Hi, I am Don Sherman, PEGA CTO, and today we're gonna talk a little bit about what we call the Center-Out Business Architecture, and why that is so important as you think about your digital transformation initiatives. You see, so much of the software that we built in the enterprise wasn't actually built around the idea of automation, or around the work. It was actually built for a world by which we assumed the people were gonna do the work. And because of that, we actually built a lot of mistakes into our software architectures. First of those mistakes was we built our software really around channels. So we built a lot of apps for our employees to use, or we built self-service applications, either on the web or as mobile applications, potentially for our customers. We built contact center applications for our contact center agents to use. And increasingly, we're repeating this mistake by building chatbots for our customers to be able to chat with using AI tools. But the problem is, in each of these instances, we've encoded the logic, the experience we wanna deliver into the channel apps, which means that every time we wanna make a change, we have to go into each application and make the change again and again. And worse than that, when our customers try to experience this and they move, say, from a web self-service application to calling into the contact center, you have no memory of what they were doing. And so their experience becomes disjointed. they have to repeat themselves, and it takes far longer to resolve their requests. The other mistake that we made was that we built our applications around data. So we built databases, or customer data platforms, or ERP systems, or we were stuck working with large mainframe environments. And while data is absolutely important, in fact, it's increasingly the lifeblood of how we build AI-powered systems, trying to design a customer experience around your data store is pretty expensive, pretty brittle, and doesn't make a lot of sense. So rather than starting from the top down, or the bottom up, we advocate working from the center out, so actually build your systems around the decisions that you wanna make, the work that you want to get done, and the outcomes that you want to deliver to your customers and employees. So in order to do that, you need to actually capture inside of your systems what that intelligence is. What are the decisions that you wanna make? And increasingly, in today's world, we know that we're gonna make a lot of those decisions using AI, whether that's generative AI, or traditional machine learning or statistical AI patterns. But more than just the decisions, we actually want to capture the automation, the workflows and processes we want to orchestrate and get done. And for too long, we captured those using these really sort of legacy models like BPMN and process diagrams that were hard to read and became some sort of weird pseudo code. Rather than doing that, we'd like to capture your automations in a straightforward way, what we often term a life cycle. What are the stages that a piece of work needs to go through in order to get done? And what are the steps that need to get processed to move the work through each stage? So I've got an easy, business-friendly and stakeholder-friendly way of representing the work. And then the final piece of the puzzle is I need to have case management. And case management is essential because it wraps all this together in context so that I understand what's the data that I need, what are the decisions I need to make, what's the automation and orchestration that needs to happen, what can be done by systems, when do I need a human involved, and how does that all ultimately relate to the outcome that I am trying to deliver to my business or to my customer? So by putting all these things in the center of the architecture, and then having the right API is what we call the digital experience API on the front end that lets you plug this into any channel, whether it's a PEGA-based front end or your own web self-service tool, or even somebody else's CRM desktop. And having the right APIs on the back end, what we call live data, which is a data virtualization layer. You don't even have the data fabric, but you need a data virtualization layer that helps separate the complexity of your data store from the way in which your decisions and workflows need to use it so that you can easily plug into all of your existing legacy data stores. Or if you need PEGA to be your system of record, we're happy to provide that with the latest Cloud-based databases. But by building from the center out, you've now fundamentally changed the way you build software so that you're not building around channels, you're not building around your data back-ends, you're actually building around the automations and experiences that you want to deliver, and setting up your organization for digital transformation and the AI future.
