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The Main Scoop, Episode 20: Riding the Waves of Continuous Innovation

The Main Scoop, Episode 20: Riding the Waves of Continuous Innovation

Join us as we examine the ongoing journey of innovation, through an insightful look at some iconic products and services, their impressive origins, and today’s rapid advancements. In this episode of The Main Scoop™ co-hosts Daniel Newman and Greg Lotko, along with special guest Paulo Carvão, discuss the evolution of modern technologies, keeping pace with customer needs, and the importance of critical thinking to guide the ethical use of data.

It was a great conversation and one you don’t want to miss. Like what you’ve heard? Check out all our past episodes here, and be sure to subscribe so you never miss an episode of The Main Scoop™ series.

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Transcript:

Daniel Newman: Hey everyone. Welcome back to another episode of The Main Scoop. I am one of the co-hosts, Daniel Newman, joined by my always esteemed co-host, Greg Lotko. We’re going to talk today about innovation. Over the last 14 months, we’ve seen a disruptive force in generative AI that has created this wave of innovation that seems like almost every day, every week we’re hearing about another company, another new development, more product, more services. And it’s changed business in a short period of time. But over history, innovation has had various different lengths in time in which products evolve.

Greg, you heard me. I mean, look, you knew I’d get to AI first and fast because is there anything else? But in all serious, I mean, you’ve been in an industry and you’ve been focused on helping companies drive incredible innovation using technologies that are brand new. And of course, technologies that have stood the test of time.

Greg Lotko: Yeah, and I think that’s the part that’s really misunderstood. People think that a technology that originated a number of years ago, or many years ago, how can that possibly be modern? But if you think about what’s gone on, and you talked about innovation, and we think about innovation that matters. Or innovation or technology that endures, it’s those things that don’t remain static throughout their life. And I know we’re both car guys, and I want to make sure this relates to a product that everybody can think about, so let’s just think about something that’s been around for near 60 years now. Actually 60 years, it’ll have an anniversary this year, the Mustang,

Daniel Newman: I thought you were going to say you.

Greg Lotko: No, not quite 60 yet, but thank you. So 60 years. The Mustang launched in 1964. It was actually launched not too far from here, at the New York World’s Fair in 1964 as a ’65 model. So everybody thinks, oh my God, a Mustang, that’s something that’s 60 years old. Why has that vehicle captured people’s attention and continued to be relevant through all these decades? It’s because it preserved the core and the essence of what made it valuable as a car. So you think about it, somebody who could drive a 1965 Mustang could hop into a current 2024 Mustang and be able to drive it.

You have the same interface; you have the steering wheel in front of you, you press the gas pedal to make it go faster, you’ve got the brake. jAnd then you think about what’s happened in automotive technology. There’s antilock brakes, there’s stability control, there’s traction control. Nobody is unfolding a map in their car anymore, we have GPS devices either integrated in the car or we’re tying our phone to the car and being able to navigate. So technologies that provide real, lasting, enduring value, or serve a really good purpose, that’s one part of their longevity. But continuous and ongoing innovation, that’s the real secret sauce.

Daniel Newman: And Greg, it’s really important, what you pointed out were innovations that happened over a period of time. A lot of times people are looking for these Hallmark moments of new model to new model. A massive redesign. Innovation can be iterative too, though. It can be even year to year.

Greg Lotko: Or ongoing.

Daniel Newman: Or ongoing. And of course, as we’ve entered, I mean you’ve set me up well for this, but the software defined vehicle. I mean, the whole idea now is that you can have a vehicle literally remap itself completely.

Greg Lotko: Change paint color.

Daniel Newman: Day to day. It can create new levels of fuel efficiencies. You’ve got augmented paint experiences coming in, or interior lighting that can be done on the fly, different infotainment and entertainment experiences. So you and I, this show will always have a car theme a little bit, because something we’re passionate about. But I think there’s such an alignment.

Greg Lotko: And we’ve got a great guest that we should pull in, absolutely. So I am honored today to have Paulo Carvao with us. I’ve known Paulo for more than 20 years now, and I met him more than 20 years ago when he was a software seller focusing heavily on mainframe, but selling the broad portfolio. But he didn’t stop there, his career continued to expand. He was the general manager and head of sales for all of systems across all of IBM. And he’s now moved into academia. And check out his blog, he’s talking about technology and how it relates to humanity and politics. But let’s pull Paulo in and hear what he has to say and share with us about continuous innovation.

Daniel Newman: Paulo, it’s so great to have you here. I find it fascinating. The work you did at IBM, and you just grew and grew and grew, and now you’ve grown into this really exciting role. You’re at Harvard. I’d love for you just to share a little bit about the journey beyond your IBM years and what you’re doing as a Harvard fellow.

Paulo Carvao: Hey, Dan and Greg, super excited to be here. Thank you for inviting me. I’ve been at Harvard, starting my second year there as a fellow. And when I started thinking about doing that, I had two things in mind. One was this intersection between what I call technology and democracy, which is everything that is going on with social media, artificial intelligence, and the impact on polarization, radicalization. And potentially the erosion of some of the democratic institutions today.

And given that I had dedicated all of my professional life for technology, I was thinking about what can I do to have an effect there? And the other one, as Greg knows well, I am a Brazilian American. I’ve grown up in Brazil, started my professional life there, but lived half of my life here, half of my life there. And I wanted to give back to Brazil a little bit. And I started studying social mobility and also entrepreneurship as a vehicle for social mobility. And so I’ve been kind of a focusing on these two areas, tech and democracy and entrepreneurship and social mobility.

Greg Lotko: You heard what we opened up with and we were talking about technology and ongoing innovation and innovation that matters. What are your thoughts around the topic?

Paulo Carvao: Well, first, some things never change. We had to start this with a car talk, so I’m glad that we’re back to that. And innovation, I think, is at the core of what moves the economy, but also moves some of the most important products that ever existed. And I think the product that you and I have been affiliated with, and I love, which is mainframe, has been at the heart of it. So when I think about mainframes, the first word that comes to mind, almost paradoxically, given the image that people have of it, is innovation. And I bring it back to when it was born, which was before I was born.

Greg Lotko: Same time as the Mustang, though.

Paulo Carvao: Yeah, here we go. Exact same year. Which, even the whole proposal at that moment was completely revolutionary. I remember studying the topic and the promise would be that, never again you have to rewrite code. Which, today, we know that we don’t do this, but back then you had to code to the hardware. And if you had an upgrade, if you had to move to a different product, if you had to change anything, you have to reprogram. So from that core innovation of … By the way, it created the bespoke or legacy industry, one can say. From that to, how you could mix and match peripherals. How you could upgrade within a family. All of those concepts were completely revolutionary.

Greg Lotko: And I don’t think a lot of people today maybe who have started their career in the last 20 years realize that. Right? The idea that, think about if you were getting a new cell phone or if you were getting a new laptop, that you’d go, “Oh, I have to rewrite Excel or my spreadsheet.” You had to rewrite all your programs for the particular hardware.

Paulo Carvao: Yeah. It would be a nightmare, but not only that, imagine the economic value that would be put to waste. All of the business knowledge that is embedded in those applications that you had to redo, and rewrite, et cetera. But that’s history. I think what’s been amazing, it’s similar to the conversation you guys were having about the new Mustang. Is how it has been on top of each one of the successive waves.

So if we go back, fast-forward 30 years from when it was launched to the late 90s and early aughts, it was a time of eBusiness and web enabling the world. And there was this debate on, well, if we launch WebSphere on the mainframe, what’s going to happen to CICS? And what happened is, transactions on CICS exploded because you basically were having everybody coming and exercising the core data that wasn’t the mainframe.

Greg Lotko: And that was the other part, right? So it wasn’t just the innovation around the capability or the innovation on other platforms, it was that connectivity innovation. it was really the advent of where we went with open APIs and different technologies, computers, software, et cetera, talking to each other. And you’re right, it caused an explosion.

Paulo Carvao: And here you go. So after web enabling the world, then we got into another wave of the initial inroads into artificial intelligence and machine learning. And if you wanted to do that related to business, the natural movement would be, how do you do this together with your core data? So constantly riding each one of these successive waves, and I think that’s what’s maintained it as a current viable product and, frankly, a bestseller also.

Daniel Newman: So the customer driven aspect varies from technology to technology. There are certain technology CEOs and legends that came to bear by saying, “The customer doesn’t actually know what they want.” The Apple-esque. How much did you see this innovation be driven by the customer saying it has to be?

Paulo Carvao: I would say it was customer driven, client driven innovation. And I think one of the things that have differentiated this world that we lived in for so many years was, remember the number of user group meetings? Pre-launch design sessions, user-centered design, it was always, always driven by clients. Clients prioritizing investment decisions, driving R & D, having ideas together with us. So I think this is the other very unique characteristic of the product, it was very, very user-centric and has a very strong community. Very passionate about the product and very vocal about what they want and therefore what has to be.

Greg Lotko: There were also, you talk about the Apple type of thing, of the customer doesn’t know what they want and let’s do this. It happened in the mainframe space, but it happened differently. So Paulo is absolutely correct that there were all these user sessions across hardware and software and other partners in the ecosystem. There were things that customers said, “I need this on the screen,” or, “I need this functionality.” Clearly there were. But there were other times where customers would talk about the need, but they didn’t know what they wanted the technology to do. So they said, “Hey, I need more resiliency. I need more stability.” And Parallel Sysplex and all that stuff got invented. No customer was saying, “Hey, invent Parallel Sysplex and here’s how you do it.” But then the relationship that has been in this ecosystem, we all were watching what was going on and participating actively in it.

Daniel Newman: And I think there’s a certain amount of … There’s the great quote about Gretzky, he skates to where the puck is going. And I think there’s a little bit of that in innovation.

Greg Lotko: Absolutely.

Daniel Newman: That, companies understand the customer need. The customer doesn’t always understand how to get there. And I think you both study digital transformation a little bit. I’ve written several books about it, spent a lot of time doing research about it, and what we consistently found was that the companies wanted to do it, but oftentimes with transformation, they would literally try to just digitalize an analog. An old process. And what I’m saying is, so the customer kind of knew-

Greg Lotko: They focused on the technology versus the outcome that they need

Daniel Newman: Exactly. They’re like, “Oh, we do this and we’re going to just turn everything into a digital version and do it the same way.” Instead of thinking, how could we completely do this differently? So where we’ve landed though is that, 60 years later, the mainframe still runs all these industries; financial services, government, airlines, healthcare. So it would be laughable for someone to say it doesn’t have staying power and that it hasn’t been innovative. Why do you believe that these industries will continue to be run by mainframes?

Paulo Carvao: So I think there’s this third aspect that we’re discussing is economy and economics.

So on one hand, it’s running the economy. I think until today, probably 45 out of the top 50 banks, most of the largest retailers, most of the credit card transactions, at some point in time, even if you’re pumping gas in the gas station, the transaction is being cleared on a mainframe somewhere. So it is kind of running the economy.

But at the same time, it has a set of viable economics, because money talks and eventually if … not only you didn’t have the technology that would integrate to modern hybrid cloud and an API economy. And we can talk about AI, generative AI, et cetera, et cetera.

But if you didn’t have a set of economics that would be favorable, then the system would expel it naturally. So I think that’s the other well-kept secret about mainframes, is this related to economics. Because on the surface, they are big ticket items, but the cost per transaction is still the best in the industry, and that’s what keeps it there. So it’s this combination of core, transactional processing is the best cost that exists. And if you continue to innovate and integrate this to all of the other modern technologies that surround it, I think this has been the recipe for staying power.

Greg Lotko: What was the presidential quote? Walk softly but carry a big stick? So the reality is, that’s what the mainframe’s been doing. Not everybody understands how pervasive it is. Not everybody understands how economically efficient it is, and resilient and everything, but it is quietly going about carrying a big stick. Doing a lot of the heavy lifting in the world and doing it without disruption.

Daniel Newman: But Greg, there is a underlying theme here, and it’s that the mainframe of today is very different than the 1964 mainframe and all-

Greg Lotko: It’s evolved. It’s evolved. So just as we are not neanderthal man, we’ve evolved. We are still human, but our level of intelligence, our understanding, our ability to learn and adapt has expanded vastly. So this is actually one of the things I love inherently about the mainframe. You could take a program that was written in 1965 and still run it on today’s mainframe. But what today’s mainframe is capable of is way beyond what anybody imagined.

Paulo Carvao: I would even bring you car guys back to the beginning of the conversation, which is, the current Mustang is not a 1964 Mustang. So maybe the essence of that brand is there, and that promise is still there, but the technology that is running today’s car is radically different.

Greg Lotko: There’s actually no part in common. It’s even a different horsey logo.

Daniel Newman: And that’s probably the only one that could have ever potentially survived this long in any car, whether it was a Corvette or a vintage Ferrari. They’ve all completely turned over their parts. And I sort of led in with the AI and the innovation and the silicon, but you look at, it’s really mainframe plus. I mean, we’ve entered an era, as I see it as an analyst, it’s mainframe plus. Meaning-

Greg Lotko: No technology sits on an island in isolation.

Daniel Newman: There’s mainframe plus AI, there’s mainframe plus very strategic cloud, there’s mainframe plus security and mobile. And so what I’m saying though is, it has adapted and adopted every major technological trend to be able to be supported by the mainframe. But it’s had the staying power of a brand, like a Corvette, like a Mustang, because the economics. Because the robustness, the inherent value. That’s powerful.

Daniel Newman: Well, you know there’s a topic, I can’t make it through a show without bringing up. So in generative AI. I’ve made some references already throughout the show. Paulo, I’d love to get your take on generative AI at large, maybe whether it’s the innovation technology or some the ethical and responsibility challenges. How do you see it in your role today?

Paulo Carvao: Yeah. Well, it’s a couple of things. So if we think about large language models and how we’ve been training them, we’ve been training them on public data. So everything that is on the internet. Now, a lot of the data, some say that most of the data actually is behind firewalls and-

Greg Lotko: Most of the valid data.

Paulo Carvao: Yep. And the data that has tremendous economic value. And if you think about using this in the context of business processes, I think that’s the next generation. And even if you think about startups, there is an opportunity for startups to start thinking about that in the context of business processes. And that would require access for … Or two, smaller data sets. New technologies that would provide the same level of training and capabilities on smaller data sets. And as you get into usage of more confidential data, private data like healthcare data, et cetera, ethical questions are even more important.

And along those lines, I think the age of moving fast and break things, Facebook, apologize to you guys, but that age is over. And I think there is much more conscience within society and the industry in general, that ethical use is important. And there is a role for including the mainframe community where a lot of this data is. And the mainframe community that has the wisdom of experience to now balance, and with that, bring their perspective to ethical use of data.

Greg Lotko: And I think there’s two lines, two paths of thought along that ethical use of data that cause challenges. So you talked about most of the really valuable data being behind a firewall versus being out in the public domain. So you get into one aspect that says, hey, I have access to this data. I know this stuff about people. Whether it be personal information or a condition or whatever. Whether or not I should use it, whether or not I could use it if I anonymize it, and how I then use it. Then there’s the other aspect that is more to the validity and whether or not it’s ethical to use it. So if you’re using data that’s in the public domain, or if you’re using opinions versus facts, is it ethical to not really vet your source and know the veracity, the validity of that data? And those are two really serious dimensions of the ethics of what you’re making decisions off of with your data.

Paulo Carvao: Which is also in the frontier of technology development today. In order for you to even test the validity of the data, you need to trace back to the data. And so this whole discussion about attribution, that would make generative AI more usable, even in academic research. Or the whole discussion about copyright today and the lawsuits around this. We need to have not only transparency, but technology that would allow you to have the right attribution. And with that, you can either trace data back for validity, but also you can generate or almost unleash the next economic cycle through monetizing that data.

Daniel Newman: Yeah, it’s absolutely going to … The focus on grounding. Paulo, one last question. I would love to get your vision and trends, outlooks, any big predictions, not just for the mainframe, not just for generative AI, but of just any technological trends or shifts that you’re paying attention to over the next couple of years.

Paulo Carvao: I think the trend that puzzles me the most, it’s not even only a technological one, but I think society at large will have to become much bi-literate, duo-literate. Not only technology, but a lot of liberal arts associated to that. Starting with the critical thinking and how we’re educating the new generations to have the discernment, the critical thinking to be able to deal with all of this technology that are coming at us at an unprecedented pace.

Greg Lotko: And I think that’s a huge challenge. I agree with you, I worry about it the most. Think about the generations that are growing up now that may drive a car but have no idea how to get across town, because they enter the address into the GPS and they just accept the answer as fact. Or they go into Google or a search engine and they say, “Who’s the smartest person in the world?” And whatever comes back, they accept as fact. So I like that, bi-literate. So it’s the reasoning and the introspection versus the just search for the answer.

Daniel Newman: Are you worried about the end of critical thinking?

Paulo Carvao: I am. I am. And that’s why I think that’s one of the most important things that we need to develop in current and future generations. Because without that, then we’re in trouble.

Daniel Newman: So in short, technology in the humanities; sociology, psychology, anthropology, will come in vogue as we try to shift to an era of not only technological advancement and constant innovation, but a society full of humans that are contributing meaningfully. And that maintain a bit of objectivity and a desire to think critically.

Greg Lotko: They need to be. And we need to raise that awareness and have discussions like this to get the right focus.

Daniel Newman: It’s a great conversation. Paulo, I appreciate the answer.

Paulo Carvao: Thank you.

Daniel Newman: Thanks, everybody, for joining us for this episode of The Main Scoop. Hope you will stay with us. Hit that subscribe button, come back often. But for now, for myself, for Greg Lotko, it’s time to say goodbye. See y’all later.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.

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