You're listening to From the Horse's Mouth. Intrepid conversations with Phil First.
Welcome to the latest edition of From the Horse's Mouth podcast. I'm your host, Phil First, and joining me today is somebody I think I've known for around 20 years. His name is Francisco, or as a lot of us call him in history, Frank Duza. Frank, do you want to just quickly introduce yourself to the audience who don't know you?
Sure, Phil. First of all, thanks for having me on the podcast. I was the founder, co-founder of Cognizant Technology Solutions in the early 1990s. I spent 26 years at Cognizant, including 12 years as CEO. We grew that company from a startup to 280,000 people, $16 billion of revenue, and about $40 billion of market cap when I left about six years ago. I created Recognize, which is a private equity business that focuses entirely on investing in the next generation of digital services businesses, and I've been doing that for the last six years. It's great to be with you.
Terrific. Thanks. It's good to have you back. I've known Frank for like 20 years, and during which time I've seen him grow one of the largest scale, most successful services firms in the industry. I know you've probably been asked this question many times, Frank, but as you look back now and you look at where the industry is now, what maybe two or three things would you credit most to your success at Cognizant?
You know, Phil, I think there were two or three things. The first is that we founded Cognizant at a moment when the industry was going through a massive operating model change, and that was the offshoring moment in the early 1990s. There was a whole confluence of things that happened at the same time, low-cost bandwidth, the internet, and so on, that enabled global delivery to happen at scale. We were in the right place at the right time. The second part was that we executed really well. We had an incredible team, and we spent a lot of time on this idea of talent density, putting the best team against the highest opportunities. The third thing is that we created for ourselves and with our investors the opportunity to invest in the business. We had a rule of 40 business before we talked about the rule of 40, which was that we maintained our margins at a level consistent between 19 and 20%, below where our competitors were, to give us the room to reinvest in growth. Our investors should expect to have faster growth as a result of that investment. So I think it was those three things: we were at a moment when the industry had tremendous tailwinds, we had the best team in the industry, and we had the space to make the right investments. Those things together created some magic.
Drawing some comparisons from then to now, would you say maybe it was also a time where some of the incumbents took their eye off the ball? They might have been a little complacent and they didn't really focus enough on who the next wave coming up behind them. And that's maybe happening now a bit.
Yeah, I would absolutely, Phil. When industries, whether it's our industry or others, go through moments of big change, you have the well-documented phenomenon of the innovator's dilemma, which is that the incumbents tend to focus on the current operating model, the rules of competition that they are comfortable with, and it's very hard for incumbents to reinvent themselves. At those moments in time, the challengers have an advantage. They don't have the baggage of the past. They start with a clean sheet of paper, and they're able to disrupt the status quo. You see the pecking order shift at these moments of great disruption.
Yeah. So let's move along. I know you put out a paper very recently, and obviously we'll get into some of what you talked about there, but one of the things you started with was a core paradox where you said code is becoming more valuable while it also becomes worthless at the same time, and the services industry is built on monetizing that labor. What do you think this paradox means, and how would you advise a CEO today on communicating this on earnings calls when utilization drops, spot AI, productivity rises?
Yeah. In the white paper, I talk about this idea that code in some senses has never been more valuable. If you think about some of the most valuable companies in the world, we talk about Anthropic, OpenAI, and SpaceX, these massive IPOs that are lining up, companies that have achieved revenue growth in periods of time that have never been seen before. What underpins the value of many of these companies is their code, their product which is embedded in code. At the same time, the act of producing code, the cost of that, is falling to zero. Large language models today are incredibly capable of writing code, and the marginal cost is tending towards zero. So you have this paradox where code has never been more valuable, coding is becoming lower and lower cost. If you think about that in the context of any other industry, if you were the CEO of any other company where your product has never been more valuable and your factor of production is becoming cheaper, that would be a formula for tremendous value creation. The issue in our industry is that we have historically anchored pricing on the input, not on the output. You don't go to buy a new car and say, 'I'm buying four tires and a transmission and spark plugs.' You just go buy the car. In our industry, for some reason, buyers have got used to selling the tires and the chassis and the spark plugs. So I think the industry has this great opportunity to move to output and outcome pricing, and then have a situation where the factors of production change and create tremendous value.
Right. You articulate that very well. It's how do you sell an experience versus the inputs. It's a big mindset shift that needs to happen. Do you think it's possible in the current way that big corporates are set up and these relationships were set up to make this mindset shift leap?
I think so. The industry has been talking about this for a long time, Phil. It's been accelerated by AI and generative AI in particular, but as long as I've been in the industry, we've been talking about moving more towards output and outcome-based pricing and commercial models. The industry understands how to do this. There are some places where it's quite possible, and by moving to output and outcome pricing, you align interests between the service provider and the client much more strongly. So I think it's possible. But it's not an easy transition for the incumbents because everything about the industry right now, the culture, the way people have been trained, many of the incentives and metrics that we traditionally use to track the health of a business are anchored on what I call the scarcity era, where producing code was the scarce resource. We anchored on utilization, numbers of people, and many input measures. Making the shift is going to require firms to focus on a new set of metrics and then change the culture and the compensation accordingly.
Yeah. I sat through a tremendous round table last week with around 20 major clients present, and we got into the inertia that they're facing just trying to move their own AI agendas forward. The real thing everything kept dialing back to was talent. You can talk about process debt, data debt, tech debt, but if you don't have access to talent with the passion, the curiosity, the desire to do things differently, you're never really going to make that shift. I get the sense maybe that's a symbol of hope for services. If this really does go back to ultimately talent and becoming the best partner to your clients, isn't that the big opportunity that's opening up? It's those services firms that can win the talent race in terms of creating that next wave of smart young and mid-career talent that are going to win.
Absolutely. I've always believed, Phil, and I continue to believe that one of the most perhaps even underappreciated aspects of the services industry is the fact that because any individual company has clients across a range of industries, technologies, and functional areas, that diversity of work attracts the best and the brightest people to come work in the industry. People want to have breadth of experiences, to experience different technologies and industries. Structurally, I believe the industry is advantaged in that it can create more interesting career experiences for consultants. I believe that we're going through a moment right now where everything is changing, technology is new, AI expertise is scarce, but this is a moment when the industry can shine by attracting the best and the brightest to come and do their best work for the great clients that the industry has.
Right. So moving forward, you talk about the J curve danger. This resonated with me a bit at our summit where you were keen enough to talk about this. What are the earliest signals where a firm is maybe on the wrong side of this, and which firms today look closest to that cliff?
You know, Phil, when I talk about the J curve, what I mean is that there's a gap. For the existing work that any firm is doing, if you're really deploying AI and using the tools to their fullest potential, you're likely going to see a compression. For a given amount of work, you'll be able to do it with fewer humans because AI can fill that gap. If your pricing model is based on an input price, which is the number of billable hours, then you're likely going to see some compression in revenue. You might have this J curve of revenue, where you find some compression before you start to work your way out of it. Most firms that have been in the industry for a while face some degree of J curve. If you're not facing that J curve, it's probably a sign that you're not deploying the latest AI technology in the most effective way. If your revenue per employee or profit per employee is flat or declining, it's a pretty good sign that you're on the wrong side of the J curve. If it's starting to flatten out or increase, then it's probably a sign that you're through the J curve and on the other side of it.
Right. And if you're running a business in this industry today, we're seeing several leading services firms struggling with their stock, for example, and Wall Street and other investors are looking negatively at people-heavy businesses. Is that going to get worse, that attitude, or do you think we're just in this J curve where the big frontier companies are coming to a vast realization that they need talent and services if they're going to get enterprise adoption? Do you think we're just in a dip before this starts to come through the other side?
Yeah. I believe, Phil, that if you step back, there is Jevons paradox, this idea that as the cost of something comes down, the demand for that thing goes up. I think that over time, that is true in software. The world is clearly becoming more software and technology intensive, not less. The need for software is going to be substantially greater than it is today. The challenge right now is that in many of the public companies, we are still using scarcity-era metrics when we're talking to investors, and it has not been made clear how to dimension the J curve. If we were clear with investors that we are in this moment of transition, which everybody intuitively understands, but that there is a path through it, and we were able to dimension that path, we could explain to investors that you have to accept that there is a productivity gain from AI. That causes a short-term compression on the existing revenue base, but in theory, if done right, should improve margins. Once we get through that, we come out the other side. That's a message and an explanation that investors are capable of understanding and would welcome.
Right. But it might actually take seeing some examples of leading firms really starting to move in the right direction. Anyone who's in that Anthropic ecosystem right now seems to be growing exponentially. The revenues of the big AI tech firms on the whole are exciting investors. America has taken a giant bet on AI right now. Is there some better alignment needed between services also taking that giant bet and saying, 'Hey look, we get it too. We are really going down a path where we're going to meet that demand'? Maybe they're just not doing a good enough job convincing investors that they're on the right track.
Yeah. It has always been the case that great technology innovation leads to a great tailwind for the services industry. That continues to be the case here. The frontier labs that continue to innovate and produce ever better models, ever better vertical slices, ever better functional versions of those models, every time there's that level of innovation, it creates an opportunity for services firms to focus on what I call the first mile and the last mile. To take that technology and make it real, make it do something important, and do that in a safe, ethical, compliant way requires a set of services around the edges. The courage that the services firms need to have right now is to say, 'Some of the things that we did in the past, AI is better at doing. AI is generally better at writing code, writing test cases, and those kinds of things than humans. That is progress.' The services firms need to stand up and say, 'These are the parts of my business where productivity is going to have a dramatic effect, but these are the other opportunities that are emerging where we think we can grow.' On balance, that's going to be a net positive for the industry.
Right. So how do you view the recent announcements that OpenAI and Anthropic made where they're generating billions of dollars of consortium to partner with various entities in the market, and you see big names like McKinsey, Capgemini, and a few of these firms really trying to get in early? When I first saw this, my gut feel was this could be really bad for the traditional services industry. But the more I look at it now, the more I think this creates a big opportunity to partner with these companies. This may be their way of building out that capability to say, 'We want to work with you to help you train the talent of the future who can implement these models into the enterprise.' Do you view this as a big threat, or do you also view this as potentially a big solution to a lot of the problems we've been talking about?
I view it as a tremendous opportunity, Phil. I'm very much in the latter camp. In the first days of generative AI, there was this great fear that LLMs were going to do all the things that humans do, and there would be no need for services firms. The fact that these large language model frontier lab companies are actually partnering to create their own services business is first and foremost an acknowledgement that the technology still needs humans in order to make the technology work and do something productive for the client. These services businesses and deploy codes to me are a great acknowledgement that the future belongs to humans and agents together deploying solutions for a client, not one or the other. That model is now clear, and the investments that you've seen make that model clear, which then makes it an equal opportunity for the services firms to partner with the frontier labs to create that same set of services.
