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PegaWorld iNspire 2023: The Future of Work: The Autonomous Enterprise

Leading organizations are focused on automating their business to create new business opportunities, reduce costs, and better service their customers. Enterprises are on various levels of automation maturity. Learn how successful companies are progressing from simple low code and case management up through autonomous service. Understand how businesses determine where to best invest to drive value with automation.


- I'm Ken Parmelee from Pega, I'm Director of Strategy, and really cover kind of a lot of where we're going in terms of the platform, and the market, and those kinds of things. I'm joined by Saurabh Gupta, who's with HFS Research. So we're gonna do two things today. I'm gonna go through a little bit about autonomous, and you heard some of this, this morning with Don Schuerman, if you were at the keynotes this morning. And then I'm gonna turn it over to Saurabh to really take you through some research findings that HFS has had on autonomous. And so, they're really interesting. There's a paper that they've done as well. I highly encourage you guys to check it out after the event, but this is hopefully something that you both have interest in and have questions, we will do Q&A at the end as well. So there's a lot of hype. This area, especially with autonomous and generative, has continued to bring about this concept of, you know, is it gonna be panacea, this wonderful thing where I've got digital assistants that are helping me do my job, that are gonna help improve the way my business runs? They're gonna give me more ability to operate on data and find things that I had the ability to do on my own. Or is it gonna be the machines take over the world and destroy everything? We don't believe it's gonna be the latter, or we wouldn't continue to push this space, obviously. But the idea of autonomous is not to get to where machines run everything by themselves. It's really to put the power in the hands of users and to optimize your processes to the point that they will run as autonomously as you want them to. And you can put a human in the loop, you can remove humans from the loop, but it really is gonna come down to, a, the environment you're dealing with and what kind of processes you're trying to automate. So, there's been a lot of evolution over technology over the centuries, and the point to really think about with all this generative and autonomous stuff is, at one point, trains were dangerous. People were afraid of 'em. They were gonna ruin everything. Like, they were gonna destroy the country. Like, you know, take away everything. That's evolved over time, obviously. We've had so many technical evolutions over the years, everything from, you know, standard stuff like RPA and some of these newer technologies over the last few years. Everybody evolves into these things. You know, people value the software by what it does for them. You think about VR glasses, how many generations of these have we had now, right? Apple just announced a new one. Many of them have disappeared, right? They've come and gone. The value comes when people find the use cases and they really evolve to use them in a way that adds value to their business or the way that they operate or their jobs. And so, really, you're gonna find, with generative and with autonomous, that there is this phase right now of megahype, right? Tons of hype. Everybody's talking about particularly generative ChatGPT, this stuff. But it's gonna find its value areas, and then in other areas it's gonna have less value and go away. One of the things that we would tell you that is highly valuable about generative, is it allows, for people who are non-technical, to start engaging in doing technical things. Now, it does a lot of stuff around content creation. There's a lot of other things that you can do with generative technologies. But I think the people or companies who are really gonna make something happen here are applying it to real-world problems as opposed to kind of pie in the sky stuff. There's obviously cool use cases. All of us can go and play with this stuff and come up with good or scary art, depending on what you saw this morning. But, you know, I think the objective here is we really have focused on how you apply this to real-world problems today, not some evolutionary concept that may or may not happen in the future. And so, when we talk about autonomous, we're really talking about an AI driven set of capabilities. And that just means insight, understanding patterns. How are people adopting your things? How are they responding to offers? How are they driving their use cases with AI? Automated end-to-end focuses on that idea of having the automation to drive through those processes most efficiently. There's a lot of different things that apply to automating end-to-end. It's not just about having a nice process flow, right? It's about understanding how people actually use the process. Do they follow the steps? How much of it is fully automated versus things that you require humans to be a part of? And a lot of what's happening today is modernization of processes, right? So, every company's had legacy systems, many applications, many backend workflows for a long time. So, how do you kind of evolve those things forward, leveraging AI and other things to drive that intelligence, to drive that advanced set of use cases that you can take advantage of today. And self-optimizing is kind of that last bit. When we talk about self-optimizing, it's really a focus on the idea that the process understands how it should run. It's able to tell you where things are not working effectively. It's able to focus on where there are problems, and tell you where there are problems so that you can either tune it or let it make its own changes and update. And so when you think about that cycle, that's a loop, and it's continuous. It's not a linear thing, right? You're not gonna analyze your process one time and say, "Okay, I got it. Everything's good." You're gonna continue to focus on how you can improve it over time. Sometimes that's gonna mean you can remove steps. Sometimes that means you can remove, you know, different kinds of things that are happening in that process that allow you to more effectively enable your business. We see in call centers all the time, and in marketing, and those kinds of things, these, you know, antiquated processes that really require a huge amount of manual effort where things could easily be automated. Sometimes that's an advantage, right? Sometimes you wanna be able to automate those things out. Other times you need the creativity or you need the insight of individuals to be a part of that process. And so, you don't engineer this stuff so that it removes every human everywhere. You really leverage humans for what they're good at and what they do better than these automatic insights. So, why is this such a big deal now? Why are you hearing about autonomous enterprise? There's a really good reason. There's a bunch of technical change, and there's a bunch of business environmental changes that have happened in the last several years that have really disrupted everybody, right? You know, digital transformation, as much as that's the overused term of today, is something that's came out of an idea of I can innovate my business through these new software technologies, right? But when you look at what we have here on the technology innovation side, it's not one thing. It's a lot of different things. It's the evolution of AI. It's the fact that you now have all of these technologies around eventing and kind of the integration technologies that allow you to not only do this stuff in a way that's much more effective than you could before, but also faster and lower the bar for the skills needed to build automations, to build workflows, and to build applications. And so, those technical things have enabled things like low code, and they've enabled things like real-time integration and those kinds of things that used to require really senior level developer people. Now, do you need those people still? Absolutely. You still need those people. But why? Because what you are doing now to today is architecting to enable a wider proliferation of the ability to build things, like workflow, and applications, and AI insights. On the other side where we're talking about business realities, I mean, we all know all the challenges we've been dealing with, disruptions from the pandemic, supply chain, all kinds of different things that have disrupted the way that people work. I was in a client session yesterday from a big insurance provider and, you know, they were talking about how much it took them to adapt to allow people to work from home, you know, applications, security capabilities, all the different things that they had to deploy to make sure people could do their day-to-day job in a way that was effective. And so, you know, when you think about what that means, architecting and building the application to the workflows you need, to kind of already have that insight of being able to adapt when things occur, it really provides for a way for your business to evolve in any way you want. That could be digital innovation with new applications, going into new lines of business, all kinds of different disruptions that provide an opportunity for your companies. So, there was some reference this morning to some research that Pega did. And one of the things that we found, and look at the lower part where it says, Phase, is that in terms of autonomous or even intelligent automation, very few companies have gotten to even that intelligent automation phase. And when you look at what that means in terms of your ability to do better, more, faster, that's a major challenge. Because if you can get past simple automation, just to the intelligence space, you at least understand more about what's working and what's not. You understand more about your clients and your partners. All the kinds of interactions that you have, you can enable that in ways that you couldn't before. When you get, you know, further up that scale, you can understand the 360 degree view of your clients. You can understand much more about the way that your business operates, and what works and what doesn't, but that requires breaking down silos in the organization. That means you need to have unified intelligence. There's a bunch of things that need to work together to make that happen, which is why you see such a small percentage of folks getting to that space. But that evolution is starting to increase very rapidly. What we are seeing is that move to intelligent automation is something that's very active right now. Companies are investing millions and millions in getting there. And it's for the simple reason that you have too many gaps in your understanding of the way your business runs, and so much of it is so manual that it makes it very hard to evolve without putting some of these technologies and these new processes in place. So I already talked about these disruptions that are happening. I think one of the things that's important to understand is part of the way companies are focusing on fixing these challenges is really by getting hyper-personalized. When you understand your customer, you understand the things that resonate and the things that don't with them, you can evolve your channels. You can really focus on the way that you are adapting your business over time. And that also means you can do things like testing the market more effectively. And so, when you think about kind of these different areas from hyper-personalized to as a service experiences so that people are, you know, taking care of their own challenges, whatever they need to with you, the focus on efficiency, which is more about, you know, costs and bottom lines and how fast you're able to adapt to things, and then the agile everywhere, these are all really reactions to what's happening in the market, right? But this is a consistent set of things that we are seeing, you know, in our client base in terms of the way that companies are focusing on how they become more autonomous. So, how many of you know Leavitt's Diamond Model? I'm sure many of you. Yes. So, the thing that's important about this is, this is not just a technology thing. You know, there's lots of great technology on the market to handle some of these problems. The thing that's important to understand is this does take change on multiple levels. You need to make sure you have the right skills with your people. That they are focused on the right kinds of things. On the process side, obviously you're focusing on how those processes run and that they run effectively, and then the technology supports those things. When you have all three of those things working effectively together, then you have the ability to make change. Saurabh has a great concept around here, which is the data also now plays a role in this, 'cause it is one of your natural resources in the business now, right? Understanding how data affects all of this, leveraging AI is an impact that is also interesting in terms of how you make this change more effective. So with that, I want to turn it over to Saurabh. He's gonna take you through the HFS Research and what they've found as a part of autonomous. Thanks, Saurabh.

- Fantastic. All right. I think we could just be more intimate here. We could even like talk to each other almost instead of this being a presentation, but let's carry on. So look, I think one of the things that I've realized, and I've been in this industry for donkey's years now, is that businesses and people react. They don't do just stuff out of their own volition, right? You need triggers for people to change. You need triggers for businesses to change. Otherwise, nothing happens. You know, we just keep going. You know, the cog keeps turning. And I think over the last 30 years, there have been three triggers. The first trigger was the internet, you know? The internet is what changed the way... The internet brought globalization, otherwise it was so hard, right? And that changed the entire way that companies operated. And that was the first trigger. And through the internet, we had the Y2K problem, you know, and I got my first job as, you know, just to make sure that there are four digits instead of two digits. That was my first job, to just code that kind of stuff on AS/400. How many of you remember what an AS/400 is? Does anybody remember? I have five-

- Used it? Yeah. Oh, you still use it?

- Most of the-

- Yeah. I was like joking to somebody, like, if I had stayed on with my first job, I would probably be earning like 1,000 bucks an hour right now. But anyway, so I think the second trigger was the whole economic recession of around 2008, right? And that sort of created all these IT companies. I think some of you might be there from Accenture, EY, Infosys, you know, Cognizant, Wipro. Look at Accenture, they are like 800,000 people. It's not even a company, I call it a country, right? That's been booming for the last 15 years. You know, that whole IT revolution, IT services, SIs, whatever, BPO, whatever we call that, has been just going up and up. We saw that hockey stick happening through the recession. And now I think there is the third trigger, and that third trigger is inflation. You know, I was doing my staff's compensation evaluation earlier this year, and, you know, we have an India geography, we have a UK geography, and a US geography. And India was almost always highest inflation, right? So the wages were almost always the highest increases in India. And this was the reverse. For the first time in my career, where I had to, you know, increase the salaries in US, or UK was probably the highest, second was US, and third was India, right? How many times have you seen that happen, right? They've not. Inflation is brand new to the western world, and we don't know how to deal with it. And we might be trickling it down, but still there's inflation. Along with inflation, there's supply chain disruption, there's cybersecurity issues, there's talent crunch. You know, how do we solve for this talent crunch? You know, there's probably a higher probability of finding an alien than finding a hidden continent under the ocean right now, right? So we can't solve for these things. And as a result, I think that is where autonomous enterprise, the concept of it, starts to make more sense, because there's no alternative. That's a trigger. We wouldn't have become autonomous just by, you know, our own volition. Because Pega is saying it and it sounds sexy, so let's become autonomous, right? There needs to be a trigger, and I think the trigger is, right now, there's a bloody war going on in our world, right? We need more and more people. It's not about replacing people. It's about how do you accelerate in your businesses today? And there's no other way. I can't think of another way, you know? And that's why we came up with this thing. I think we are living in a digital dichotomy today. You know, on one hand, there is a slowdown that's happening. You know, every quarter all of us are listening to the big R word, right? Is the US economy gonna grow by 1.1% or is it gonna be minus 1.1%? You know, I was talking about all the macroeconomic issues. In fact, we did some research where we reached out to 600 Global 2000 enterprises. In 2022, these 600 enterprises were projecting like almost 11% increase in IT budgets. When we reached out this quarter, that is a 3% increase. So, budgets are shrinking, right? And as I mentioned, the talent crunch is not going anywhere. So there is a slowdown. Whether we like to believe it or not, there is a macroeconomic slowdown that's impacting your CFOs, your CIOs, your own budgets, everything. But at the same time, there's a big hurry to innovate. Everybody wants to get transformed as of yesterday. You know, there is a big hurry along with a big slowdown, right? Digital is no longer some sci-fi that's gonna happen in three or four years. In this room, can you tell me one transformation which is not digital? I can't think of any, right? So why do we keep using this adjective, digital, in front of everything? It's just there. We need to transform digitally. It's essential for survival. I think its model is a great example of, you know, you need just not technology, but you need to solve the people equation, you need to solve the process debt that you have in your organizations. You need to figure out what's the data that you need. You need to figure out your culture. And that's the real transformation that we need. But at the same time, I think you need to find ecosystems. You need to collaborate more, right? If you look at it, every industry is trying to change their business models today, right? Every CPG company wants to go direct to consumer. So what is CPG and what is retail? I don't know. Where do you put batteries? Is it a oil and gas industry? Is it an automotive industry? Frankly, who cares, right? But things are changing very, very rapidly on one hand, but there is a slowdown on the other hand. And I think that's the dichotomy that every C-level leader that I talk to faces. And I think the only way to get out of that is having this autonomous mindset. Is how do you do a lot more with a lot less? And you need that autonomous mindset to be able to do that. This is what we call the three horizons, right? Let me explain the three horizons. I think Digital is horizon one, as I was just explaining. You know, digital is no longer some sci-fi that's gonna happen. You know, it's right here, right now. It's essential for survival. Horizon two is what we call the OneOffice. And OneOffice is, you need to have, you know, your front, middle, and back aligned. In today's world, you can't say finance is a back office. You know, I subscribe to my telecom provider who has good billing. You know, finance is absolutely impacting CX. And then the third horizon is OneEcosystem, which is what I was talking about. You know, I was talking to the chief digital officer for UnitedHealthcare, I think the top five companies from a market cap perspective. And you know what he's working on the most right now? He's working on how does UnitedHealthcare partner with Walmart to create new value propositions, right? So, companies are trying to figure out what is that ecosystem that can come together to create new sources of value. And I think if you look at the blue bars over there, you know, obviously, everybody's focused on digital, right? That's the buzzword. We keep saying digital, digital, digital is front of everything. But if you start to ask enterprises and start to explain this and say, "What is gonna be the innovation focus in the next two or three years?" It starts to shift, right? If you look at those yellow or orange. I don't know what color that is. Orange, let's call it orange. You know, that starts to shift. And if you want to move towards that OneOffice, OneEcosystem, you need to start talking about all the stuff that Ken was talking about, right? You need some AI, you need some automation, you need to start thinking of having an autonomous mindset. One of the myths that I wanna... You know, to be frank, the reason why I don't like the word autonomous is because the first reaction that people have when they hear the word autonomous, is it's gonna be an enterprise without people, right? It's gonna be, you know, "Let's do everything without people." And I think that's not what it means. All autonomous means is, you know, how do we get that hockey stick curve for our enterprises in today's world, you know? And you need that autonomous mindset, you know? And I'll give you one of the best examples there is, is Amazon, right? Has anybody visited an Amazon warehouse? Nobody? Okay, then I can make up stories, okay. So then if you go to Amazon workhouse, that is what comes closest to autonomous in my mind, right? Everything is flowing smoothly. It's very complicated. They're picking up the smallest of SKUs, and things are moving. And it's a man machine sort of happening in tandem very beautifully, and synchronized. But if you look at their man to machine ratio, and it's actually a published number if you look at their SEC filings, for the last 10 years, it's been one is to three. It has not changed. One machine for three people. That's been the ratio. Both have increased dramatically, right? Look at Amazon, the number of people that they employ, and the number of machines. And I'm not talking about software machines here, I'm talking about hardware, but still, it's sort of the same concept. So this myth that we have that autonomous means, you know, zero people, and everything will be done automatically, is just BS, right? And I think autonomous is, you know, how do you drive that generative growth that everybody's looking for in today's world. You just can't keep throwing bodies at it. You know, that's not gonna be the answer to it. You need to think of it very creatively. I won't go through this data circle, this cycle. But I think there are three things that come to my mind. I think data is your strategy today. You know, you need to get a hold of your data. Automation is almost like a discipline. Automation is not a thing that you do, right? Automation is just built into. How can you automate your daily lives to the extent possible, because everybody needs a work-life balance. And then AI is the refinement. AI is the exception processing. You know, that's what autonomous means to me, is you look at your data, you automate whatever you can, right, the boring, mundane, stupid stuff that we have to do, and use AI to refine it. But you'll always have people in the loop. The whole point is, how can you take decisions very, very fast? Because this world is changing very fast. Now, I feel this research, which was done three months back, is old and outdated, right? Because, you know, when we did this, generative AI wasn't a thing, Ken, right? So, it's perhaps useless. But that's how fast the world is moving. And how do you take decisions in that fast-moving world, is what autonomous is. The biggest issue that we have is the legacy dragons that we all have, you know? The legacy, you know, sunk costs, technology, debt, whatever you call it. And we reached out to about 500 Global 2000 enterprise executives, and as you can see, extending the life of legacy systems is pretty big as a challenge. And that's where I think things like low code, et cetera... You know, RPA came out as a breath of fresh air, 10 years back. In fact, HFS was the one who introduced RPA to the world. We called it Robotistan, as the cheapest destination for offshoring. And then the economist and others picked it up, and we suddenly had RPA becoming a big, big thing. And then seven years later we said, "RPA is dead." But the reason is, RPA alone cannot solve for this. RPA is a Band-Aid to your legacy systems. It is brittle. It'll break. And we need a more permanent solution than just, you know, putting a Band-Aid on it. It needs to be self-healing underneath it. The good news is, people are, you know, taking some initiatives. If you look at that same set of respondents, people are investing in improving automation of their processes. People are figuring out how do we respond to consumer shifts. I think this apps modernization around cloud is perhaps the one sort of... I'm generally a very cynical person, but that fourth bullet is what gives me some hope, right? That we are not just talking about cloud migrations, we are talking about modernizing our applications landscape around cloud, or which is sort of, we are fixing that legacy, those legacy dragons. That gives me some hope, at least. I think the other thing that's important is you are not in this alone. I think this whole... You need to use your services partners, your technology partners, your consulting partners, your academicians, you know? You need to build an ecosystem around you to solve for this thing. And I think when you've looked at partners, you know, the purple charts here say, "What do you use partners for?" And again, the orange-ish chart bars here say, "What's gonna be the focus for partnerships in the next two or three years?" And I think today it's all about cost and efficiency, right? We keep using, whether it's an Infosys or an Accenture, or whoever you like to work with, we just squeezing them for more and more cost reductions. And I'm telling you, every lemon will run out of a juice. You know, it's just not possible to keep squeezing the lemon and keep extracting more juice. You've gotta figure out how do you drive new sources of value leveraging these guys and gals, right? And I think that's another heartening thing that we are learning from this study. But you're not in this alone. And I won't go through this. This is a complicated slide, because I do wanna leave some room because it's an intimate crowd to have some chatter. This is an iterative process. This autonomous is not something that will happen and you're done with it. One of my favorite books is this book called "The Infinite Games." It's a very old book. It was written by a religious scholar. His name was James Carse. And I think it's been recently made more popular by Simon Sinek. Anybody's heard of that "Infinite Games"? I would say, you know, it's very cheap on Amazon, so just take a look at it. But it's fantastic. And it says there are two kinds of games in this world. There's finite games and there is infinite games. Finite game is, you know, a tennis match, or a soccer, or a football, or a cricket or whatever. Where there are set rules, you know, there's a start, a middle, and a finish. You know who your opponents are. They don't change. And there's a winner and a loser in that. Infinite games are completely the opposite, you know? You don't have set rules, the rules keep changing. The opponents keep changing. You'd never start or finish, you know, it just keeps going on and on and on. And that's what a lot of gaming developers, right? If you see your kids, they're just hooked onto these games because they just keep going on. They're just not finished. But that's what businesses are as well. You know, you can't say that, you know, "Now that I have 5% market share, I'm done." You know, somebody else will come. You know, the rules will keep changing. New regulations will come in. And you need to think of it as almost like an infinite loop. And that's what this picture is trying to represent very badly. But it is trying to do that. Then you think of autonomous, you need to think of data, you need to think of interactions, you need to think of processes, you need to think of AI, you need to think of automation, you need to think of your mindset, you need to think of so many things, and you need to keep evolving, keep churning, keep churning, keep churning. And that is why you need help from data generative AI, you know, automation, folks like Pega and others, because you just can't keep throwing bodies at it, you know? That's not the answer to this. So, last, how do you start, right? I think of it about experience, whether it's employee experience or customer experience. Take small bites at it, right? Don't try and change the world. Don't try and solve for world hunger. But try and look from front to back, right? Look for interactions that start from front to back. Don't, you know... Is anybody from SAP here? I hope not. Okay. So, SAP F'd up our world, because we organized our organizations based on SAP modules. Here's a AP module, here's a AR module, here's a, you know, whatever module. That's not how business is run. You need to look at data flows, right? Where is customer data flowing from start to finish? You need to look at it. Where's employee data flowing? Where's monetary data flowing? And that's what end-to-end is. And I think you need to get out of that siloed mindset. I think don't put Band-Aids on it, you know? Think of how can you simplify processes, you know? Eliminate some things. You know, in my previous job, I used to work for a $25 billion biotech firm. It took us six months to get a approval for implementing a RPA bot. What's the point when in six months, RPA was not even a thing? You know, there something else was coming in. Define a COE structure. You know, identify two or three people in your organization who can be champion for this. You know, build an infrastructure around that. You know, even if you fail, you'll have at least two or three people who are trained in some cool new technology, right? So what's the harm? And monitor this thing, you know? Establish a management monitoring system. The governance is very, very important because it's not one and done. It needs to keep churning. And finally, market the hell out of it. You know, talk to people. You know, showcase your successes however little. You know, you need to get excitement going about this thing. We all need to be marketing and sales professionals in our jobs today. That's it. I think that's it. Would love to get some questions, responses. Was this useful, crap, whatever?

- If you have questions, you can come up to the mics on either side, we're happy to take questions. Or you can come up here afterwards if you wanna ask us in person, so...

- Or shout.

- Really? Nothing? All right. Well, we thank you all very much. Anybody who has questions can come up as I said, and appreciate your time. Thank you.


Assunto: Autonomous Enterprise Assunto: PegaWorld Área do produto: Automação inteligente

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