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The ‘centralized brain’ in the context of an Autonomous Enterprise refers to a centralized system or platform that serves as the core intelligence and decision-making hub for the organization. It draws inspiration from the human brain, which acts as the central command center for processing information, making decisions, and coordinating various functions.
In the context of an Autonomous Enterprise, the centralized brain typically involves leveraging advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics to collect, process, and analyze vast amounts of data from various sources. But what is the importance of a centralized decision-making system compared to a human being?
In this podcast episode, Alan Trefler, Founder & CEO of Pegasystems, discusses the evolution of digital transformation and the vision for the future of enterprises with Pari Natarajan, CEO, Zinnov.
Their conversation reflects on the progress made in digital infrastructure over the past decade, such as Cloud infrastructure, data layers, and advancements in technology. Alan goes on to talk about the need for a centralized brain in enterprise systems to replace the existing decentralized approach, which is scattered across various channels and systems. Alan and Pari also discuss how technologies such as Intelligent Automation are critical to build Autonomous Enterprises, where human involvement is centered around empathy rather than merely running processes. The episode also touches on the role of Pegasystems in serving both legacy enterprises and digital-native companies, emphasizing the significance of having a centralized brain for effective orchestration.
Is a paradigm shift in enterprise systems towards a more intelligent, automated, and centralized approach the need of the hour to drive digital transformation? Find out more in this exciting episode.
Pari: Hello, everyone. This is the latest episode of the Zinnov podcast. I’m Pari Natarajan, CEO of Zinnov, and your host for today. It’s my pleasure to introduce Alan Trefler, CEO of Pegasystems. Alan is a visionary leader, technology change agent, and a trusted advisor to business executives around the world. He has built and grown Pega from a startup to a 1.3-billion-dollar global public company with presence across the world. Prior to Pega, Alan pioneered the model-driven software, which is known as Low-Code, with multiple patent awards to his name – Alan has blazed the trail that is inspiring. Welcome to this episode, Alan. It’s great to have you with us today.
Alan: Well, thank you Pari, and thank you for that generous introduction. I’m thrilled to chat with you again.
Pari: So, let us dive into the conversation and hear from Alan itself. Our view of digital transformation over the last 10 years, Alan, is really about modern digital plumbing, right. You had Cloud infrastructure – it deployed across companies. You had the data layer deployed. You also had modern technology at the edge – be it mobile, be it more powerful PCs, Internet of Things (IOT) censors, and all of that. So, it’s really, the digital infrastructure got built over the last 10 years and during Covid we saw the benefits of it. Be it in terms of level of collaboration or more mobile-led user experience design – which allowed people to seamlessly interact, buy products, operate literally from home. But it looks like that’s just a start of something bigger coming in and our view of digital transformation coming in over the next few years, is really about – more intelligent and automated workflows within enterprises, right. Our view of automation going forward is really about inference and automated actions which results in the solution, right. Which could potentially improve employee experience, partner experience, customer experience, and also improve productivity of everybody involved in an enterprise. I want to get your perspective. You’ve seen digital transformation evolve across all your customers. How do you see it evolve over the next 10 years?
Alan: So, you know, I think you bring up an interesting point and, perhaps, at the risk of being a little, sort of, confrontational – let me frame it in the way that we see it. let me frame it in the way that we see it. Now you use terms like the infrastructure as being built out, unquestionably true, you use terms like plumbing, though a lot of us have been feeling that we’ve been plumbing together data and services-oriented architectures and all sorts of different computers for a long time. But, I think there is and has been a lot of plumbing that’s needed to get done in these most recent phases of digital transformation. But, when we talk to our clients about digital transformation and building on the skeleton, as it were, to draw an analogy of the infrastructure, or the plumbing that is out there, that is like, the circulatory system for data and makes things happen – to draw an analogy. One of the questions we often ask customers is – where’s the brain? You look at your system, you look at what you’re trying to do, where is the brain? And it’s funny, if you look at the diagrams, there is no brain. The brain is spread out. It’s in the channels. People write business logic and process logic in their front ends. They put some of it in their backends and this is a disaster because by diffusing the way you want your business to run across all of these channels, all the existing systems, you create a very, very hard-to-evolve system. And that’s where most customers are today. And I think that’s what’s got to change radically in the next five years.
Pari: But also, there is a concept of a decentralized enterprise with blockchain coming in and things like that. So, how do you see that fit into a more centralized decision-making and a brain foreign enterprise versus a more decentralized organization?
Alan: A great question. So, you know, as so much in this world today is virtual. The central brain needs to be virtual too. It needs to feel like it’s a coordinated, organized central brain – but it has to be able to be federated. You need to be able to take rules and process definitions. You need to be able to take the way you make decisions and federate them out to all the places, all the points of contact – where a decision needs to be made. I can give you a couple of good examples from real life. The idea though, is when you change the brain, it needs to instantly percolate out to all the different places where your enterprise needs to operationalize that. Because let’s face it, if you’ve got great infrastructure and you know you’ve got great data, but you can’t operationalize what you want to do or what you want to change, it’s not going to be a successful company.
Pari: Got it. Got it. And you have spoken about your vision for an autonomous enterprise, right, where, you know, you – in your words are ‘cases,’ which Pega solves, and the whole workflow is completely automated and the human in the loop is really for a empathy perspective, right, and not really to running the processes in workflow of a company. Now, how far are we from a vision of an autonomous enterprise? And are there some examples, use cases, you see here, which shows some weak signals that we are getting closer.
Alan: Well, I think there are a lot of good examples that are emerging. And just to be clear, the autonomous enterprise is not one that sort of tosses humanity to the side. The autonomous enterprise says, hey, we’re going to change our thinking about how we build our systems and infrastructure. Historically, we’ve built our systems for the people, right. We’ve put in a front-end system or a middle office system or back office system. The engine of those systems are humans, and candidly, routinely, they get pulled into a lot of very inhumane tasks. They have boring days. They look at the same stuff over and over again. The system does not participate with them as a partner. They get asked to do things they shouldn’t do because the system should be able to figure it out. The autonomous enterprise is one in which you say, look, there is work here. There are decisions we make. There are processes we follow. We’re going to put those in a brain, make that federate-able to all the front-ends and all the backends, and then the interaction with people is only going to be when the people add value. it can involve some empathy, it can involve some ethical checks – which people still need very much to do to make sure that fairness exists. It can involve a personal touch or it can involve filling a gap that’s not yet automated. But the principle has got to be – it’s not about standing up these systems that, you know, vomit data to the staff and make them interpret what’s going on and try to synthesize what they want to take as an action. It’s about saying, hey, every single time we touch a customer, there’s an objective, there’s a goal.
We’re going to understand the objective. We’re going to apply the Artificial Intelligence (AI), we’re going to apply the prophecies, we’re going to see how far we can get in achieving that objective. Now, let’s talk about onboarding a new child, for example, in our family healthcare plan, right. That’s an objective – that’s something that should be able to be done in multiple channels. It should be easy, should bring together information from multiple data sources. A person should only be consulted when there’s something that’s either missing or that that person can add. I sometimes like to call AI. It shouldn’t be Artificial Intelligence, it should be talked about as augmented intelligence. This is where, you know, you have the engine driving the power and the human brain augmenting it – and being augmented with this interplay, you know. These two things we’ve just talked about, this idea of having a center out brain – that you have this brain in the center, virtually – can be federated center – that drives your front-ends and how you interact with your data, and that what you define are intrinsically automatable processing that lets people pop in when they’re needed. Those are radical shifts. To business, take that plumbing you talked about up front, right, and take some of that infrastructure, and even take some of those, you know, investments that may not have paid off the way you expected. You know, that enormous Salesforce system that was going to save everything, but now just looks like another channel or that big SAP system that was going to record everything, but you know, now looks like, well, I’m not sure how smart it is. You can take those very systems, you have to replace them and you can make them better by putting something in the center that knows – how not just to orchestrate but to automate the objectives of your business. Very powerful. And, you know, the important thing, Pari, to realize is in any material company, is that, there’s not just one system of record, they’re multiple. And they need to be coordinated, they need to be in sync. That’s not just the master data, but the transactional information needs to be organized. And, you know, the Cloud for all the wonderful things that Cloud brings, the Cloud – brings a massive increase in complexity to how, for example, these systems of record might work. I might end up having a system where I’m posting my transactions, maybe that SAP system I mentioned. I might have another system where I’m calculating my commissions. Think of that as another system of record. I might have another system in which my product returns are received and managed, and 40 more. Several of those – maybe Cloud systems. They all have different data structures. They all operate in different physical domains and domiciles. What holds them all together? The naive answer is microservices – because we all know that microservices solve every problem. You know, and we use microservices, extensionally, but microservices need orchestration. They don’t bring orchestration. Microservices need rules, need guidance, need that sort of auditability and control from a business point of view – that this brain and this muscle, this set of engines for decisions and process, that’s what Pegasystems is committed to bringing. We want to be that engine in the center – capable of unifying multiple Cloud platforms, unifying multiple backends, not obviating them. Absolutely, SAP is a great place to post stuff. It just might not be the best place to decide that – this customer should do this transaction. Because boy, there’s a lot of logic and perhaps a lot of process steps in doing that, and it shouldn’t be there and it shouldn’t be in the front-end.
Pari: Got it. It’s very interesting. So, now customers can bring in different types of records. Whenever they’re looking, going into a new country, they can bring in the system that already will have the Pega platform over the top, which is the intelligent layer, and which will then orchestrate and bring that new system of record into that layer – and automatically be able to drive it on top.
Alan: So, I think that’s right. I’ll give two little clarifications. First, it’s not just going into another country. Think of what happens when these bank mergers occur. Right. Suddenly you’ve got a whole new collection of records. You may want to get rid of them, but it’s going to take years. And you don’t want to expose that to your clients. You don’t want to destroy your operation by having to do too much swivel chair between things or manage risk across multiple systems. This is exactly what this center-out way of thinking does. You said Pega over the top – I consider that an old way of thinking. We don’t want to be over the top, we want to be at the center.
Pari: Got it. Alan, do you see a difference between, I would say, a modern conglomerate, I’d call a Google or Amazon as a modern conglomerate, working across businesses built over the last 20 years – the systems are very new. A lot of these systems are homegrown versus small legacy large banks, large manufacturing companies who’ve been Pega customers for a long time. Is there a way in which their organization, internal systems and architecture, is different and does Pega play a role in both? Or do you see your role more in the legacy enterprises than the more digital native companies?
Alan: Oh, we very much see ourselves playing a role in both. Both of those companies you had mentioned are important Pega clients. So, we work absolutely with that full gamut. What I’ll tell you about the companies that have a more digital native start is – they do some things that are better equipped around, for example, having Application Programming Interface (APIs) available, around having sometimes a more modern approach to the technology they’re using. You know, we for example, were a Kubernetes shop, in terms of how we run Pega Cloud and other things. That’s much more common, obviously, in companies like a Google, which is Kubernetes – through and through, versus some other firms in more traditional businesses that are just adopting it. But the more important question from our point of view is what does the orchestration? Is the orchestration done in like front-end systems? Is the orchestration done by building more and more into SAP or backend systems? You know, do you go by a Timco bus – like people did 20 years ago to, well, you know, that hasn’t exactly clicked, but, you know, those questions, which are examples of doing on the edge which should have been done in the center, is still something that applies – candidly – to most businesses that are out there. Because even the people who are entirely API and entirely microservices- based – still need a brain, they still need a process engine because otherwise, they end up coding things in the front-ends. And once you code in the front-end – how to onboard a customer, once you code in your front end how to handle a dispute, you’re screwed. Because if you got to do it on the mobile, well, it’s got to be redone, it’s hard to keep in sync, hard to get coordinated. You want to do it now with an API? Well, that logic is outside your APIs. You got to find some way to make that accessible. You want to do it in the contact center? Wkell, that requires a new implementation. That’s why all of these businesses, including the new ones, struggle with change.
Pari: Very, very interesting. Because once you bring it to the center, then it’s very easy for you to orchestrate it, bring in new channels, and make the organization a lot more agile. So switching into your customer segment – so, you work with large Chief Information Officers (CIOs) and Chief Executive Officers (CEOs), what are the biggest concern for CIOs when you meet them today? Like, what are they worried about?
Alan: Well, I think a lot of them are worried about how a reaccelerating technology landscape, powered by things like – generative AI and other elements is going to be survivable – when they’ve had so much staff turnover and where really high-skilled people are in short supply, and often lack the loyalty and the stickiness to stay. And you know what our, you know, pitch to these people are – is look – a model driven architecture makes it much easier for people with less experience and perhaps who are not as senior – to achieve things that otherwise some miracle worker would have to do by hand in Python.
Pari: Interesting. So the model-based architecture will allow them to not require the same level of domain capability or the technology skills in their talent pool to be able to drive these.
Alan: Well, rather than calling the people unskilled, I’d rather say it provides the guidance and the out-of-the-box capabilities to accelerate people to become excellent – as opposed to the normal learning curve. So, it really can get people far more effective when it comes to applying AI. Far more effective when it comes to managing these rules. You know, we’ve built a lot of this in. We have this concept, Pari, you may have heard of code or we patented it called the ‘layer cake.’ Where we’ll take a very large business and we’ll say, hey, you’ve got these things that apply across your business as a whole. This is stuff for your consumer division versus your commercial division versus another division. Here are the process and rule and decisions are going to be made for North America versus Europe versus India. And then here are maybe product variations and the ability to organize the rules and processes at enterprise scale. Get the decisioning to work, at enterprise scale, is part of what our vision of the autonomous enterprise is. And it’s really, I think, how we strongly differentiate ourselves from a lot of these other folks who call themselves low code because, we use that moniker too, but ours doesn’t look anything like theirs.
Because everything we do is built with this idea of, you know, the “Low Code”, the model driven piece is fitting into an enterprise structure, is managed by an enterprise structure, will be visible in an enterprise structure and a lot of, a lot of those other systems, candidly, they’re just kind of like the new generation of Lotus Notes. Things you can whip together fast, but that, you know, become technical debt in, you know, 24 months.
Pari: Got it. And, and one of the other thing you mentioned about the CIOs, uh, looking at technology acceleration and things like Generative AI, something in their mind, and you are one of the first companies to launch, integrate Generative AI in your product.
So how are customers, using it? Any early feedback from customers on the launch you did recently?
Alan: Yeah, so what we showed recently were the specific cases we’ve been working on, since last year to bring Generative AI into the fold, but do it, I would say carefully and wisely because, there’s an enormous amount of buzz, but there are some use cases that are just, you know, awesome and brilliant and there are some use cases that are going to get companies candidly, in trouble. So the use cases we’re using, and we’ve just begun introducing these to clients, so, you know, it’s still what I would say emerging days. Sure. But the pace of this emergence is going to be lightning fast because everybody, everybody wants it. And by the way, it’s going to be the highlight of PegaWorld, which is in the MGM Grand Las Vegas from June 11 to 13,
We’re going to be showing and letting people touch and play with, what I’m about to describe to you here. The capabilities include primarily making Generative help me as a builder, build the system my customer needs. Being able to ask what are the types of fields that would be appropriate for this type of objective, for onboarding your customer? What are the types of stages a piece of work might go through? What are the types of ways I would want to describe what I’m doing to a customer? And we generate these and then allow a human to say, yeah, I like that. I’ll take it. Or say, nah, not so much. So that is a model where we really, you know, are dramatically simplifying our bill. But doesn’t have a lot of the risks people are worried about where the AI will start hallucinating and destroy your customer relationships.
Pari: So, so very interesting. So the design of the, some level, the design of the workflow application, you are using Generative AI to augment human, to give them the right inputs and then your Low Code system and they can use your traditional, Low Code system to be able to deploy it.
But it, it helps in designing that by bringing in all the inputs from all the organization capabilities. Pega has. Very interesting. I’m looking forward to seeing that at the PegaWorld.
Alan: It’s pretty magical because in addition to using it, it’s also now interfaced to our system. So you can adopt it with one button push.
Alan: And it actually builds a model.
Alan: It’s pretty remarkable. I also, by the way, think “Low Code”, you know the Low Code market, which has like 120 people who say they’re in it one way or the other. I think the entire, bottom end of that market is going to be destroyed by Generative AI. It’s going to go away. Lots of those little vendors that you know, advertise you can build little systems – you can now generate those systems.
Pari: And how does it impact the, you know – this is the final question I had – how does it impact the Pega ecosystem? You have a set of partners, Independent Software Vendors (ISVs) building on top of yours. We have system integrators. Several of them have built hundreds of millions of dollars of revenue on top of Pega. And with all of these newer Generative AI systems coming in, is it going to be a positive or a concern for your partners who are building on top of Pega?
Alan: Well, first of all, I think the partners absolutely need to become educated in how we’ve incorporated this into our products. So, you know, we will have Pega Academy classes and they’ll probably need to each take a couple of days of classes to make sure they really understand it all that well. But having done that, this should accelerate their projects in very meaningful ways. And what I’ve always believed is that, if you get the work that you’ve been asked to do faster, you get more work, not less work. Right. And so this should be, I think, positive for the partners because it will make their work more cost effective. And digital transformation – It’s not like we’re reaching the state of finished, right. Digital transformation – if you can do it, you know, with less expense, greater reliability and greater speed, the demand goes up. And so I think that’s going to both power our partners and empower us.
Pari: Just in time learning for your partners or your customers learning on Pega.
Alan: Yeah. Well, at least, just in time – reinforcement. I don’t, personally, I don’t encourage complete – just in time learning. I think it’s good for people to know something when they walk in the door. Right. A little early. But reinforcement and that sort of extra care that the autonomous enterprise can have both in terms of its tooling but also in terms of how it treats its customers are extremely powerful.
Pari: Great. Thanks, Alan. Thanks for covering a wide range of topics from how digital transformation is changing and the need for a centralized brain. And hopefully, that will be Pega than anything else from a customer perspective.
Alan: Well, we feel really good about having worked, you know, the way I describe it is – you know, we’ve been doing this 39 years and have become an overnight success. So, we really feel like we’ve pulled a lot of things together – that now are doing extraordinary things for clients, like, RaboBank in the Netherlands has an amazing set of implementations that really live up to sort of the principles that I’m talking about here.
Pari: Thanks a lot. Thanks for taking the time to share your insights with the audience. I’m pretty sure it was very insightful for them and, really, I’m thankful for taking the time with us.
Alan: Brilliant. A pleasure. Talk again soon.
Pari: And that brings us to the end of the episode. We’ll be back with another episode featuring another pioneering leader. Until then, take care and stay curious.