Unlocking Growth: The Real Cost-and Opportunity-of Legacy Transformation

So Pega just conducted research, surveys, surveying executive leaders within large enterprises. And what we found probably won't shock you, but on average, enterprises are spending $370 million per year investing into legacy technology. So Ken, first off, thanks for joining me.

Glad to be here.

So as an executive who oversees IT, cloud, operations and finance, I thought you would be the perfect person to explore this research with me and really get to the heart of, within this $370 million, what are the key factors and how can enterprises really approach unlocking growth? So the first thing I wanna understand is we've all heard that AI, 95% of projects which are done by enterprises to adopt AI, aren't realizing any return on investment.

Yep.

So, I wanna know, is this stuff junk?

Well, I think it's an interesting point because I do agree with the data and the feedback I've heard from clients and from people in the industry that a lot of the AI projects are not being successful. But I think there's a different problem, because I think the problem is that enterprises are trying to use AI to solve the wrong problem, and I think they're not attacking the right opportunity areas. So I don't believe that it's an issue with technology or that AI won't be incredibly transformative for us to use in our operations. But I think we're trying to do, you know, we're trying to solve a magical problem with AI that it isn't really built to solve. So if you kind of go back to this concept of modernization, of legacy transformation, at modernization, there's lots of buzzwords that are being used in the industry, but really it's around taking a legacy footprint and trying to finally, and for real, get yourself to a modern state that can be sustained. When you think about it that way, AI is an incredible enabler when you get to that point, when you get off of this legacy technology into the future state. So I think clients are very committed to figure out how they can leverage AI. And so the transformation from older legacy applications into modern environments will help them really be able to get the real use cases that AI were designed to help with.

Yeah, I'm definitely seeing the same thing you are. Most AI projects I see out there are simple chatbot type use cases, maybe marginal benefits, but they're not transformational. And while there is that stat, which is probably the most overused stat in the industry right now, that 95% aren't delivering ROI, there's other research done by like McKinsey and others who do show that once you can cross the chasm and adopt AI as an enterprise, you do accelerate your growth when compared to competitors. So once you can get there, I think there's something there as well. So definitely, with regard to legacy debt, I think the first cost, as we're getting at, is really within innovation. But let's get to some others.

Okay. So there's of course the more apparent costs with regard to legacy debt, like operations, maintenance support, the things you think that could just fall under the IT remit. But what are some of the less apparent costs to the business at large?

Well, I think when you spend resources and focus to deliver an outcome at a company, in the land of enterprise organizations, there's a concept of scarcity, which is resources are not infinite. You only have a certain amount of budget, a certain amount of individuals, what they can focus on. And so if you take those resources and they're actually helping support, say, legacy applications that aren't driving value, that customer experience is not great, they can't integrate with AI, that are not built in an optimized way to leverage, for example, scaling, you end up taking resources from other opportunities, whether that could be to fuel growth, whether that could be to increase the profitability and the performance of the business, whether that could be used to acquire or partner with new technology and innovation and make you more relevant. So that's one kind of theme. Another area is around the customer experience. Now, the customer could be your end customer or it could be your employees. But the disconnect of not being able to manage that kind of experience and make them efficient, that's where AI can come in, not actually allowing real time personalization, some of the ways that we help our clients with being highly relevant around the timing of what you do and why you do it and when you do it. I think employee productivity becomes a really big factor. And some of it is, some of it is tied to how an employee does their job and the amount of time that they spend in systems and doing work that they otherwise shouldn't do by automating the workflow, for example. Some of it is also the distraction that it causes them in the morale drag that it has when employees and clients are working in environments that are less than optimum. So I think there's a series of cost drags. One is a kind of scarcity choice of investment options. Another one is the experience that might lead to higher turnover or bad experience for clients. Another one is just the lack of automation and the amount of inefficiency that that drives.

Yeah, yeah, absolutely. I mean, I think of, you know, even when I joined the workforce, about 10, 15 years ago now, like coming into older, disconnected applications, it just took me a long time to get up to speed.

Yeah.

And imagine coming into a contact center who has 15 applications that a customer service rep might have to deal with, some of them mainframe, some of them Lotus Notes all over the place. They're not gonna be proficient for 6, 12, 18 months. So definitely onboarding and productivity. And then, yeah, I think your point is interesting, like a lot of modernization approaches are sort of predicated on let's lift and shift, let's move these apps to the cloud. And what you're not doing when you're doing that is thinking about what are people doing today that we could probably just automate, get rid of? How can we consolidate, rationalize, and automate? So I think that's great. I think there's also an interesting vector or maybe dimension to the cost of legacy debt, which is risk.

Mm-hm.

Now I talk with a lot of IT leaders and one of the things that I hear often is, you know, the mainframe is actually kind of notoriously stable. There's not a lot of downtime, not a lot of latency.

No.

It's predictable, predictable from an operation standpoint. But I think you have an interesting perspective that maybe there are some more existential risks to the business with a legacy, so.

Well, yeah, so it's interesting. One of the biggest... I worked, when I was in college, I did a summer internship and worked at a large bank in Pittsburgh where I went to college. And it was, we were using systems and screens that were in today's world, you might look at and say, "Wow, that really seems like 1980s." But the reality is, if you walk in to many of those companies, they're the same screens, right? They look like, I remember the systems that I used, and when I see some of the Cobalt applications that people are running on the mainframe, and you look at them, they don't look all that different than what I experienced being able to do backslash and try to like toggle through.

You could hop back in.

Yeah, I could, right? I'm trained. But I think what... Human beings are used to patterns and they're comfortable with consistency. And what they fall into at times is let's not change anything. Let's just keep doing things the same way until there becomes a compelling reason to do that. Well, certainly AI is a compelling reason to leverage new technology. But what is often overlooked is the cost of not changing. And the cost of not changing is not just with employee productivity and morale and experience. It also starts to get into the area of risk. Systems that were built 20, 30, 40, some ways 50, 60 years ago were built in an environment where there wasn't the amount of cyber risk and the openness of applications that interact. So when you think about in today's world, that's a massive risk. If you try to have those systems be interoperable with other systems or with the internet, there's a series of holes that exist because of the operating systems that they rely on that aren't even supported by the OEMs, by the original equipment manufacturers of those software and physical systems. So you have a system where you say, "Well, I'm dependent on Windows 95." Well, there are vulnerabilities in that Microsoft doesn't support Windows 95. So there are vulnerabilities that are obviously going to be at risk, and now you're at risk in that system, and there is nothing that you can do to prevent that risk. So then what our clients, we see companies doing is they just don't feel comfortable leveraging those systems except for the narrow purpose of what it does. And then you lose the value of innovation. So that's really a big driver as well, is this inherent risk that if you don't stay current, you are gonna continue to get exposed to all the bad actors that are out there trying to steal things from you.

Yeah, end of life, end of support also, just these unmaintained systems can definitely open you up. And I think you're also hitting on an interesting dimension with regard to the people as well and sort of the philosophy of the organization. So how should executives think about setting their people up to drive modernization and growth?

Yeah, it's an interesting point, just to touch on the people for a second. I was just talking to a client earlier, earlier today where they have systems that they're using, that they have one person remaining at the company that actually understands those systems. And the reason why is that the rest of them have retired. The systems are so old that, and they're not even able to find people in the marketplace to be able to support this. So some of this is really good, talented people wanna work with the newest technology. They wanna work with what is modern. They don't wanna work with things that are old, stale, unsupported. So you have an issue with your talent try to... So another angle on the talent is, a really important one is you want to ensure that you have a team that is really focused on this concept of the growth mindset, right? There's kind of a fixed mindset and a growth mindset, and it's a very simple delineation. A fixed mindset tends to be the type of approach or the culture or the person that thinks, "Things just can't change. People are who they are, they can't reinvent themselves, they're destined to their past." And the growth mindset really sets for a view of, "No, it is possible to evolve, to be resilient, to embrace change, to really think about what could be." And when you build an organization full of growth mindset people, you allow yourself the opportunity to really reach potential that you couldn't with the mindset of I'm destined to do what I've always done. And that ties to system, system evolution is that that same mindset gets stuck in the mainframe system. "It just works, it's fine. Why do we need to change it?" It's really this missing, this opportunity of what opportunity are you foregoing by not actually evolving?

Yeah, yeah, yeah. And that obviously opens up the risk of disruption and being sort of leapfrog by competitors and falling behind your customer expectations. It's funny on the people leaving the organization who sort of have that, the brain drain, right, of the people who sort of understand these systems. I was talking to one government agency actually who has to contract people out of retirement homes to come in and talk to them about, you know, how these mainframe systems-

I believe it.

are architected. So let the people retire. And I think that also gets to some of the opportunity with AI, which I want to get into. So modernization projects, obviously notoriously long, complex, costly, risky, and prone to failure. I think there's something like 75% of modernization projects fail to complete ultimately.

Yeah.

So what has sort of shifted in the market, and how should executives be thinking about modernization differently in the economics around it than they have before?

Well, I think that AI has changed a lot of things in our world. One of the biggest things that's changed is it's given you a path to think about faster change, faster evolution. And modernization is really nothing more than a continual evolution of getting better, right? Of trying to change. And so modernization now can be executed faster, much more cost effective than previous, reducing a lot of the manual effort that is done, the amount of consultancy time, the amount of ideation time that needs to be done on the front end to really jumpstart how far down the road you can get on that reimagining your application. So for example, moving legacy code into a model-driven platform like Pega with AI and allowing that business value through that modernization project to really drive faster transformation, to get the efficiency, to get the customer experience gains, to get employee retention to improve because their experience of working with your internal systems is much higher. And it's really a far more, more material business case for companies to actually go through that transformation. Whereas in the past, if they had a system, they had to plan it out and they had to maybe spend millions or tens of millions of dollars or even some cases, hundreds of millions of dollars. I've even heard clients spending a billion dollars or more trying to work on modernization projects. And it's a lot of try and fail, like it's a lot of experimentation, of lots of manual work. And quite frankly, resources are at a premium for the people to actually do that work. So I think it's not just around the cost, it's also around the speed at which you can move. Because now, imagine if you could cut that work in half, and that means you can do twice as much with the same amount of resources. I think AI can be even more materially impactful than twice as much, but you can move faster. And as you move faster, the systems become modern, which then gives you efficiencies that you can then redeploy back to move even faster. So what I think there's really a flywheel kind of approach about that AI can really help in terms of how you move and how fast you move with your transformation.

Yeah, I love that. I think to your point, AI has sort of changed both the numerator and the denominator of the ROI calculation.

Absolutely.

Compounds the business value can extract and then obviously makes these more cost effective on the backend. And I think your point on timing is great too. Like, for a project that's gonna take 5, 8, 10 years, the CIO who signs up for that, they might not be around to like, see, reap the fruits of that labor-

Likely will not be.

Right. So I think it is important, and I think AI has unlocked this opportunity to show value quickly within six months, within 90 days, and sort of start to reap that and be the person who's getting the organization off of legacy. So appreciate your time, Ken.

It's been great to be here with you, Matt.

Thank you so much. So if you wanna learn more about Pega's approach to AI-led modernization, go check it out on pega.com. And if you want to get hands on with AI-driven modernization right now, go to pega.com/blueprint.