Josh King:
So curiosity, courage, incisive, and collaboration. Talk about some other issues that are so important to large organizations. Why is increasing gender diversity not just the right thing to do but also mission critical to Genpact's agenda?
Tiger Tyagarajan:
So our business, professional services, has really only one raw material, and that's talent. We don't make things. We don't have factories. We have nothing. We talent. So if you step back and say, "How do we make sure we have access and we have the brightest and the best talent in the world anywhere in the world," you have to easily come to the conclusion that half the talent in the world are women. So the business problem is really how do we make sure that we are really a great place for women to join, which is half the talent of the world to join, and a great place for women to thrive in and be successful, which is half the talent of the world. So our objective here is really attracting the best talent of the world, and if you can become attractive to women as to men and if you can then make sure that they stay in the company because they really like what they're doing and they grow and they succeed, then we've actually solved our problem, which is to bring the best talent to our customers.
Tiger Tyagarajan:
Then, of course, there is this whole topic around there are some problems that actually require diverse thinking, many problems that require diverse thinking, and you really want different voices. You want different voices based on gender diversity, ethnicity, background. In fact, more and more we think about cognitive diversity, which is the way you think is different. We like cognitive diversity because it allows people to debate. Then you've got to make them inclusive, which is you bring them in and have the conversation. But, ultimately, you take a decision which is one decision, and even though I may have had a different view, once a decision is taken, I then subscribe to the decision and move forward.
Josh King:
Looking at this talent that you have, which is basically the commodity that you're selling, how do you help people continue to learn from the lowest level of the organization to be able to move up and become the next level of leaders at Genpact?
Tiger Tyagarajan:
So, again, Josh, it starts with culture, so we drive learning and curiosity as a very deep culture. As an example, if I meet anyone and they tell me that they have so-and-so point of view on a topic and I actually disagree with that person, so my instinctive answer is, "I don't agree with you," that's a bad answer. That's a bad reaction. Our objective is, "So, Josh, tell me, you said this. Why do you say that?" So the word why for us is incredibly important. Again, it's fascinating. Six Sigma asks you a lot of questions. I mean, you're supposed to ask a lot of questions when you use Six Sigma. One of the fundamental questions you're supposed to ask is keep asking why. So we drive that hard.
Tiger Tyagarajan:
We use video conferences a lot to train. We use virtual training rooms to train. We use videos and podcasts to train a lot. We think training has to morph from being the old world where you bring people into a classroom and you spend a week. We think a lot about apprenticeship-based training, kind of the German model. We think that you learn something because it's important for your job today. You go and try it, you test it, you succeed a little bit, but you fail a little bit, you come back and do it all again. But the coming back doesn't have to be into a classroom. It can be, "Hey, I want to set up a 15-minute conversation with my guru because I tried it and it didn't work. So what did I do wrong?" Then you debate it, and then you say, "Oh, I got it," and then you try it again next time. So you iterate your way to learning.
Josh King:
So Genpact has announced a number of partnerships over the past year. What is your strategy for creating new partnerships?
Tiger Tyagarajan:
It's really, first of all, focused on a specific set of industries. We are big believers in focus because we are big believers in incisiveness and granularity and expertise. You cannot really say that I'm granular and expert in everything. So we picked seven industries to really focus our energies around and build expertise around. In every one of those industries, our objective is to be a truly trusted partner of all the key players in that industry to make them competitive, to make them win, and to help them transform and change and become more competitive themselves and to create real value for their customers.
Tiger Tyagarajan:
So Walmart is a great example of that in the consumer goods retail industry. McKesson is a great example of that in the healthcare life sciences, that ecosystem. Another example I would call out is Bridgewater, another relationship that we announced in the last quarter, in the fourth quarter of last year, where our objective there is to really transform the way a set of functions perform in Bridgewater for the Bridgewater Investment Group and make it much more digital, much better experience, much more connected with each other between HR and finance and IT and facilities and so on. That journey with Bridgewater has just started, so that's another example of an iconic firm that we are partnering with in order to change the way they operate. That'll become an example for others in the industry to follow. So our objective here is to change companies and help them navigate through this transformation journey using digital technologies a lot and using the foundation of Lean and Six Sigma that we bring to the table.
Josh King:
Talking about iconic firms, one example in connected ecosystems is Cruise, which has become a joint project between competing automakers General Motors and Honda. I want to listen to General Motors' president, Dan Ammann, talk about it.
Speaker 10:
Well, our mission is to deploy this technology safely at massive scale. That's going to require a lot of resources, not just financial resources but also engineering resources. We have a longstanding relationship with Honda. They've been a tremendous partner to General Motors on a number of projects. So bringing them into the picture with Cruise on our AV mission is a very logical step. They're bringing 2.75 billion dollars to the table to help with the mission and a lot of engineering resources as we look to develop a purpose-built autonomous vehicle to deploy, again, safely at massive scale.
Josh King:
General Motors and Honda joining forces together to deploy it in that massive scale. How does a collaboration of this scale actually come together from the start?
Tiger Tyagarajan:
I think it points to a very, very, very important topic, which is the world of today requires the ecosystem to partner with each other to solve a problem because the chances are you'll find much better solutions. The way we are approaching it is partnerships at three levels. So, first of all, we partner with our clients. We often co-innovate with our clients. An example would be in the pharma industry, which is another large industry of ours, and we serve 15 of the top 20 pharma companies in the world. With one of the largest pharma companies, what we are co-innovating with them is a problem that the pharma industry has grappled with for many years, which is when any of us and any consumer in the world takes any medicine, any tablet, any capsule and we have an issue with it, it could be, "Yeah, I don't feel good after taking the tablet," you send in a complaint, you call a 1-800 number.
Tiger Tyagarajan:
It used to be, "I'll send in snail mail," but these days it's, "I'll send in a Twitter. I'll tweet. I'll send in a social media feed." All of that becomes something that the pharma company has to look at, has to investigate, has to then report to the regulator. So imagine doing that manually. Every pharma company in the world does that today and reports to every regulator in the world. That is a mammoth task that every pharma company spends time on. It's growing at 10% a year because regulations are growing and drugs are growing and the ability for customers to say, "I have a problem," is also growing. 98% of those are actually false positives. It's not a problem, but it's important for the pharma company to regulate and report.
Tiger Tyagarajan:
We've partnered and co-innovated with one of the largest pharma companies to solve that using AI. The AI actually reads those feeds, picks it up from the ecosystem, compares it to the dictionary that the FDA has and a lot of other regulators has and then crafts a note after doing the analysis saying, "This is the note that the regulator should get." The thesis there that us and the pharma company had was once we build this, we will go to all other pharma companies and give them the solution. So think about this. The pharma industry wants to partner with each other to solve this problem because it solves problem for humankind. They compete with each other but not on this topic. This is not a topic you should compete on.
Tiger Tyagarajan:
That's the way the world is going. So Honda and GM is a great example of partnering together, even, obviously, though they compete with each other. So we partner with our clients. We partner with large tech companies, the Microsofts, the Googles, the Salesforces of the world. We use their platforms. Then we partner with startups because startups is where some of the newest things are getting invented. We partner with them on experiments. In the Valley, we have a Palo Alto innovation center where we do that. We partner with them in Boston, where we have our AI center. We partner with them in Tel Aviv, where we did an acquisition and we have a center there of real deep thinkers and technology and AI people and analytics people there. We partner with them in Bangalore. So we've tried to leverage our global ecosystem, create partnerships of startups there, bring that into the company, create solutions, and take that to clients. We partner with clients, and then, of course, we partner with large tech companies.
Josh King:
So much partnering, Tiger, so much traveling. We've covered so much ground in this conversation. I read that you are basically on the road about 15 days a month. I think I also read that you took your family on a 10-day holiday to China, and you were saying, "Boy, maybe my ideal vacation would just be at home with maybe one exception, which is, hey, if there's a cricket match on, I could blow off work to watch that." But if there's one thing that artificial intelligence can't shorten the process on, it might be cricket. Or is there an AI way to shorten the length of the cricket match?
Tiger Tyagarajan:
No, no, no, no. The five-day cricket match is the best cricket match in the world. No one should try and shorten it. There is, of course, the three-hour version as well. But, no, there are some things that can't be AIed out. I know that there is an attempt to try and create some of the best artwork using AI but I would say, how do you pour emotion and empathy into art? I don't think AI can do that.
Josh King:
And on that note, we'll leave this conversation because there is no taking shortcuts when it comes to emotion and empathy. So thanks very much, Tiger, for joining us Inside the ICE House.
Tiger Tyagarajan:
Thank you, Josh. Enjoyed myself. Thank you.
Josh King:
That's our conversation for this week. Our guest was Tiger Tyagarajan, president and CEO of Genpact. If you like what you heard, please rate us on iTunes so other folks know where to find us, and if you've got a comment or question you'd like one of our experts to tackle on a future show, email us at [email protected] or tweet at us @ICEHousePodcast. Our show is produced by Peter Ash and Theresa DeLuca with production assistance from Ken Abel. I'm Josh King, your host, signing off from the Library of the New York Stock Exchange. Thanks for listening. Talk to you next week.
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