Matt Ellis - Digital transformation lessons we can learn from the 1972 Beetle
Matt Ellis is Senior Manager of the CIO Advisory Practice at BearingPoint, an independent multinational management and technology consulting firm.
In this episode, we talk about the 1972 Volkswagen Beetle and what modern-day digital transformation lessons we can learn from it, focusing on exponential growth and the costs of remaining on outdated legacy technology.
Links & mentions:
"There's lots of taxes, complexity taxes associated with older technology, but really what it comes down to is that the underlying system becomes more rigid and that you start to lose the opportunities, right? So it's more of an opportunity cost than anything else."
Welcome to the Agile Digital Transformation Podcast, where we explore different aspects of digital transformation and digital experience with your host, Tim Butara, content and Community Manager at Agiledrop.
Tim Butara: Hello everyone. Thanks for tuning in. I'm joined today by Matt Ellis, Senior Manager of BearingPoint's CIO Advisory Practice. We have a fantastic topic for you today, which I'm sure will resonate with a lot of you listening right now. Namely, we'll be talking about Volkswagen's Beetle from 1972 and what modern day digital transformation lessons we can learn from it, which I know might sound a little bit counterintuitive to some listeners, but just hear us out because we're sure that you won't think so anymore by the end of this episode.
Matt, welcome to the show. I'm really excited to have you here to discuss this with you today. And of course, we need to start with a bit of background, right? And I want to ask you, why are we talking about the 1972 Beetle in particular?
Matt Ellis: Yeah, absolutely. And I'm glad to be here. So I was looking, I was talking to a lot of my clients and they were having a hard time understanding the the impacts or the technology curve, kind of the growth and opportunities that have come up over the over a period of time.
And so I was looking for a way to use as an anecdote or a metaphor what something they could relate to. And there's not, if you look at it and technology has grown over an exponential curve over the past 50 years, and for the most part, most humans aren't exposed to anything that have an exponential growth rate, right?
So even people, engineers, scientists who are doing things in that space, they even have a hard time understanding or predicting exponential growth. And so what I was looking for was something that was iconic that someone, everyone could relate to, and came up with the 1972 Beetle. 1972 in particular, because that was the first year that Intel released their microprocessor at a wide scale. Right?
So everyone can imagine what that Beetle looks like. If I said 1972 Plymouth. Everyone would have a hard time imagining it, right? So, if we take that and apply it, most people are used to a linear growth, something that grows consistently over time. But starting in 1972, the Intel's chip, Moore's Law came about, and that was the concept that the number of transistors on a chip doubles every two years.
Now, again, that's the beginning of exponential growth. Again, people have a really hard time understanding what that means. And so if you, I turn on and applied that same law to the 1972 Beetle. And so if you were to say 1972 Beetle, that was 51 years ago. And if at the time the max speed was, it was like 80, 82 miles an hour, miles per hour was the top speed. And if you apply the exponential growth to it, Moore's law to it, that 1972 beetle would now go 164, don't even know the number, how to describe it, there are 15 zeros after it, miles per hour.
Similarly, if you do the miles per gallon at the time, it was roughly 22 miles per gallon. And now it would get something like 64 and 15 zeros after it miles per gallon. Right. And so that's just mind boggling. And obviously no one is no longer running that 1972 microprocessor, but there are a lot of companies who still have technology that's 15, 20 years old that was installed in the late 1990s, early 2000s.
And so all of a sudden it kind of clicks for him like, oh, wow, there are exponential growth changes and that has lots of ramifications. And we can talk about a little bit more, but now change management. How do you bring your users along? What are the new capabilities and what are your strategies to support it?
Tim Butara: Well, let's talk more about those, why not?
Matt Ellis: Sure. So I think let's go for the strategies piece. So when we talk about digital strategy and the new capabilities, there's, we talked to a lot of clients about how to keep up with the Joneses. I want everything. I want to implement everything. I want to, I want all the cool tech, and that's just not possible.
And so I think when we start talking about exponential growth, we got to talk about really, really specific about where you want to invest and what's going to differentiate you going forward, because there's no company out there that can afford to keep up with that, the exponential growth of new technology, constantly implementing new capabilities, let alone the organizations and there's every organization has its maximum amount of change that it can absorb over a given period of time. And so you have to be really specific about which capabilities, which technologies you're implementing and rolling out to your teams.
Tim Butara: So, it's really crucial that, you know, companies as well as society, on the other hand, kind of identify this potential of exponential growth, even if they aren't able to keep up with it in in every single case possible?
Matt Ellis: Right, I think you need to work as an IT or CIO leader. You need to work very closely with your business to understand what the business opportunities are and not necessarily just the IT opportunities. It starts to, IT starts to become the business or business becomes IT, and you need to make sure that it's seamless because if it is going in the wrong direction at an exponential rate, all of a sudden you can be on completely different pages in developing capabilities that have that are not aligned to your business needs.
Tim Butara: That was a very, very good point. And, like, one of the problems here that you also kind of pointed at is this adoption of tech for the sake of adopting tech without any real business value attached to it. And that just seems like a pitfall of all of this.
Matt Ellis: Absolutely. If there's not a a justifiable change, change for the sake of changes is noise and distraction.
Tim Butara: So, yeah, to kind of retrace back to 1972, it really seems like that was a kind of milestone year for digital transformation, right? We had, it was, it seems like that was the first time when we could start conceptualizing this concept of exponential growth or something.
Matt Ellis: Absolutely. And prior to 1972 and even after 1972 and other technology domains, it's linear growth, right? And so you could do the rate of adoption for typewriters to word processors. Like, there wasn't a whole lot of big difference. Or improvements in vehicles, right? And physical manufacturing, again, not a whole lot of difference. It's still a linear growth, but now when you introduce the technology, 1972, that's when the capabilities just become astronomical and continue to grow.
Tim Butara: And so that's why there's another really huge reason why it's so important to talk about this today, right? Because, I just watched the AI Dilemma a few days ago and they pointed out that, you know, one of the biggest, both potentials, as well as risks on the other hand of all this AI innovation is the rising in the exponential growth and development of these technologies. So it somehow seems to me like if we didn't have this concept around for now over 50 years, we would have an even harder time imagining the true impact of all this AI innovation and how it might develop in the future.
Matt Ellis: Absolutely. I love that show. I think i've watched it three maybe four times. It leaves goosebumps on the back of my neck every time I watch it.
Tim Butara: Yeah, it's good that you mentioned that you watched it a few times because they do point out, Aza and Tristan point out at the end that you're going to have one of these moments as soon as you stop watching it, and then you see a cool AI tool on Twitter, you're going to be like, oh yeah, you know, maybe the risks aren't as great as they pointed out, so you know, the more you watch it, the more you actually keep this holistic perspective of the whole thing and not get swept up in either of the two directions, either, you know, those being maybe too afraid of AI development on the one hand, or those too eager to just keep innovating in that sphere without any regard for the risks that this innovation might pose.
Matt Ellis: Right. I mean, you're absolutely right. So the, you know, I initially spoke in the context of great capabilities, but with that becomes also great risks that you need to learn how to manage as well. And there's a lot to be discovered and developed in that space. But I think, you know, at least in the terms of risks, or development of an effective development and implementation of technology. I think it's that alignment between the IT and business, but in the broader context of society, how do we we implement safeguards around technology that may escape our control. I think that's something that's yet to be discovered and figured out yet.
But I think so in the context of AI Dilemma, in the past 48 hours, ChatGPT has recently announced that they are implementing or have implemented the ability to do voice. It's no longer just, it's just no longer text. And then if you dig into it, there's actually now rumors out there that some of the code to enable that voice was written by ChatGPT itself. Still had a developer behind it, right? The developer was still in the driver's seat, but they were using ChatGPT on the side to help code some of the methods and functions to support it. And that's another one of those scary moments.
Tim Butara: But I love that you used the term that the developer was still in the driver's seat because we are talking about the 1972 Beetle originally, so we're staying true to that car metaphor.
Matt Ellis: Yeah, exactly. Yeah. But the question becomes what happens when there's no longer a driver's seat.
Tim Butara: Oh man, I think that can be a topic for a further discussion, but now I want to dedicate a few minutes to talking about, like, you mentioned that a lot of technology that was developed in like the late 90s and put in place then is still being used, even though by this point there's been a lot of new tech coming out and that that might cause additional new considerations, new challenges, new risks. So what are the costs to businesses of using outdated or legacy technology?
Matt Ellis: So I think as a, call it a developer society, that whole ecosystem of software developers and infrastructure teams, there's constant development going on and there's new technologies and everyone always wants to develop on the newest platform. So the risk of staying older technology is you are no longer tapping into the most brightest minds and the most recent ideas, but the second piece of it is that we've started to use this term called complexity taxes, and it's that, you know, the concept of technical debt, things become a little bit older.
Customizations within your ecosystem, all these things make your system more rigid. And as a result, there are both tangible and intangible costs associated with it. More development time to do tests. And if you have redundant connections, you have to retest the code on a more regular basis. If you're using really old technology, there's lots of security updates, right?
So there's lots of taxes, complexity taxes associated with older technology. But really what it comes down to is that the system becomes more rigid and that you start to lose the opportunities. Right? So it's more of an opportunity cost than anything else. I think that's one of the hardest conversations I have with my clients because they always want a business case. And more and more the business case is about missed opportunity, right?
And so, and it's no longer about, well, can I save on compute power or storage, right? Or even some manpower. You have to change the dialogue to more about what the future could hold and what the opportunities are and how to make sure that they're well positioned for the future.
Tim Butara: So one of the biggest downfalls or pitfalls of over reliance on legacy tech is the inability to be future ready or to be future oriented and to think more long term.
Matt Ellis: Absolutely.
Tim Butara: Okay. So how can today's businesses turn that around? So, how can they maybe challenge these traditional assumptions and what can they do to remain competitive and thrive in this super competitive environment marked by exponential growth as we just alluded to multiple times?
Matt Ellis: Yeah. So that's a really good question because the easy answer would be, well, everyone needs to have a strategy and know where they need to invest. No one has a strategy and no one knows where they need to invest. They don't know what their competitors are doing and they don't know what tomorrow holds. So exactly what you mentioned earlier, how do you become future ready?
And if you look at, consider like layers of technology. There's core foundational pieces of technology and of your infrastructure, of your internal capabilities. Master data management, as an example, that is a core capability here. Then after that, your core transactional processes within a company, right? Only on top of that, you start getting additional capabilities around AI, analytics, big data.
And so what we've been trying to work with our clients to do is tell them that those lower levels, that's not a place to innovate. You don't go innovate on your master data. You don't come up with new processes transactions that have never existed before. Businesses have been around a long time and we know how to do basic business processes.
You don't, a PO is a PO, you pay an invoice the same way. It doesn't matter what company you are, you're not special. And so we really focus on making sure that our clients are future ready by saying, let's standardize that core, those lower levels, let's keep that clean. Because what that does is it allows you to innovate on the edges.
Let's innovate on the AI, let's innovate on the big data portion. Come up with great new business cases for data. How do we transform the overall business model? And then that way you can, I don't want to say it's plug and play, but it's much easier to start swapping out, changing up, updating that core if it's clean, because every time you customize something, you then have to percolate that customization through every single layer before. So, yeah, we try to get that clean core, it provides the agility going forward. You're able to adapt and move to the innovation on the outside, not within within it.
Tim Butara: And the cleaner it is, the more long term stability it will also have.
Matt Ellis: Absolutely, for so many reasons. I mean, we're moving into a cloud environment more and more. Or at least companies are moving into a cloud environment more. And so, by moving into the cloud, you get the benefits of of the security of Microsoft or Azure AWS or... as well as the constant updates. And so absolutely, there's a certain level of stability that you can apply those updates quickly, adopt new capabilities quickly if there are something very, very specific.
A great example of... in general, I'm tired of COVID examples, but COVID was a great example. For those people who were in the cloud during COVID for their companies, the leading HR platforms from SAP and Oracle, immediately after COVID hit, they were able to innovate quickly and roll out updates to the cloud to be able to track vaccination status of their employees.
It was a capability they rolled out overnight. Anyone who was more focused on doing things on prem or who weren't up to date or had customized their core and had prevented that or broken the upgrade path, they weren't able to accept that update. Again, the idea of innovation and that stability, it provides stability to the business. You can do the updates, whether or not it be a new capability or security issue.
Tim Butara: Well, and this example also shows that it's not just about your own innovation, but you won't be able to tap into the innovation done by others if you mess with your core systems because they won't be compatible.
Matt Ellis: Absolutely. I mean, I know I can't keep coming back to like the Oracles and the SAPs, but those are huge companies that have huge R&D budgets. And the number of developers are way higher than any of my clients. I think, SAP right now is a 160 billion company. The amount of talent dedicated to just pure innovation is far exceeds the innovation budget that any of my clients have ever seen.
Tim Butara: Well, but you also, I think another theme of this episode has also been that just like adopting tech for the sake of adopting tech can backfire, so can innovating for the sake of innovating backfire if this innovation is not properly directed at your business goals that you've determined through your long term approach that you've developed through everything that we've hopefully showcased clearly throughout this conversation.
Matt Ellis: Exactly.
Tim Butara: Well, and I want to finish up, Matt, with kind of maybe a more fun question. And returning back to 1972 and Volkswagen's Beetle, I want to ask you, how do you think people then, for whom that was a revolutionary car, would react if a time traveler traveled to 1972 and told them about autonomous or self driving electric cars that we now have in the 21st century?
Matt Ellis: That's a, I can't help but laugh because you're asking the question with hindsight, with the benefit of hindsight. Oh my gosh, people 50 years ago, they would never believe that we had you know, Teslas that could drive down the highway by themselves right now. And they wouldn't believe it, because again, their, mindset is they've never been exposed to exponential growth. It's always been linear. They just, they can't grasp it. But if I was to tell you right now in 50 years, we'd all be driving flying cars. What would you say?
Tim Butara: Yeah, I mean, I would probably be like, I don't think it's going to take 50 years.
Matt Ellis: Well, that's because you benefited from watching the AI Dilemma the other day. So, but I think the average person would look at me and say, you're crazy, right? But again, it's the power of that exponential growth curve on technology. We just, and I think that's going to be applied to more and more going forward. As technology becomes more embedded in everything we do from, from business to, to medicine, to manufacturing, we'll start to see that exponential growth occur, capability growth occur in lots of different industries and products.
Tim Butara: You know what also occurred to me now with this example, and I know it may not be that related, but I think it's super interesting in this context that I think it was in 1977 that the first Star Wars movie was released and that kind of opened up the sci-fi genre in cinema. And with that came a lot of new conceptualizations that were previously not just not possible, but never even thought of, right? Before, I mean, since we're talking about 1972, it seems much more likely to me that if you talk to somebody from 1972, they would have a harder time imagining self driving vehicles than someone in 1978, or 1980 after already having watched some sci-fi movies and after already having been having been told that, yeah, you know, this is what the world will look like in the 21st century from, you know, maybe Blade Runner or something like that.
Matt Ellis: You know, so that's, you're right, we're, you take a car and you say, well, maybe the next natural evolution of it is a more efficient car, faster car, and then after that, it's a self driving car and maybe taking the natural step again is a flying car, but what the Star Wars movies did was that it provided, it gave people an idea.
Because so many people... even their, like our imagination is so linear. So when you come up with ideas, what would those look like? So, I mean, Star Wars, you had the communicator and that's the cell phone, right? So I think you're right. It's not only understanding the exponential curve of growth, but also being able to imagine the heart of the possibility on the other side of it really helps ground people.
Tim Butara: That was very, very, very well put, and I think it was the perfect note to end this great conversation on, Matt. Just before we do, before we jump off the call, if people listening right now would like to connect with you or learn more about you, how can they do that?
Matt Ellis: Yeah. So my company's website is, is bearingpoint.com. We do a lot of this type of work where we help companies and clients really set the digital foundations that they can continue their growth on. Outside of that it's Matt Ellis on LinkedIn and I'm pretty responsive on there, happy to engage with any of your listeners.
Tim Butara: Awesome. Well, thanks again, Matt. I really, really enjoyed this conversation. I think it was super fun to talk about all of this and I believe that it's also super insightful and engaging for everybody listening. So thank you for being our guest today.
Matt Ellis: Absolutely. Really appreciate the opportunity.
Tim Butara: Well, and to our listeners. That's all for this episode. Have a great day everyone and stay safe.
Thanks for tuning in. If you'd like to check out our other episodes, you can find all of them at agiledrop.com/podcast, as well as on all the most popular podcasting platforms. Make sure to subscribe so you don't miss any new episodes and don't forget to share the podcast with your friends and colleagues.