S4 Episode 18: Sanjay Srivastava Chief Digital Officer at Genpact on their partnership with the Envision Racing Team and the future of electric vehicles

Andrew Grill: 0:02

That's a sound many listeners may not have heard before. It's a Formula E car on a qualifying lap. Formula E is the electric racing series, run by the FIA as the Formula E World Championship. Formula E is fairly new, with the first race held in September 2014, and in 2020, this series was granted FIA World Championship status. I've partnered with Genpact, a leading professional services firm for this special two part podcast series around formula E and Genpact’s involvement with the Envision racing team. I was invited to Silverstone the home of British racing to view firsthand the Envision racing cars, as well as speak to one of the team drivers, Robin Frijns, as well as team principal, Sylvia’s Fillipi. Owned by leading digital energy company Envision Group, Envision Racing is one of the founding and leading outfits in the FIA Formula E World Championship. As we'll hear in this two part series, The championship is more than just a racing series, it's a battle for the future. Formula E cars, powered by pure electricity, pave the way for the cars of tomorrow. Genpact is a principal partner of the team, and as we'll hear from Genpact’s Chief Digital Officer, Sanjay Srivastava, the Genpact partnership goes way beyond their logo on the cars. With the cars being almost identical for each team due to Formula E rules, the competitive advantage comes from the work done off the track and at scale. Genpact powers many of the solutions to analyse the reams of data from the car after each race, and provides actionable insights to tune the car for peak performance under race conditions. I spoke with Sanjay on-site at the Envision racing HQ at Silverstone. So let's start the podcast!

Voiceover: 1:45

Welcome to The actionable Futurist® Podcast, brought to you by Genpact. Your host is international keynote speaker and Actionable Futurist®, Andrew Grill.

Andrew Grill: 1:58

Welcome, Sanjay.

Sanjay Srivastava: 1:58

Thank you for having me. It’s great to be with you.

Andrew Grill: 2:01

Now I've only been here an hour or two, and already my mind is blown with what your partnership is developing and what the Envision racing team is doing. Genpact was founded in 1997, as a unit of General Electric, which I didn't know. Perhaps for our listeners, you could tell us what you do for your clients globally and how Genpact has grown over the years.

Sanjay Srivastava: 2:17

Well, we're first off, a global professional services firm, and we deliver digital transformation for mostly Fortune 500 companies, essentially large global corporations, we serve over a quarter of the Fortune 500, we've been obviously around for a little bit, and what's been interesting about us is that we've transformed ourselves. So you as you said, we started as an internal business within GE, spun out, became a private company, and then became a public company, expanded our business, grew to be a leader in the business process space. And then all along the way, we've been transforming ourselves. And so today we've become a digital transformation company. We deliver data, technology, artificial intelligence, enabled capabilities, and then we match that with process knowledge and people and operating model knowledge to be able to really transform core business processes for large corporations. And that's what we do every single day.

Andrew Grill: 3:11

We're here to talk specifically about your partnership with the Envision racing team, we've had an amazing briefing this morning about what you're doing, I was amazed at the various things that you're not only getting out of the partnership, but things that you're learning from the Partnership, which was really interesting. You talked about the aims of the partnership, maybe you could tell our listeners, why the partnership was set up, and actually how it started - it was 2018, wasn't it?

Sanjay Srivastava: 3:32

Yeah, in 2018 is when we actually started the partnership. We've been at it now for multiple years in a row, through four seasons. The partnership actually started because I bumped into the Managing Director for the team at an AI conference I was speaking atm and we got talking about data and the role of AI, and he brought in motor racing, and as we developed the conversation more, it became very obvious. This is something we wanted to look into. I think in the end, though, there are three things that stood out for us. First of all, we have a lot of passion for data and analytics, and so what we do every single day, we love doing it, we love learning off of it. And it was very clear that the Envision Racing team really understood the role of software, that they believe that actually it's the software that fuels their race. It's the data and analytics that drives performance, and that was good to see the clarity of thinking there. But even beyond that, I think there were two other vectors that was that were very appealing and have become even more so in the years since. The first one was their view of mobility, E-mobility and the future of transportation and electric vehicles and autonomous driving. And if you really think about the work we do, and now we've done I mean this is about creating models and new algorithms and approaches and techniques that allow us to get battery efficiency and more power and better performance off of that, better safety. And every single small little thing we do in the end adds up to a larger whole, and we believe that all of this together with the work others are doing in the space will eventually transform the world we live in and it will move towards the mobility and an E-mobility future and a vision that is much more compelling for the world we're in. And then, of course, the last bit was the climate change topic, and it's been on our minds, it's become more and more important. Back in 2018, when we started the conversation, you know, this was a race against climate change. It wasn't a race just for car and motorsports it was a race well beyond that, and this team represented a team that wasn't there to sell a product, they weren't selling a car, they were selling the vision for a very different world, and we identified right away with it, because that's who we are. So it's for all those reasons that we got together, and what's been really interesting is that we've learned so much on the back of it, that we weve iterated through so many ideas, and the good news is not only we helped deliver performance on the racetrack, not only have we helped with climate change and the race against climate change, we've actually taken these learnings and applied it to our real business, so this makes a lot of business sense for us, because we get value from this relationship in so many dimensions.

Andrew Grill: 5:54

One thing you said this morning that really hit home was that in your normal business operations, the clients you normally talk to, it's a year long process, they do something, they improve something, they report the numbers to the street, and they start again. But a race is very compact. Maybe you could use that analogy between what you do with your clients and what happens on the racetrack.

Sanjay Srivastava: 6:11

It's exactly right, which is if you think about any corporation, their annual reporting cycle, they run their business on an annual basis. Budgeting mostly is done year to year, revenue is forecasted, and then all of the different components of the business run on an annual cycle, now that's changing a little bit, and companies are getting more agile, and so forth, but for the most part, that's where the world is at. When we turn to EV (Electric Vehicle) racing, and we look at the work we're doing with Formula E, and specifically Envision Racing, what we're finding is that the entire business cycle - so the idea of thinking through what happened last year in our business performance, what are the changes we're making to our supply chain, to our sales and marketing programmes to the way we financially account for things and manage our treasury operations, core business processes. The normal business cycle would be you'd look at last year's results you plan for the next year, you go through and implement a number of process, people, technology, data changes, to enable all of those things to happen, then you hopefully deliver better performance at the end of the year, and you report it back to the street and it's a full cycle. Well, in a race track, what's happening is we learn from the last race, we then take all of the data, drive analytics, come up with insights, use recommendation engines, and then go make those changes happen on the next race. Well, it's an hour. At the end of the race, you actually get the results back. So that cycle of a year is almost like a morning, one half of a day, we get through the entire cycle. And we've learned often, and what that does for us is two things. It teaches us to operate at scale and at speed, because the velocity is really high. and this is where the world is headed. So what we learn here about doing it at scale, and at that velocity, actually, will translate in the business world. But the other thing is even more interesting, it allows us to be much more agile, and so we can be much more iterative, and we can do incremental learning, and apply it right back, and that insight, that way of working is something we're now translating into all the work we do. So it's really, really interesting, you know how the timelines are so compact, that scale of data is so much larger, and the need to process them at lightspeed is is crucial.

Andrew Grill: 8:11

We heard this morning, the difference between Formula One and Formula E in terms of qualifying, they have several days to get things right and repeat things. As you just said, Formula E is so compact, they literally have qualifying, a break qualifying, and then they're off. So I suppose the partnership relies on the agility of what you can deliver, because you've got to turn things around so quickly and set the car up with almost no time.

Sanjay Srivastava: 8:32

One of the things we find with Formula E is that, you know, this is a race with software. If you look at the cars that are on the circuit, they have the same chassis that the same body, they have the same engine, it's the software that is different, and it's changing from one race to the other in a season. So in Formula 1, where you can actually have a better car, and that gives you a significant performance boost. In Formula E, you can't, it's really how you take the data and the analytics and use that to then make decisions that actually drives better performance, and so that's one of the most striking reasons why we narrowed down on Formula E, because, you know, most of my clients will agree with me is when I talk to them, I talk about the fact that every company is a technology company, some don't know it yet. Well, Formula E is a technology race. It's a race on data and analytics, and that's really the driver of performance - it's been great to be involved in that.

Andrew Grill: 9:23

So you've been working with them for a large period of time. What's the most surprising thing you've learned as a result of this partnership?

Sanjay Srivastava: 9:28

What we're increasingly finding out and by the way, I'm a technologist by heart. I've spent my entire career in data and AI in particular, and so forth. But I'll tell you this, technology is no longer the long pole in the tent. When you look at large corporations, you drive instrumental change and climate change is one of them, but just even think about businesses as normal. The challenge is that technology is there, it's here, it's now it's available. It's absolutely ready for what needs to be done. But instrumenting the change in technology with simultaneously thinking through the changes in people, the operating models, the resourcing the scaling the price process, the end to end value chain, the design, the experience that delivers. And then the data fabric that actually enables all of that you have to administer change across all four of those dimensions in a synchronous fashion, in a very programmatic fashion, and that's a learning that we're finding coming out of this that I hadn't expected. We see this with large customers globally. But because of the scale of data because of the velocity of decision making, and because of the iterated nature of what we do here, we're learning off of that, and it's been surprising to see that but it's so replicable in everything else we do.

Andrew Grill: 10:31

Can you give an example of something you've learned as part of this partnership that's then gone into a client engagement, and they've actually benefited from this partnership?

Sanjay Srivastava: 10:39

The number one thing that is obvious when you speak with this team is their sheer innovative mindset, the clarity of understanding that data will drive competitive differentiation for them, and the nimbleness with which to approach new things, and so, you know, I work with large corporations every single day, and my number one advice is culture. How do you think about innovation as a culture? There's a difference between the world invention and innovation, and many companies focus on invention and invention is nice to do, but it's actually fundamentally wrong for businesses, because you can't scale it, you can't do that in volume. Innovation is about leveraging the ecosystem, it's about building on the shoulders of others, it's actually about designing the thinnest layer of technology you can put on top of an existing set of capabilities already available to drive significant value-add, and it's the thing that delivers return on invested capital. So this idea of working with teams, and then learning from this experience, and really taking that culture, that mindset, and the approach of top down to the companies I advise has been a great learning that we've been able to extract.

Andrew Grill: 11:44

What I found in a local point of view, as the team here is quite small, and many of them have different roles, and they wear many different hats, and only some of them are allowed on the racetrack and they have to do things remotely. So I suppose you're right about culture. and it's great that you're working with a team that is just so nimble, they have to be doing that, and it's all about technology. Talk to me about the people side, so how do you involve Genpact people with the Envision Racing team? Obviously, you're not the only person that interfaces. How's your culture learning from this very agile, small team here?

Sanjay Srivastava: 12:11

It's a great question you ask because there's a large set of people that are involved in getting the race performance to where it is, but actually even broader than that, and leveraging our relationship, because the relationship isn't just about winning a race, it's actually about a lot more. So clearly, there's a team of data scientists and analytics professionals that get behind the monitors, if you will, and actually work through the data extraction, the data engineering and the AI modelling, and that's a great set of people, and I have a lot of respect for that team. But even beyond that, you know, as we think about the work we do together has on the future, the world we live in, and you know, our purpose at the company is really about the relentless pursuit of a word that works better for people. Now, I said that very quickly. But every single word in that statement was thought through very carefully and actually intensely debated. We have a community of 110,000 employees, almost as many partners and ecosystem colleagues we work very closely with, and we're all focused on actually taking a purpose driven approach to the work we do. And so the work we do here has a lot of meaning because beyond actually delivering the performance, it has implications for climate change, and so we get involved, we take a lot of the work out, we talk to our candidates that we're interviewing, and we tell them that story, and they get a sense for who we are beyond the specifics of the job they're recruiting for. We talk to our clients about it, and frankly, our clients want to get engaged in that story, and then two plus two becomes 10, and those sorts of things. And so for us, this has been more about purpose, more about community engagement, more about, frankly, talent. You think about the talent war that's going on, you know, having a larger purpose and being clear and very articulate around it, is super important and actually convincing candidates that we're a great place to work. So it's really had profound implications, for the company well beyond what I think has just been fantastic work on the artificial intelligence and the data side as well.

Andrew Grill: 13:58

We've heard a lot of talk about sensors and data today, and businesses must use all these inputs to be successful. So how do your solutions source and process the reams of data produced during a race?

Sanjay Srivastava: 14:07

You know, artificial intelligence is a really large role to play over here, because what's happening is a combination of three things. You've got a lot of data, so we're down to hundreds of telemetry inputs from the vehicle itself, to all of the weather, and, you know, we look at the track and the road surface and the coefficient friction and every single bit right, and then, of course, the driver performance, the competitor's performance, historically, and then we take all of that and design simulation programmes that our drivers can actually practice and really simulate what it's going to feel like to be driving on that track, on that date, in those weather conditions, against that set of competitors. The better we get at it, of course, our drivers are faster because they've kind of practiced that. Now to do all of that you need a ton of data, and it isn't just that you need the data, you need an infrastructure to actually process the data in a meaningful fashion, and so we've had to layer a foundation of data underneath all of this, and it's kind of the hard part, it's more of the grungy part of the work, but it's super important because if we don't get that right, you can't get the AI right, at least at scale, you can't get it right. So that's been one big piece of it. I think, the second big piece of it is essentially scale and speed, and so we're talking about 1/10 of a second difference between the first and the last person in a race. I mean, think about it, it's 1/10 of a second, and then everyone is in between those two spectrums. And so when you're talking about that level of speed, and you're looking at the scale at which we're trying to process the data, you need institutional, mainstream, production quality infrastructure that can ingest data, that can classify it on the fly, that can auto ML(Machine Language) it, that can run algorithms at speed and be able to come up with results, so I think that's been the second thing. And then, of course, the third one is how do you actually make sense from the data? And so you know, we look at, for instance, audio conversations that are happening, and we're able to listen to the audio, converted it into text, classify that text on what's relevant, and what's noise, I mean, 99% is just chatter, you don't need that, but it's the one or two specific things, then feed it to the driver to the engineer, and then therefore to the driver to be able to take action on it. And it's the sort of thing where if one of the other race drivers that you're racing against is going to take a tone, you get to know about it. If you know, about it, 30 seconds late, it's too late, you can't do anything about it. You know, about it a second later, you can actually do something about it. And so being able to process all of that is where the AI comes into play, and we use a lot of extraction techniques, we use natural language processing, we use voice, and extraction, and then we use a lot of ML modelling to be able to simulate that. If we didn't have the data foundation, and if we didn't have the AI on top, I don't think we could take the car out of the garage.

Andrew Grill: 16:40

I just want to break down what you just talked about the radio analytics engine. Just for our listeners, this is a very interesting thing that I hadn't really thought about. All of the radio transmissions from all the teams are open and asked a question this morning - why? Because of fan engagement. People want to listen to their favourite driver, and if you've watched those documentaries about Formula 1, you hear all the messages coming through, and sometimes they're a bit rude, but what's fascinating is, as you said, you basically listen to all those conversations, and then you make sense of them, and you then say, well, do we need to let the driver know that someone's about to pit or they've got an issue? And actually speaking to one of the drivers this morning, he said they also use code words, because they know that everyone's listening. What I thought was interesting, if you look back to the Enigma, and the whole code breaking of Alan Turing and everything else, they were listening for one word in German, and they worked out that was the start of the code. You're listening to things in real time, you're doing speech to text, right, you're basically presenting the data, then something has to analyse whether that's worth worrying about or not. That's got to happen in real time, and as you say, it's got to happen before the next turn.

Sanjay Srivastava: 17:39

That's exactly right. It's a fascinating piece of work, it's super interesting, because it's open to anyone, as you say, anyone can listen into those channels, and it's meant to promote more engagement on the fan side, and it's actually if you listen to it, it is a much more enjoyable experience, if you will, if you're into racing. The challenge for us is, you can't do that with colleagues, with human colleagues, you need about a couple 100 people to be able to listen to all of this and pick up the pieces and do it in real time and get it and you still can't get it to the driver because you gotta get to the garage, and then the operations team and the engineers, and then over to the driver, that's just a very long loop. So you need something that can process that at scale. So to break it down, we automatically listen to the conversation. First, you've got to separate it. So you know, this is Sanjay talking versus Andrew talking, so you got to put these into different buckets, you know, who's who, and then you can manage a conversation thread through. Second, you have to then sort of by that speaker, or by that team going back and forth, you have to then convert it into text, so you can actually do something with it, and this is a bit about structured data versus unstructured data, so it allows for computers to be able to work on it, so there's a process you have to go through to kind of convert that. But the real part of this, as you said, is actually the classification. You've got to classify something that's being said as kind of a chatter, side conversation, not really interesting, and the little bit that's said, that is super interesting, and a competitive advantage if you knew about it, and could act on it in time. And that's the classification work, and that requires a lot of training over time, because you're essentially telling a computer, because it's about the only thing that can do it as fast as it needs to be done. You're teaching it how to be able to tell which is which, and that takes time and training and then modelling and really good data science and AI Engineers, and we spent a lot of time, and got that right. Almost a quarter of a million conversations later, the amount of training and depth that has gone in, and by the way, I must say it's in a very collaborative way with our AI Engineers and Envision Racing's drivers and Engineers. You can't do that alone, you need subject matter expertise, you need people that have got their fingers dirty, and you need people that really understand AI, and that team together, kind of cracked the code on this, and now we're at a point where we're getting massive performance boosts from being able to do that.

Andrew Grill: 19:44

How would you use that in a corporate environment? I've talked to a lot of people about the use of ambient voice. We all have a voice device either in our phone or at home and we talk to it, and I've been talking for a while as a Futurist about ambient opportunities. So we're in a meeting room right now. With permission, it could be listening to what we're saying. Talk to me that how what you developed with the radio analytics could be used in a corporate environment with permission?

Sanjay Srivastava: 20:05

There's so many examples, Andrew that come to mind. I'll start with something that's simple, because it's here and now, and then we can talk about some of the things that I think are coming in the future. I'll tell you very simply, I mean, we serve clients across so many different industries, we just pick one, I'll pick financial services. One of the challenges is, you know, for banks that are operating, let's say, a lending platform, they've got to be really compliant with the regulatory requirements in their business. You've got agents and colleagues and employees and partners that are on the phone working through with a client on the other side, or working through a loan document, a loan processing mechanism, and there's things you can say, things you can't say, there's questions, you can ask the questions you can't ask, and you have to be exactly right on that. Now, you don't need to run a large distributed organisation with tons of these kinds of applications going through, but you have to do it exactly right. So a great application of AI in exactly the same idea is to actually put that into play, with permission, and then be able to use that to essentially coach our agents on getting to better performance and following the right process, and so that's here and now, I mean, we're doing that today. I think more broadly, if you look at it, the real use and application of this is, as you start understanding not just the text and the context of what's being said, and the words themselves, but you start picking the tone, and you start picking voice and annotations. You start picking up signals that you and I in a real conversation would use to be able to make decisions. You know, what I just talked to Andrew about this, I think he's gonna ask me this next or, here's where he's headed, maybe you can give him this helpful tip. Those sorts of things come through, not just based on everything you're saying, but the way we're interacting and the way we're, you know, looking at each other, and so forth, and the magic of that, you know, is that if you can capture some of that with AI, you can use chatbots, you can use conversations to be able to then sort of say, before you hang up, Andrew, here's something you want to think about. You know, we use a piece of technology inside the company, and we've all been through this whole COVID phase, and it's been incredibly tough from an employer and employee engagement perspective, and we implemented a piece of AI technology that actually goes out and speaks - by email, we tell people that it's an AI on the back end, there's a whole ethics piece to it as well. What it does is it queries people on how they're doing, and depending what you say, I'll ask you a few more questions, and will kind of come back and forth. Obviously, Andrew, we want to know how you're doing, but what I think we're trying to figure out is across 110,000 employees now working in a hybrid environment, not everyone we're seeing every single day, they're mostly working with colleagues and they're not working with their managers as much, our entire HR system is hierarchically trained for managers to evaluate employees and values, you know, so so none of that now works. And so we use AI to figure out, you know, where are the hotspots, where are the concerns, what are the issues, what's on people's minds, and that gives us instantaneous information to be able to do sort of respond in a positive way. So you know, the applications of this are enormous, we're seeing this in so many different cases, and I think there's a lot more to come

Andrew Grill: 22:50

As a Futurist, I dream up some of these things, and what you've described is something I've been talking about for a while that ambient voice might help with mental health issues, so if it knows that normally, I have a happy disposition, and today, I'm not sounding so great, it then my

say: 23:02

"Andrew, get your buddy to ask if you're okay", because now we're working remotely, we want to make sure there aren't any health issues we should look at. So finally, my predictions have come true, and this is this is a reality.

Sanjay Srivastava: 23:12

You're exactly right. I saw something recently, that is meant for parents of young kids, and it's it's something that teaches a child how to brush their teeth, and you know, how many seconds on one, you know, top half versus this or that, and it's amazing how much difference that voice makes and kind of driving an experience that is more compelling, and so yeah, we see it every single day.

Andrew Grill: 23:31

One thing I heard today that really impressed me was you're not just talking about the climate change issue, you're really behind it, and part of it is educating the next generation so that they understand not just that Formula E is a great race to watch, but there is a whole purpose behind it. You've set up this thing called Fan 360, maybe explain what that is, but what is the ultimate goal to get people talking about climate change?

Sanjay Srivastava: 23:53

Well, if you think about EV racing in particular, I think there's two broader goals. One is to help the innovation and to speed up and accelerate the innovation in parts and components that are going to make EV more affordable, more accessible and more efficient. Really, the other track is actually the race against climate change and getting awareness in the in the world out there, and then making electric cars, which is one way to address it. You know, a lot more acceptable, it's for us, it's not like the special thing on the side that we have to wait many years on, and so the progress we're making there is incredible. But to do that, you know, it isn't about winning the race, it's actually about engaging the fans and the audience and getting them more compelling and sticky experiences that they want to come back for, and they engage in a manner that actually gets the idea through. And so really the work is actually pretty straightforward. What we do is we work across all of the data elements of understanding was at Fan is, you know, it could be, you know, our team's data, it could be you know, people hitting websites and such, mailing lists. It could be you know, publicly available information, Twitter and Facebook and other things. It's information that we can source from third parties, but the idea is that you want to bring a 360 degree view of an individual and you understand all the different ways they've interacted with you in the past, and then you use that to predict where they are in the journey of engaging with you, what is the next step in the journey and how to embrace them further and pull them in more with the right bit of information and the right nudge at the right time, through the right media. That's a business challenge, stepping away from racing for a second that every single Corporation is now facing. We're increasingly living in a world you've got text, you've got voice, you've got phone calls, you've got chatbots, you've got social media, and across all of that, you have to manage a relationship that is holistic, that is complete, and then you have to progress it on a journey, and so the lessons we learn here are so broadly applicable to pretty much everything we do in our lives. It's just been amazing.

Andrew Grill: 25:41

So talking outside racing, and the whole need for transformation. You're the Chief Digital Strategist for Genpact, I'm sure you deal a lot with digital transformation initiatives. What are some things that clients need to consider before they embark on a digital transformation?

Sanjay Srivastava: 25:53

That's a great question, Andrew, you know, I start with digital transformation. As a term, I think, oftentimes, and I'm glad to use the word because I think oftentimes, people talk about digitization and digital transformation as the same thing. Actually, the couldn't be further apart. You know it's important to understand that digitalization is about taking an end to end process. We've all done this, but just to quickly put it out, you dig an end to end process break into its parts, you take every single part, you automate it. And then the whole process gets better. It's faster, it's quicker, it's more efficient, it's probably cheaper, it's a little bit more agile, great. We got digitization done. That that is not digital transformation. That is a better process that runs faster. The thing about digital transformation is you've got to take a step back, you have to think about what's the value of delivering what is the process you using? What's the end to end value proposition? And then you before you do anything else, you sort of reimagine what it needs to look like. How do you drive more sticky experiences? How do you get better revenue growth? How do you get a fundamental disruptive differentiator in industry? And now you're able to do that with these new emerging technologies that have come through, that you probably didn't have 30 years ago when you put your foundations in place. And so that's the purpose of digital transformation, and by the way, once you're done with it, the work actually changes, it isn't the same work happening faster, it's different work, because you've transformed the way things get done. Now, on one side, that's super insightful, because it allows us to sort of spot a digital transformation project different from a digitization project. And that's important because you take the right steps to get there. But on the other side, what that means, is now to drive digital transformation, it isn't just about technology alone, because you're not just automating the parts of a process. It's actually about reimagining all of that value chain. So you need people, you need the operating model, you need the subject matter experts that can kind of come in, you need the skilling to get them into the new world and adopt the new capabilities. You also need a design and an experience that drives a more sticky value proposition. And so you have to rethink that. And so to get digital transformation done, you have to think about people, you have to think about process, you have to think about data, and of course, you have to think about technology. So the number one thing I talk to boards that I'm working with or executives at Fortune 500 companies is the fact that be clear, that digital transformation is different from digitization. And to drive digital transformation, you have to purposefully execute changes on people, process, data and technology. And that's a big insight, and of course, that has many ramifications, it changes the role of the CIO, it changes the role of the CTO, because now you're actually looking for people that have outside-in perspective to bring new innovative ideas. We need people that have inside-out perspective, because they need the championship, they need to drive change at a fundamental ground level, and transform the company, and so many implications on the back of that, but that's super important.

Andrew Grill: 28:33

Like me, you've been in the tech industry, your whole career. What surprised you most about the last 10 years? And what are you excited about for the next 10?

Sanjay Srivastava: 28:39

I came in from an all-tech background into a company at the time, we weren't major in technology. I was super excited and humbled by the learning that in the end, technology isn't the long pole in the tent, that it is actually about getting people and processes and data and technology executed and together. And so my biggest learning in the last 10 years is really for large corporations, really for fundamental transformation projects, how to make that happen in a much more compelling way, and to drive actual return on capital. The next 10 years, I think things will be very different. Three things stand out. I think the pace of change is the slowest it's ever going to be. So as much as we've gone through all the digital acceleration in the last few years and the pandemic, and you know, 10 years of work has been done in two, three years, and the like, the reality is, this is the slowest it's ever going to be. The foundations are now coming together in a manner that the pace of change will only accelerate here on, and so the next 10 years are going to be interesting because there will be a play for people that can lead with data and analytics and agility and culture and learning and talent, right? We're not hiring as an example talent for skills anymore. We hire for attitude, because the reality is the skills today won't matter tomorrow, and frankly, the better reality is we don't know what skills we need tomorrow. So you need talent that can adapt, that can learn and this curiosity, the humility mindset and so companies that understand that the pace of change is only going to be increasing massively in the future and therefore design a culture and organisational strategy, a data foundation and a technology leaning are going to get ahead, and that's the reality of the world.

Andrew Grill: 30:07

We're almost out of time. Before we finish, I want to run you through my favourite part of the podcast: a quick fire round. iPhone or Android?

Sanjay Srivastava: 30:13

I use an iPhone.

Andrew Grill: 30:14

Window or aisle?

Sanjay Srivastava: 30:15

Window. Online or in the room? Both actually.

Andrew Grill: 30:17

Your biggest hope for 2022 and beyond?

Sanjay Srivastava: 30:20

We get a handle on climate.

Andrew Grill: 30:21

What's the app you use most on your phone?

Sanjay Srivastava: 30:23

Unfortunately, it's Outlook

Andrew Grill: 30:25

The one thing you won't be doing, again, post-pandemic?

Sanjay Srivastava: 30:27

Travelling as much as I did before.

Andrew Grill: 30:29

The best piece of advice you've ever received?

Sanjay Srivastava: 30:31

I can give you a personal, I can give you a professional one. Always ask the people around you what is the one thing they think you don't want to hear, because the blind spots are what get you in the end, and being thoughtful about that is super important.

Andrew Grill: 30:43

What are you reading at the moment?

Sanjay Srivastava: 30:44

I'm reading a book on DaVinci by Isaacson. I've just started the book.

Andrew Grill: 30:50

Who should I invite next on the podcast?

Sanjay Srivastava: 30:52

That's a great question. You should invite my boss Tiger Tyagarajan- on learning. He's got a great mindset around learning.

Andrew Grill: 31:00

I'll take you up on that. And the final quickfire question, how do you want to be remembered?

Sanjay Srivastava: 31:03

I want to be remembered as a great father and a great husband.

Andrew Grill: 31:06

Now as this is The Actionable Futurist® podcast, can you give us three quick things that our audience should do today, when it comes to using data to develop high performing solutions for clients?

Sanjay Srivastava: 31:15

Starting thinking about a foundation, it's not going to happen without the foundation, and the foundation is easy said, hard to get done, because data is all over the place. There's tons of governance and lineage issues around it, and fundamentally give data voice in the boardroom, right? It needs to have its natural representation, it's in its own asset class. The second is experiment and innovate with new emerging technologies. The pace of change is significant, and the new stuff that's coming out is really a game changer, and if you don't use it, or if you don't try it, you won't get on it. And so that's the second thing. And the third one on data is ethics. You know, it's a topic, we haven't touched upon Andrew, but data ethics and actually more broadly, digital ethics is a super important topic, and it's going to become more and more important in the future, because these capabilities are coming through really fast. and, you know, as much as we want to use them, if we're not thoughtful about how we use them, we can get into a lot of trouble collectively as a system. And so, invest in an ethics subcommittee. I believe that boards will end up having a digital ethics subcommittee, just like they have a compensation or an audit subcommittee, it's just going to be the part of the way we do things and get started early, because you cannot apply ethics at the end, you know, you can't go get the job done, and the temll me just apply a layer of ethics, and so if you don't build it in the foundation, it's difficult to get it right.

Andrew Grill: 32:23

Last question, how can people find out more about you and your work?

Sanjay Srivastava: 32:26

I'm on LinkedIn, that's probably the best way to reach me, and I'm super engaged on that forum and happy to help and advise and be part of ideas, and I'm always looking for great ideas and great connections.

Andrew Grill: 32:36

Sanjay, thank you so much for your time today, and thanks for having me at Silverstone. I've learned so much, and I'm even more excited now about Formula E.

Sanjay Srivastava: 32:42

Thanks for coming up here, and thank you for your time.

Andrew Grill: 32:47

I'm delighted to also be speaking with Envision Racing Team Principal, Sylvain Filippi. Had a really interesting overview this morning about the team, what you're doing here, the challenges you're facing. Talk to me about how the team got started and how you personally got involved in Formula E.

Sylvain Filippi: 33:02

It's a long story, so I'll keep it short. Personally, I was involved in a group in the automotive industry, all my jobs were in the automotive industry in the early 2000s. But I really fell in love with the electric vehicle technology, when I was in consulting, working for car manufacturers at the very beginning of their EV programmes, and then I drove one of the first Tesla roadsters in the UK, and that really opened my mind on you know, what electric cars could do. And then it took from there really, so I started being involved - I started a startup on electric racing, and then FIA came up with a Formula idea and it took off from there really. So yeah, we started this team, we are one of the founding teams. Informally we started the company in 2013, and we started racing in 2014. It seems like an eternity away, but it's not that long ago, and since then, it's been really, really fast paced. As you know, every year changing the technology on the cars, and the technology is evolving so rapidly, that the sport has been growing so much. And yeah, it's been it's been really fun.

Andrew Grill: 34:00

I got to see one of the cars downstairs, which is a generation 2 car, and next to it is the dear old generation 1 that looks a bit unloved now, but talk to me about the next generation generation 3, what that will do on gen 2, and what are the advances in technology that are going to help you?

Sylvain Filippi: 34:14

The main aspect of Formula E is the technical roadmap, right? Formula E as a sport is two things really. The first is a technology play, right? Our job is to use the motorsport engineering resources and mindset and so on to accelerate the development of this technology. So from Gen one to Gen two, we had a bigger jump in energy density of the batteries and power and efficiency and so on. And Gen two that we are currently racing versus Gen three next year, which we are just starting testing, we're doing another huge jump in technology. To give you an idea, the power of the car is going from 250 kilowatts to 350 kilowatts, which was in percentage terms and a really big jump. But it was interesting that for the first time we are designing and racing an electric car that is lighter and smaller, so the new car will be around 60kg lighter, which in motorsport terms is gigantic, it's a really huge amount of weight to remove from the car. And the car will also be shorter and narrower, which is better for racing and so on. So we need to fight the cliche that an electric car has to be big and heavy, and might be faster ar accelerating and so on, and we're now developing a car that is lighter and smaller than the Formula 1 car. You know, 10 years ago, no one would have ever thought that possible, so that's really fun. And then the other big area of development, you know, for that particular generation of cars is the regenerative braking (regen). So of course, regenen is a super important part of electric cars. Currently, we regenon the rear axle at 250 kilowatts. Next year, we are adding a powertrain on the front axle as well, so we have the 350kw at the back 250kw on the front, which means we will be able to regenerate 600 kilowatts. That doesn't mean much a lot of people, but it means it's probably 8-10 times more than already a very good electric road car in terms of regen. So much so that we are taking a brave move, and we've actually removed the rear brakes on the car - we don't need brakes anymore, this brake's hard enough. So that's a glimpse into the future, right? Like if you can optimise the regen of these cars, it's all benefits really, you don't need brakes, you remove the weight from the car, you remove some complexity, and every time you brake the car using regen, you don't waste the energy, you get that energy back in the battery. So to give you an idea, to get your head around it in Gen 3, if you look at the total energy that the car will use to cover the race, 40% of that energy will have been created by the car itself. So that's pretty incredible, like the car becomes its own power station, yeah, and that really shows you what the picture looks like. And then finally, we are also creating the capability for very fast charging, because really we know for mass adoption of electric cars, the cars are getting there, though, in terms of like really good range and price point, and so the technology is getting there. The final piece of the jigsaw is enabling long distance travel and that's through you know, a few times a year not that often you need to fast charge on the journey. Currently, most cars can charge at around 200kw, the very best ones can have a peak charging rate of about 350kw thanks to high voltage that was developed in Formula E four years ago. Next year we have the capability to charge at 600kw, which is completely crazy, like there's nothing like it, you know, in the real world, and again, it's a it's a technology showcase, right? If we can do this safely and reliably, then we open up for the future this idea of charging stops that take five minutes, 5-10 minutes to add another 100 or so mile range and remove all of the all of the perceived issues around the range of electric cars. So it's really exciting, like really technology's going so fast, and we are pushing it even harder by by putting it in competition.

Andrew Grill: 37:48

I've followed motorsport for years and actually worked at the Adelaide Grand Prix back in 1990, so I've seen how the Grand Prix, the Formula One, Formula E it is used by car manufacturers, tyre manufacturers to basically make their road products better. So talk to me, and you mentioned some of it there how the innovations that you're developing, that your competitors are developing will then get into the road vehicles that we're seeing on the road and will make it faster, cheaper, more efficient. That's obviously one thing you're doing. We'll talk about maybe climate change in a minute, but talk to me about the innovations on the racetrack that then get onto the road car,

Sylvain Filippi: 38:19

It's back to the main principle of the Formila E roadmap - it is designed to focus our attention, resources, and so on the powertrain. So, you know, basically, in seven years, we went from a car that was producing 150 kilowatts of power to 350 kilowatts of power. And you know, we've more than quadrupled the amount of regen we're getting in that car whilst lowering the weight, so it's really about maximising energy density, which is, you know, the amount of energy you can store in a battery for a given weight and volume, and then the power density of the powertrain. So basically a smaller, lighter, more efficient powertrain that can produce lots of power. That's what makes an electric car better for the road basically, tyres also come into play, of course, suppliers, and so on, but these are the main movers. I talked about all the previous electric cars on the road up to last year, pretty much we're operating on a kind of old standard of 400 volt architecture, and at Formula E, we started racing on 800, even 900 volt architecture, from the beginning and up to now, and now we've proven that it's safe and reliable, and now the latest generation of electric cars or latest ones are going to be based on that architecture that was really pioneered by Formula E, of course the components are different, they are designed for mass production, but they use our concept and our design fundamentals and produce that, and make that into into mainstream cars, so that's really, really fun. And you know, that was in the past, in the future where I talked about about superfast charging, removing the brakes, this will happen at some point in road cars, and that's what's fun. We are basically a very extreme, very harsh testbed for technologies. You know, you've seen it before, designing particularly is on the CAD on the computer is one thing, then you have to test them in the real world. Well, doing testing by yourself in the real world is only one thing If you then start to compete with 10 other companies doing the same thing, that's when you really, really push the technology, and if you can make it work there, then you're pretty confident it's going to work in the real world.

Andrew Grill: 40:09

You said this morning that because in Formula E, many things are quite the same across all competitors, so all you've got is data analytics to make things faster and faster. Talk to me about how your partnership with Genpact really helps you become more and more competitive and how the partnership has evolved and how it's working for you.

Sylvain Filippi: 40:24

The cars look the same because we decided not to spend any time on aerodynamics that make race cars go faster, but don't make road cars go faster. So the cars have the same chassis so the aerodynamics are the same, but all the powertrains in the cars are different. So we design our own powertrains, basically, from the battery to the drive shaft, everything is designed by us to push that development. But it's one side of the story. Ultimately, we're here to win races and championships, and the car is one element to it, you know, you have the car that I talked about, you have got the driver. Racing in Formula E is different to other race series. So drivers have to be very aware, you have a lot to do on the car, you have to think quite a lot, because it's not just about going fast, you have to think about your energy management, and there's a lot of strategy involved. Then you have a third pillar, which is the rest of the team operations, the strategy, the optimization of the car, and so on, and that's entirely a data game, basically. Like it's not new, it was already the case in motorsport, but because these cars are electric, they generate so much more data, and also, the way to make these cars faster is so much more through data. Of course, we can still do the normal mechanical changes on the car that make the car go faster, but once you've done that, then a lot of optimizations are on the system, the controls, the software of the car, to make it more efficient, and use the power in the right place, and so on, so that's that's all data. And then all the strategy around the attack mode, you know, the sporting aspects of the sport is also entirely based on data. So really, I mean, my team recognised a few years ago that, you know, if we are to achieve great things, we can't do it on our own. And clearly the data, the big data problem, which is really exactly what we have here, you've got to work with specialists, so the very clever people at Genpact are really great at data science in general. So they helped us at first how to gather the data in the first place, how do you store it and structure it? We were already pretty good about it on that because we are a race team, so we tend to be good at it, but you can always do better. So how do you structure the data, and then back to the challenge of Formula E, you have less than an hour to get all of the data, understand it, gather insights, and then make actual decisions on the car, and you can do that at the last minute, you have to allow time to actually implement that decision. So you're taking about a few minutes to basically do all of that. So Genpact have been helping us on how to do all of that quicker. It's basically a Big Data and Data Science Challenge, which was really fun, so we are learning a lot. I think they are learning a lot also, because if you ask them, I think even now they're still so surprised by the pace at which we are working, right? And that's normal, it's competition, right? So speed, speed is really everything. So we think very fast, we make decisions very fast, and we implement very fast, which I think for them is fun, it's challenging, and gives them good case studies for other applications. And something that is equally important is that of course, as the greenest team on the greenest grid as we call ourselves, we have to lead by example. So we are of course a carbon neutral team, but carbon neutrality is a lot of work, you have to first measure your emissions do that accurately, then take all the steps necessary to remove these emissions to the bare minimum possible, and then offset, and all the steps. So that was very time consuming. I only have about 40 people in this team, so we are approached Genpact and said, hey, that's also a data problem, nothing to do with making the car go faster, but can we make that more efficient, and actually, we developed together a carbon calculator, and now does this exact same job in a fraction of the time it used to take. And actually that's going to be a template, I think for many many companies in the future, because everyone's going to have to do all this, and if we can do it reliably, and quickly, it's going to interest everyone, so yeah, these are a few examples.

Andrew Grill: 44:01

So final question, what's the most exciting part about managing a Formula E racing team?

Sylvain Filippi: 44:06

Everything's exciting. This job, it's so varied, you go from one minute, speaking to drivers, and then you're on the technology of the car, then we are talking to commercial partners, and the media side of it. Because really, it's, as I said, it's half a technology play and half a media play, right? There's not much point doing all of this, if no one can see it or hear about it. So our job is to grow the sport to make sure we have some form of impact. As I said, sometimes I think Formula E a powerful recipie, because it combines the technology of the future that people are increasingly getting interested in, but also it creates - it's a sport, you give the passion and the engagement and the interest of people that you know you don't get to normal conference, you know, as interesting as it might be. People are way more engaged in sports. They are they are emotionally invested. So they are they tend to listen a lot more and more carefully. So, you know, the better we do in a championship then the larger share of voice, and then it's our responsibility to use that share of voice to talk about what we care about, you know, renewable energy, electric cars and how the future can be great if we do all of this stuff.

Andrew Grill: 45:10

Sylvain, thank you for your time. How can people find out more about you and the Envision Racing team?

Sylvain Filippi: 45:14

Well you can go on our website envision-racing.com and then you go on all the social channels, Formula E and then we have a lot of races now coming up. So we just came back from Marrakesh, we have a race next week in New York, then we come back to London, and then we go to Seoul in Korea, mid August to finish the championship. So lots of races coming up. I encourage everyone to just have a watch. The race is about 45-50 minutes, you won't get bored, it's action packed, and it's a really great way to see what electric cars can do, but also it's really good entertainment.

Andrew Grill: 45:44

Well, I'll be with Genpact again in London in a few weeks, so good luck for the rest of the season.

Sylvain Filippi: 45:48

Thank you.

Andrew Grill: 45:50

I hope you found part one of my Genpact formula E Episode is interesting as I did recording it. Stay subscribed for part two, which I'm recording on site at the 2022 London E-prix to be held at the ExCeL centre in the docklands area of London. We'll be covering the race day activity from the Envision Racing team, as well as hearing more about Genpact's ESG agenda and how they're winning the war for AI talent.

Voiceover: 46:15

Thank you for listening to The Actionable Futurist® Podcast brought to you by Genpact. You can find all of our previous shows at actionablefuturist.com, and if you like what you've heard on the show, please consider subscribing via your favourite podcast app so you never miss an episode. You can find out more about Andrew, and how he helps corporates navigate a disruptive digital world with keynote speeches and C-suite workshops delivered in-person or virtually at actionablefuturist.com. Until next time, this has been The Actionable Futurist® Podcast brought to you by Genpact.