Age of Autonomous Enterprise – Don Schuerman, Pega

This is Textron tv. Hi everyone. Welcome back here to Textron tv.

I've got a, a, a guest I want to introduce you to here for this segment. His name is Don Schuerman. And Don Don wears a lot of hats over at Pega.

He is the, uh, CTO o chief Technology Officer, as well as Vice President of marketing and technology Strategy. So that's a, a lot, a lot of work right there. And, uh, Don, welcome to techstrong tv.

It's great to be here. Thanks for having me. It's a pleasure to have you here.

So, Don, as I said, you got a lot of hats, you got a lot of responsibilities. How does one, you know, did you forget not to volunteer? Did everyone take a step back or use stayed still?

How, how does one wind up with all of these things in your domain? Yeah, I, I think, um, like I think a lot of people's careers sometimes are, are more drunk in walks than we want to admit. And, uh, I, I ended up here after spending a number of years in kind of the intersection of client and technology.

So I was in delivery, uh, like professional services, consulting. I was in engineering for a period of time and actually wrote some code. I spent some time doing pre-sales consulting, so sort of the technical side of pre-sales and really kind of established a niche for myself where, you know, I, I often think of CTO as Chief Translation Officer and a large portion of what my job, my team's job is to make sure that we're helping our clients understand what we're doing in our technology, what trends are going on in the marketplace, and how that connects to the value that they need.

And then at the same time, make sure that we understand what our clients are doing, what their strategies and needs are, and we translate that back into our product and our engineering teams so that we can actually make sure our roadmap is aligned with what our clients' needs happen to be. Excellent. And then that's a great, a great way of looking at it.

Um, and, and Don, look Pega in, in my world, Pega is a very known company and, but maybe there are people out here who are not familiar and there probably are. Why don't you give us a little bit of kind of the Pega background, if you don't mind? Sure.

Um, so, uh, we're a software company based in, uh, Cambridge, Massachusetts, in the Boston area. Um, and, um, we serve some of the largest organizations and provide them with a low-code platform for AI power decisioning and workflow automation. So how do we help them make the right decisions about the workflows they're doing, how they interact with their customers, and then how do we help them automate those processes so that the work is getting done both efficiently for the business, but also easily and effectively for the customer or the stakeholder on the other end.

And we work with clients, uh, you know, like Citibank recently presented at our user conference talking about how they're using Pega to personalize all of their engagement with their, their consumers. We work with large banks who use Pega to, to, um, accelerate the acquisition and onboarding of new clients. Uh, Virgin Media spoke at PegaWorld about how they're using Pega to automate the customer service experience that they deliver.

We also do a, uh, a lot of work in, um, core operations of the business. So we work with a lot of healthcare providers, for example, on things like claims and how they manage their and optimize their claims processing. And, um, we also do a lot of work sort of in what I call the resolving exception space, right?

Fixing things when they go wrong, when things drop off the happy path, how do you get them back on the right path as quickly and as easily as possible. Got it. You know, a lot of these things you're talking about really kind of in my mind fall under the, the umbrella, if you will, of digital transformation.

Yeah. Right. As these companies are looking to leverage digital technologies to just be better, to serve their customers better, to give customers what they want faster.

Um, it it, it comes under there. Now, I know, I know in your role and, and Pega in general, they talk a lot about the autonomous enterprise. Yeah.

And so what, what's, what is it, what does an autonomous enterprise mean to you? Well, well, well, so, so let me, let me ask you, I'm gonna step back to the term digital transformation cause cause I think it's a loaded term. It's a loaded term.

And I think one of the things that we've learned in technology over the last couple of years is I think in some of the early phases, we started talking about digital transformation like eight, nine, maybe 10 years ago. And I think there was this kind of perception that digital transformation was like any other, oh, pro, sorry about that. Any other project that you go on, right?

Like, we're gonna do some digital transformation, we'll get a team together, we'll all get in the room, you know, six, nine months later we'll be like, check digital transformation done, released out the door. Right? I think what we've learned is that digital transformation isn't that digital transformation is actually about becoming an organization that can continuously change and adapt.

We do not know, nor can we predict what the market is gonna throw at us. It may be covid, it may be inflation, it may be a banking crisis, it may be fantastic new technology that suddenly has got every c e o in the world being like, where can we use generative ai? Right.

What Our story. Right, exactly. So, so, so you've gotta build an organization, you know, that, that, as we say in our tagline, you've got to build for change.

You've got to actually operationalize agility into the organization. And we think the north star vision of that is this idea of an autonomous enterprise. So how do you bring together ai, both generative ai, but also some of the more analytical AI that we've, we've had in our toolkit for many years, how do you bring together automation, whether that's robotics, workflow automation, process orchestration, but how do you do it in a way that allows a business to continuously optimize, to constantly be finding new opportunities for improvement?

And in some cases, allowing those processes to become self optimizing, to automatically discover a bottleneck, suggest a fix, get the approval from a human, and actually implement the fix to make it better. And I think the really exciting thing is through the combination of both existing technologies like low code, uh, approaches to software development, robotics process orchestration, process mining, et cetera. And now with generative AI layered on top of it, the ability to actually talk to our systems maybe in a different way than we could before.

I think we're actually really close to being able to have self optimizing processes running inside our businesses. And that continuous improvement always with a human in the loop, but automated as much as possible, that's what we're getting at when we talk about the autonomous enterprise. Agreed.

Good. I I like that definition. That's good stuff.

You know, Don, I'm so old when I think of digital transformation, it was analog versus digital, right? That was kind of my worldview. But o you know, COVID has changed it.

And I think just seeing how companies, and I think you hit a dead on, if it's not covid, it's inflation. If it's not inflation, it's a banking crisis or a war somewhere or, or now, you know, ai, everything, um, digital transformation to me has now become more nim. You know, you have to be nimble, you have to be agile.

Maybe it's agile with a small a not like Scrum Agile. Um, but you've gotta be able to be adaptable, right? To, to an ever-changing world.

And, and u utilizing digital technologies is the key to that. And, and digital transformation isn't about the end state to me. It's about accepting the fact that you are now in a business that is going to have to constantly transform day in absolutely day out, constantly transform because your competitors, your customers and the market are gonna demand that you do it.

I couldn't agree more, and I think perfectly said. Thank you. Um, all right, so, so we've defined the autonomous enterprise.

Now, just because you defined something doesn't mean you can get there, right? Right. It's like, okay, now I got the map, but I still gotta follow the map and get there in one piece, hopefully.

Yeah. Um, so how, how can businesses working with Pega, you know, how can businesses in general kind of follow the path? How can they accelerate, get there faster, be there quicker?

Yeah. Well, obviously, like one of my answers is the, the way to get there faster is to work with Pega, but putting that to the side, right? Okay, appreciate that.

But, but you know what, what, what, what I, you know, what I think of is I think there's a roadmap and a journey that you go, and I, I look at the journey very similar. The, the analogy I often use is self-driving cars. I think for lots of reasons, fully self-driving cars, like I get in the car, I say, take me here, and it just magically gets me there, right?

We're still probably many years away, not because regulatory concerns, cultural concerns, like, I like to drive. I'm not ready to completely give that up. And frankly, those of us that have built complex enterprise systems know the hard part isn't the individual components.

It's getting them to all work together consistently and predictably. And so it's a bigger, maybe technical problem even than Elon Musk thinks it is. That said, I get in my car today, I drove to the office in traffic today, and it was autonomous, right?

I put on my cruise control and the car automatically sped up and slowed down based on what traffic was doing. It warned me if I started to drift out of a lane because I was paying too much attention to the podcast that I was listening to, right? I was able to have a drive select where the car would dynamically change the responsiveness of the transmission when it detected that the road was a little bit wet because of the rain that's happening here in Boston.

Um, I was able to ask Siri to, um, play me a playlist of music that sounded like the, you know, dead end company concert. I went to this past week weekend with a buddy I had traffic guidance on, and it was constantly readjusting my route based on like where traffic was, right? All these little autonomous pieces that were making me a better, safer driver making the driving experience better.

I think that's how we think about investment business, right? How do you inject these pieces of autonomy? And the way you do that is, look, you start with, there's a lot of stuff that we still do in business that I would just say is not only unautomated, it's unmanaged.

There's stuff that happens where we don't know how it gets done. We don't even know if people are working on the right most important things. So step one is how do you take your unmanaged stuff and get it to managed?

How do you have, whether it's case management or simple process controls or top level prioritization so that people are at least working on the most important stuff for the business at any given time and you know, where the work is. And that structure right now that I have managed work, that structure gives me the ability to start automating things. Okay?

That's next step. Now I can start actually injecting automation. I can use a robot to go automate a task.

I can use a web service to go pull in data that I might wanna, wanna have. I can guide a user using business rules. And as I do more of that, I'm now building up structured data about how that work gets done.

Well, data lets me feed ai. It lets me feed intelligence. So now I can do things predictively.

I can make processes that are truly intelligent, right? I can predict, Hey, you're gonna miss an sla. Would you like me to ex uh, escalate this for you?

Right? I can predict customer behavior. Hey, customer has a high risk of churn.

Should we offer them a retention plan, right? So I'm now starting to, to build intelligence in, and when I attach that intelligence to a feedback loop, I get something that starts to be self optimizing. I get something that starts to figure out like, Hey, I predicted an SLA would be missed.

You took this escalation action and you fix that problem so that next time that happens, I might just automatically do the escalation on you. Right? Now, I get a process that starts, or a customer conversation that starts to be self-optimizing.

And that path from unmanaged to managed to automated, to intelligent, to self-optimizing, we can take across sort of every process and every customer interaction in our business. I love it. First of all, kudos on Catching the Dead and Company show.

I have, I had tickets for them on the last tour and they canceled. And then I, I just, I'm missing this tour and it's like tearing me up. It's The last one supposedly.

I know, I know. Well, no, it, I mean, look, so I, I go to, well, we'll talk offline. Um, let's get back to the side of his enterprise.

But, but you're right. It, it is about, you know, and then, then the, the, the examples of artificial intelligence and applying it are, are dead on, right? And I think, I think the examples and the kinds of things you're talking about, Don, are kind of meat and potatoes.

Where rubber meets the road, there's a lot of people yelling and screaming, and the sky is falling, you know, with ai and it's gonna take away your jobs. And, and, and I'm not, I'm not here saying it's not going to change things. It's going to change things.

But right now, where, where, where rubber meets the road, where things you could really do are the, the kinds of things we're talking about here, and it, and it works for you. Um, And, and the way you make, the way you make AI both more effective and less risky is you give it a structure to operate within you, give you, you, you, you box it into a specific task, right? So let me ask generative AI to lay out and recommend the steps for a process so that I can use that as a starting point and then iterate it, tweak it, change it.

Let me ask AI to summarize a history of a customer interaction for me so I can help my agent do the, have the conversation more effectively and quickly get what the last three months of customer history looks like. Like once you box it in, right, you find those little moments of autonomy, that's when you deliver value, but you also, it's also safer cuz you're not, you're not, you're not letting it go rogue. You're actually giving it very specific functionality for it to perform.

I, I couldn't agree more with you man. Don, we've got a few minutes left if you don't mind. I want to turn Pega specific here a bit.

Sure. So you've laid out, you've laid out a great realistic vision I think, of where enterprises and business are today, where they want to go, what they could accomplish that's doable. How do you engage our audience out here?

How do they engage with Pega to help them achieve this? So, you know, first of all, you know, we have clients, many of the people listening may already be Pega clients, right? And so, so the things that I would say is there's often expertise inside your group, inside your organization, around Pega, around how you might be automating some of your processes, et cetera.

So engage and start with that team. com. Um, we've got some lots of, uh, of great both sort of demonstrations, but also tools.

You know, I go into much more detail in of some of this on the autonomous enterprise and the keynote I just delivered at PegaWorld. And so you could use that as sort of a starting point. We've also been looking at very specific use cases for generative AI around how do you use it to more quickly deploy process applications, better optimize customer engagement and personalized customer experiences, make customer service agents more effective.

And, uh, we've recently announced about 20 of these use cases that we're putting in the, the upcoming release of our product. com as well. And I think they're just really great as sort of getting people thinking about, okay, how do I apply what can be a kind of big scary technology, but in a real pragmatic way?

com, you can, you'll see a big link to Pega Gen ai, which is our generative AI application. You can also check out from there the PegaWorld replays and see some of the stuff that we talked about at our recent user conference. Excellent, man.

Hey Don, I want to thank you for coming on here and, and talking with us today. This was great. Invite you back anytime you'd like to talk about the autonomous enterprise, digital transformation generator of ai.

These are all things we talk about all the time. So thank you so much. Thank you much, Alan.

It's great being here. All righty. Don Schuerman, CT O VP marketing technology strategy, all of it at Pega here on, uh, Techstrong tv.

We're gonna take a break and we'll be back in a moment with another guest.