Lukas Egger: Hello and welcome to Process Transformers, the podcast that talks about business transformation at the intersection of processes and AI.
Lukas Egger: For those who have listened before, welcome back.
Lukas Egger: If you're new to the show, thanks for tuning in.
Lukas Egger: My name is Lukas Egger.
Lukas Egger: I'm the head of innovation at SAP Signavio, and I'll be a host for today's episode titled Innovation Through Processes, Rethinking Transformation in the Age of AI.
Lukas Egger: And I'm honored to introduce today's guest.
Lukas Egger: Gero Decker, a pioneering voice in business transformation and the co-founder and general manager of SAP Signavio. Welcome to the show. Thank you for having me.
Gero Decker: Great to talk to you today, Lukas, and welcome everybody out there.
Lukas Egger: Wonderful. So our podcast is literally called Process Transformers. So let's start with that. What's your personal perspective on business processes today, compared to when you started, because you have been in the business for decades?
Lukas Egger: And it begs the question, what are you still excited about?
Gero Decker: So when I look back to how I even got into the process transformation space, this started with a project.
Gero Decker: I was a consultant with a large telco in Germany, and they were rolling out a new product.
Gero Decker: It combined DSL, it combined internet connectivity, and it combined TV access, a product that was new to the market and that was new for the telco. It took weeks for a customer to go live from ordering the subscription all the way to being able to watch TV and go online.
Gero Decker: Most people canceled their subscription even before going live. It was a disaster. So The consulting team and everybody gathering in that project to the rescue, and it was amazing to find how much complexity is in there, how many people involved, how many systems. We counted 120 systems involved from technology.
Gero Decker: submitting the order all the way to going live. We counted eight business units involved on that chain. And we couldn't find a single person who felt responsible for making this end-to-end chain work. We had to go all the way to the CEO of a company with hundreds of thousands of employees to say, there are things that don't match. And it was amazing to see how people didn't understand how their actions the things that they contributed to the process had serious downstream effects.
Gero Decker: If they fill the field incorrectly when submitting the order in the shop, it meant that field technicians, for example, had to go out to the customer three times more than necessary.
Gero Decker: So business process as a perspective and...
Gero Decker: end-to-end view to try to make all of these puzzle pieces fit and one step click with the others.
Gero Decker: This was the real beauty and the real relevation for me. And this is where I fell in love with the whole topic of business process. But if I compare how we did it back then, we had to interview hundreds of people to identify what was going on.
Gero Decker: but also to identify what were the things where people had completely wrong assumptions about how the process would continue.
Gero Decker: Today, 15 years later, we're much smarter because we tap into data, we look into systems.
Gero Decker: We can reverse engineer some of the things that are happening.
Gero Decker: So driving insights, it's so much faster today.
Gero Decker: So the amount of clarity or the amount of visibility that we find in organizations when using the right approaches and tools is so much bigger.
Gero Decker: And I guess we talk about AI in this podcast as well, which will put it all on a completely different level.
Lukas Egger: Before we jump in there, you mentioned something that I think still rings true for a lot of people.
Lukas Egger: We have high hopes for any change process, yet they still seem to fail on a rather consistent basis.
Lukas Egger: So why are we still under-delivering?
Lukas Egger: What is holding businesses back?
Lukas Egger: You gave a good example in the past, but...
Lukas Egger: What's today the issue that not every project to transform a process is successful?
Gero Decker: Well, there's a number of ingredients that all need to come together.
Gero Decker: One is visibility and tools and access to the right level of information.
Gero Decker: But even more importantly, it is the willingness to change, the willingness to challenge yourself and to accept that the way how you've done things in the past might not be optimal, that there are fundamentally different and better ways to go about what you need to do.
Gero Decker: But also, the priority it has in organizations, the level of funding, the level of attention it gets in the broader organization, this is often something where companies can improve on.
Gero Decker: So it's a number of things that come together.
Gero Decker: It's the people involved.
Gero Decker: It's the method.
Gero Decker: It's the tools.
Gero Decker: It's the budgets.
Gero Decker: It's the mandate.
Gero Decker: But it's also the success stories and how you communicate that to the organization and you drive excitement and momentum for other people to follow those footsteps and repeat those early wins.
Gero Decker: There's a number of things that need to come together, right?
Gero Decker: So it's really not just one thing or one button that you need to press, but it's a commitment that you need to make as an organization if you want to change, if you want to transform, and if you want to become better.
Lukas Egger: now everybody wants to become better and these days it feels like the conversations naturally gravitate towards oh the next thing to get better is we deploy ai it will be great but what you just described are things that could haunt us regardless of whether it's an ai project or not so i guess I'm trying to segue into the conversation with AI. Are you bullish on AI, despite what you just mentioned in terms of what the struggles still are?
Gero Decker: Well, the potential is massive, but I still remember those old Dilbert comics when the cloud arrived, right? And the promise of the cloud of cloud technology was, that from now on, everything is simple.
Gero Decker: So I still remember these spaghetti processes that were there in the old world, and then suddenly they were put into the cloud, and suddenly Dilbert proclaims everything is solved.
Gero Decker: So I feel reminded of that now that we talk about AI, that AI to the rescue, it will make sense of everything, it will automatically solve everything.
Gero Decker: And I just have to push one button and everything's done.
Gero Decker: So many of the principles that I shared are still true as long as we have many of the structures in companies that we have today, that we have decisions that need to be taken by people, that there is financial constraints that you're under, that there's dependencies that you need to respect in your IT landscape.
Gero Decker: That there are many things that contribute to whether something is easy or whether something is hard. An AI can connect the dots. An AI can uncover things that you didn't know. An AI can suggest solutions to you. An AI can even take over some of the work.
Gero Decker: that you need to do, but still it needs to fit into that picture. So it's not like a switch that you flip, that there is this old world where everything is complicated and impossible. And suddenly there's this new world where AI is switched on and you don't need to change anything but just switching on AI and the problem is solved. This is not the case. But let's dive into AI, I guess, and what some of the promises are. Should we go straight to agents or should we, what angle should we take, Lucas?
Lukas Egger: That's a good question. Well, agents are currently at a fever pitch of, I would say, like the hype cycle. But maybe let's start with a more general discussion, because in the past Being efficient and being on top of your business processes was definitely like a competitive advantage.
Lukas Egger: Now, I think to be true to the conversation, we first need to maybe figure out what will be so impactful about AI.
Lukas Egger: So what is it that you see, whether it's agents or AI or whatever you want to call it, That could be like this differentiating factor that companies are excited about and that really warrants all of the investments.
Lukas Egger: What is it that you see and is that the same that customers see or is there a discrepancy?
Gero Decker: So the one thing that most people look at when deploying AI is efficiency.
Gero Decker: Right. So they see all of the things that they do today. They see hundreds and thousands of people doing certain tasks and they say, well, if a machine could take over the same amount of tasks or at least half of it, how great would that be? Because it would be an immediate impact to my bottom line. Right. So the efficiency gain is in.
Gero Decker: Age-old principle for automation and technology in general that you think you just want to do the same going forward, but with less input and less cost.
Gero Decker: Great, let's do it.
Gero Decker: But the promise of AI is much greater.
Gero Decker: It goes beyond removing friction and it goes beyond removing manual work and introducing automation.
Gero Decker: But it also means that it opens up new possibilities and opportunities that you might not have had before.
Gero Decker: So first of all, one of the great levers that customers can have and some have with AI is that they can democratize certain pieces within their business. So certain tasks don't require an expert anymore, or that many experts.
Gero Decker: much of the task can be done with AI.
Gero Decker: So it's much easier to do and a lot more people can be involved.
Gero Decker: So, for example, if you look at social media, most of the social media posts that companies put out these days are actually written by AI.
Gero Decker: But what this leverages is that it becomes so much easier for companies to communicate.
Gero Decker: So you can enable people who didn't have a voice, who didn't have a say suddenly, and it becomes so much easier for them to participate in.
Gero Decker: in the conversation, right?
Gero Decker: So democratization and bringing in kind of less need for high skills or scarce skills to do certain tasks is an opportunity in and of itself.
Gero Decker: But there's also this knob that you ideally want to turn.
Gero Decker: So sometimes if you optimize things, with AI up to a certain point, suddenly entirely new things are possible.
Gero Decker: My favorite example is the recommendations that you find on e-commerce websites, right?
Gero Decker: So customers like you also bought this and this, right?
Gero Decker: Don't you want to buy?
Gero Decker: One click, add it to your shopping cart.
Gero Decker: We all know this, right?
Gero Decker: And sometimes the recommendations are pretty good.
Gero Decker: But now imagine Amazon can tune and optimize recommendations so much.
Gero Decker: that they can predict with 95 or 98% accuracy what product you want to buy at a certain point in time.
Gero Decker: You know what you can do?
Gero Decker: You can completely reinvent the process and say, let's skip the ordering step.
Gero Decker: We will just deliver because we know what the customer wants.
Gero Decker: We just sent the package to the customer without the customer having ordered it.
Gero Decker: And then at the doorstop, the customer can say, oh, thank you.
Gero Decker: I actually wanted it.
Gero Decker: Great.
Gero Decker: Thank you.
Gero Decker: Or it can say, oh, I didn't order that.
Gero Decker: I didn't want to go back.
Gero Decker: These are things where you turn the knob with AI so much that suddenly things become possible that were not possible before, right?
Gero Decker: But the biggest, I think that the biggest thing these days that companies find is the acceleration.
Gero Decker: That you can develop new capabilities, that you can introduce change, that you can experiment with things, that you can change the organization so much faster because AI supports you in doing so.
Lukas Egger: I mean, the obvious first reaction is excitement, right?
Lukas Egger: And that's what we see in the markets.
Lukas Egger: Everybody's like, oh, I want to be part of that.
Lukas Egger: But now how you explained it, it also sounds hard because AI is a different beast.
Lukas Egger: It can unlock new functionalities that we're not used to and will have to change more than we had to change before, which arguably was not easy.
Lukas Egger: So do you think overall business transformation or working with processes will get easier or harder?
Lukas Egger: Do you think it...
Lukas Egger: the democratization and all the other stuff will outweigh the challenges that companies will face by getting it to work for them.
Gero Decker: Look, we all know the chat GPT effect, right? You need to write an email or you need to, you know, send best wishes for a friend's wedding, right? And chat GPT to the rescue, and suddenly it becomes so easy to do these types of tasks. So even if, you know, deploying AI turns out to be hard and turns out to uncover all kinds of new challenges, the promises or the idea is there, the hope is there, that AI can help deploy AI.
Gero Decker: So everything that is introduced as a new challenge everything that appears, the assumption is, will become to a certain degree easier through AI.
Gero Decker: So my assumption is, even if you inherit new challenges, the net effect is it's going to be easier to change. And those companies who are afraid or who say, well, we don't need to be the first ones, we can wait a year or two and see what the others do, they will soon see that they fall behind because changing has become so much easier with AI.
Lukas Egger: And do you see, you have a lot of conversations with business leader and people who are actually in charge.
Lukas Egger: Do you see that there is a convergence of these topics?
Lukas Egger: Do business leader feel the same about the challenges or do you see like a divergence of, because there are so many topics, right?
Lukas Egger: There's AI, there's agents.
Lukas Egger: There are so many things one could focus on and businesses also feel squeezed, right? It feels like the competitive pressure is only getting bigger. What's your, I guess, also unique perspective of being able to talk to people who are actually in charge of creating change?
Lukas Egger: Yeah.
Gero Decker: Look, so I see that all the habits repeat themselves into the future.
Gero Decker: Certain rituals or mindsets that you have organizations that extend into the future.
Gero Decker: If you're an organization that was trained to look for efficiencies, for cost reduction, for takeout of complexity and so forth, they will see AI to solve exactly that challenge for them.
Gero Decker: If you have companies who have a problem with transferring skills or knowledge within the organization, they will see AI as the rescue for exactly that challenge that they had.
Gero Decker: And if there are companies who say, well, we maxed out on the things that we do today, we need to be creative.
Gero Decker: to find adjacencies or growth areas for a company to expand, they will see AI as the tool to do exactly that, right? So what I haven't seen yet is that AI suddenly changes the perspective entirely of what you want to do with your business. It is a tool for the purpose or for the challenge that you already had yesterday, but it's a very good tool.
Gero Decker: And it's very powerful and it solves a lot of challenges. Companies that drown in IT complexity, for instance, well, of course, they see AI as a phenomenal tool to do all of the plumbing for them, right? To be able to stitch data together in a much easier way or to build applications in a much faster way than they ever could.
Gero Decker: because AI, with all of its statistics and heuristics, can connect the dots much faster and more efficiently than people.
Gero Decker: But those on the creative end who say, well, I feel there's wide open opportunity for me as a company, what else could I do?
Gero Decker: Well, they will use Gen.AI and its ability to hallucinate and generate ideas to say, here's everything that we do. Here's everything that we own. Can you combine it in novel ways? Or can you connect it to something that you've observed out there to give me ideas what else I could do? So your innovation funnel suddenly becomes five times, 10 times bigger.
Gero Decker: Compared to just asking smart people about what they think or what the ideas are that they have, right? So depending on which direction you want to move into, AI is a phenomenal tool.
Lukas Egger: I love that perspective. And it goes back to maybe the old adage, with a hammer in your hand, the world is nails and not nails, right?
Lukas Egger: But now I'm curious because your personal perspective, what is it that keeps you curious?
Lukas Egger: Like, are you excited about the efficiency that we will drive in the near term?
And that's amazing.
Or are there certain aspects and...
whether it's agents or some parts about what AI can do, which was never possible, whether it's emotions, whether it's like unique kind of processes or whatever it might be.
Is there anything that you feel like coming back to that you are drawn to?
Gero Decker: Look, I'm a software engineer by background and I'm a product person, right? So all my life I've done nothing else than thinking about what type of software products can we build out there. And what you can build in terms of product has dramatically changed over the last two to three years.
Gero Decker: Until three years ago, you needed to have a very good understanding of what you wanted to do. And then you had to have, you needed to do all of the translation yourself, all the way to the technical level, to make that solution come to life that you wished for.
Gero Decker: So now with Gen AI, this is expedited, and you can sometimes take 60, 70, 80, 90% out, and this makes you so much faster, but it also allows you to build products that can take over a lot more.
Gero Decker: that only very skilled people could do previously.
Gero Decker: So maybe now is a good time to move into the area of agents.
Gero Decker: So I come from academia and multi-agent systems, autonomous agents.
Gero Decker: They were a concept for 20, 30 years out there in academia, like a dream of dealing with complexity, giving certain autonomous units a task and a goal and let them figure out how they best solve it.
Gero Decker: But there were no means to actually program these agents in a smart way.
Gero Decker: So they just ended up taking inputs and producing always the outputs.
Gero Decker: And you had to program all of the logic of that agent.
Gero Decker: So they were not doing anything surprising.
Gero Decker: They were not doing anything sophisticated.
Gero Decker: They could calculate A plus B equals C.
Gero Decker: Right. But not much more. So now with Gen AI, you can build agents that are vastly smarter that can take over entire tasks. You can give them a challenge and say, I have a business trip coming up. Can you please do everything required?
Gero Decker: to make that trip worthwhile and make it smooth for me.
Gero Decker: And the system will be able to go ahead and seek all of the context.
Gero Decker: Ah, okay, so you're going to a conference.
Gero Decker: It starts on that day.
Gero Decker: It ends on that day.
Gero Decker: It's actually in a nice location.
Gero Decker: And I actually understand from your previous behavior that you might want to add half a day to do a little bit of sightseeing on that.
Gero Decker: are and you try to travel in a sustainable way this is what you've done in the past so I prefer a train ride versus a plane and I give you all of the options right and I try to anticipate everything for you and decompose and do all of the steps required to make this worthwhile I even enable an out of office email because I've seen that you've done that in the past right this is an example for how an agent can take over responsibility or can take over quite complex tasks end-to-end and do all of the things that are required along the way. And they can hyper-personalize. They can understand the context very deeply in which they sit, in which they live, in which a task exists. So they can change and adapt very, very quickly to the specific context that they're in. But here is the interesting thing.
Gero Decker: So if you have a system of agents or you have many agents doing all kinds of stuff, it's like having an organization with many different people, right?
Gero Decker: And in fact, there will be a coexistence of these agents that are able to take over more and more complex tasks themselves.
Gero Decker: sitting and working alongside and with humans around them.
Gero Decker: So now the question is, how do you translate the strategy or the objectives of your company to what all of these people and agents are doing on the ground?
Gero Decker: You know what the trick was that has been applied for decades?
Gero Decker: business process, right?
Gero Decker: You need a viewpoint, you need a perspective that allows you, that gives you an organizing principle so that all of these constituents can work together, that all of the handovers work, that expectations are clear, that it's clear what are the two to five KPIs for a given process to estimate whether things are running in order, right?
Gero Decker: What are the boundary conditions for that?
Gero Decker: Right? What are the decision points that are there? And how can we best split up work so that we get the job done? Right? Humans are creative and they find novel ways. And of course, they provide their feedback and say, this process can be improved. Why don't we eliminate that step? Or why don't we create a third option? The same thing agents will do. They will say, why do you even give me that task? I found nobody's actually using what I give you back.
Gero Decker: Or here's another option, and maybe you want to develop a new skill or onboard something else to get that task more done.
Gero Decker: But in the end, it's all business process management.
Gero Decker: We've done it for many, many decades, right?
Gero Decker: It's trying to understand how all of these things work together that are inside of my organization, right?
Gero Decker: but also the flows that go across organizations.
Gero Decker: And how can we best organize that so that the outcome is great every time?
Gero Decker: So this is the exciting piece of our business process management in the world of agents, that it has at least the same relevance like it had before in human-centric organizations or where humans were the only ones who performed work.
Gero Decker: Now with the age of agents, where it's so much easier to deploy an additional 1,000 agents, it's not so easy to deploy an additional 1,000 colleagues to a task, but it's very easy to deploy another 1,000 agents that you onboard.
Gero Decker: Certain limitations are removed, so the degree of understanding is amplified.
Gero Decker: The need for understanding is amplified.
Gero Decker: And also the governance and the steering of this all becomes even more important because this whole system is now able to evolve much faster than we've known in the past.
Gero Decker: So this is what I'm really, really excited about, that when you discover that something that you've done for 20 years is still very relevant or is even more relevant as you go into the future.
Lukas Egger: Yeah, I would say you gave a very good argument why it should be even more relevant. Yet at the same time, whenever we're facing like a hype, there is disillusionment, there is a period where it gets overhyped and then needs to pick itself up.
Lukas Egger: Now, do you think we have already all of the parts for agents to be successful? Or do you believe that in terms of the process management, what you said is still relevant or relevant anew, that there also needs to be an innovation like how we manage processes?
Lukas Egger: So essentially, Is it straight cruising or do we need fundamental innovation in what you laid out, right?
Lukas Egger: Understanding my business, seeing everything, calculating values, impacts, and so forth.
Lukas Egger: Is everything there or do we need parts?
Gero Decker: Look, I like to compare this with technology waves that come in the past. One big wave that came was mobile, right? So suddenly everybody had a smartphone in their hand. And everybody, I think, and most likely remember the moment where for the first time you zoom into Google Maps with two fingers.
Gero Decker: It's a magic moment, something that you simply couldn't do before.
Gero Decker: It was only possible because of the device of its form factor of how it was built and how it was ubiquitous with you all the time.
Gero Decker: So very soon, once people saw the first apps, they asked themselves, well, I have this other task or I have this other thing to do.
Gero Decker: Why isn't there an app for that?
Gero Decker: There should be an app for that. So there was this, first of all, very quick understanding of the potential that everything, potentially everything that you do can be done on the mobile phone much faster, much smoother, which is two clicks. But Still until this point, I mean, when was the iPhone launch? It was 20 years ago, probably, when it was launched with the apps and everything. So still new apps come where you say, wow, this is doing something that I didn't expect an app to do before. Wow, there's something cool that just came around. So it's a gradual process until it's all there.
Gero Decker: The wonderful thing is, similar to mobile apps, now we have this moment where people can't imagine everything.
Gero Decker: They've used ChatGVT or other tools or image generation tools and so on and so forth.
Gero Decker: And they say, wow, this is so phenomenal.
Gero Decker: And suddenly you can imagine all of these use cases, all of these things that Gen.AI can do for you.
Gero Decker: And you're even disappointed if the system doesn't do it for you, right? So you open up an application and you still need to do all kinds of manual stuff. And you still have to know it in detail to work yourself through it and complete the task yourself. And you kind of just tell the system, solve this for me? Isn't this what Gen AI is for?
Gero Decker: it's going to take time, it's going to take years until, let's say, 80%, 90% of all of the usual things that can be solved through Gen AI will actually be there and will be readily available, right?
Gero Decker: Yeah.
Gero Decker: But this is just the first step.
Gero Decker: So we've seen with mobile apps suddenly your behavior changes a lot, right? Suddenly something like social networks become ubiquitous because everybody can take pictures all the time. Suddenly a significant part of your life goes into that and you start to define yourself as how you are perceived within that. How crazy is that? That you change your perception of your identity because there is new technology and that allow you to interact with people in a novel way.
Gero Decker: And the same will happen with Gen AI.
Gero Decker: So can we all predict it?
Gero Decker: You know, when the iPhone was launched, could people predict that the power of Instagram and TikTok on the world and how they can change elections and how they can change how people see themselves?
Gero Decker: I guess not.
Gero Decker: And this is the interesting path now for the coming years, where we will have to discover all of these things, all of these side effects that might be unexpected that come through Gen AI.
Gero Decker: So what are the parts that are missing?
Gero Decker: You know, I wish I had the crystal ball to see it all.
Gero Decker: I don't.
Gero Decker: It's going to be a gradual process.
Gero Decker: But what's different this time is that the speed is higher, right?
Gero Decker: So in the past, you could go offline for like three months and still...
Gero Decker: you didn't miss a lot, right?
Gero Decker: Or you could even go offline for six months or nine months and you could still catch up very quickly.
Gero Decker: Now, if you look at AI and what's possible, and if you don't look for three months, it's like, oh, it's like time travel.
Gero Decker: Suddenly you're in a different century.
Gero Decker: This is how it feels.
Gero Decker: So it challenges people in their ability to adapt and absorb all of the new stuff that is there.
Gero Decker: So the one thing, if you ask me for one thing that people require, more than ever, more than before, is the willingness and the ability to absorb change, drive change and transformation and make this the main muscle for yourself and your organization.
Lukas Egger: So adaptability as a superpower.
Lukas Egger: But while you were explaining very beautifully what is coming, I realized that a lot of the examples you brought were from a B2C perspective, from a very personal perspective.
Lukas Egger: I kind of want to throw a question out there because we're always talking about processes from a very business-centric perspective, which it always has been.
Lukas Egger: But agent technology could as easily be perceived as very B2C, just like mobile, right?
Lukas Egger: Do you believe that process management in the end could end up as a B2C product instead of a purely B2B thing?
Gero Decker: Look, with most technology, B2C, the consumer world is the first one to adopt it at scale, right? Because the cycles are shorter. You can make a decision, you see something today, and you say, I want to have it. I will take half of this month's paycheck to get this piece of technology because it is so cool.
Gero Decker: This is the beauty of the consumer world, that decisions can be made a lot faster, and the complexity is typically less because the products only need to take care of that one person.
Gero Decker: And complexity is higher once you go to businesses because you need to factor in all kinds of things and all kinds of requirements.
Gero Decker: But it's a natural path that first...
Gero Decker: You do things on the B2C world, and then you transport it to organizations. I mean, your question is interesting because it asks the question, will businesses still exist in the future? Or will we organize the world in a very different way? This question comes and goes, right? Think about the gig economy or other ways of organizing the economy. Look, After all of the technology, after all of the things that have happened the last couple of decades, companies are still the organizing principle for a lot that's happening in this world, for this economy, because it's a nice way to deal with complexity and to provide efficiency at scale and make things accessible to a very large number of people.
Gero Decker: And there with accelerating the usage and the potential of technology that exists.
Gero Decker: So business processes, they were born in the business world.
Gero Decker: Why?
Gero Decker: Because it's exactly back to my example of the telcos.
Gero Decker: It's about organizing things that are inherently distributed, that are inherently complex, that inherently have many people involved, many systems, tons of different types of data that all need to come together to produce an outcome.
Gero Decker: In the private world, yes, of course, you will see things that will help you organize your day, that will help you develop the right routines, that will take over tasks for you. We always see that. But business process management inherently, I think, is a topic that is applied by organizations.
Lukas Egger: It makes perfect sense. So you're saying, regardless of how much you push the hype, the most likely scenario will be coexistence of the new value propositions created by AI, not a complete reinvention.
Lukas Egger: And because of it, a smooth transition if you focus on processes, which sounds like a very encouraging message.
Gero Decker: It sounds a little too simple, I think, how you phrase it, because change is difficult, right?
Gero Decker: And smooth sailing is smooth.
Gero Decker: It's probably the wrong word because we talk about disruptive technology here that is turning certain things on its head, that is taking people by their pride, things that they have learned for 30, 40 years, and suddenly you have a machine that can do 70% of that twice as good as you can.
Gero Decker: Man, that's a change that is hard to digest.
Gero Decker: So smooth, I wouldn't dare say.
Gero Decker: There is a trick to all of this.
Gero Decker: And this is the ability to change, to adopt, to be willing, and to be capable of deploying change to an organization.
Gero Decker: But.
Lukas Egger: Yeah.
Lukas Egger: You caught me there because I was trying to set up the question.
Lukas Egger: If everything sounds smooth, I wanted to ask you what are the really bold parts or the bold predictions that you have?
Lukas Egger: because you have incredible insights in how it has been in the past.
Lukas Egger: And I'm sure there is a couple of things that you're excited about that might even sound too big right now for people who work in the field of strategy and so forth.
Lukas Egger: So I was curious to ask, what are your really bold predictions for the future?
Gero Decker: So one prediction is we're moving to a frictionless world. Okay. And I give you examples of frictionless already from the present and from the past. If you look at how you can buy stuff, the degree how easy it has become to buy stuff is, You know, at any time of the day, wherever you are in the world, a phenomenal choice, a phenomenal quality with high efficiency is just mind-blowing. And the same effect will happen to all kinds of things that we have around us.
Gero Decker: we will have so many people and we will have AI that will remove all of the friction points out there. That in the end, everything that can be done with a click of a button on your mobile phone will be done with a click of a button on the mobile phone. This is my one bold prediction.
Gero Decker: And of course, the companies that are the fastest to get there will win. But There's a world beyond that. And that would be my prediction number two. My prediction number two is that those companies will see the biggest success that not only focus on the pain points, the friction points in their business, but that also reserve a certain portion to reinvent themselves and look beyond success.
Gero Decker: what they're currently doing.
Gero Decker: And they see the strengths or assets that they have and turn this into opportunity for them as a company.
Gero Decker: Because frictionless alone will lead to a world where you have a shark tank of companies competing at minimal margin, right?
Gero Decker: Back to my example with buying stuff on the internet, the margins are so thin because everybody has moved in that direction and has made buying stuff frictionless.
Gero Decker: So it's other things that make you win.
Gero Decker: These are things like trust.
Gero Decker: It's things like choice.
Gero Decker: It's things like personalization, intimacy.
Gero Decker: There's many other things that you can optimize for as a company and where you can ask yourself, what can I do?
Gero Decker: Or what are completely new types of offerings that I can bring to market that go beyond what's possible today or even beyond what can be imagined?
Gero Decker: And my third prediction is, We are going to see a distinction between well-performing companies and worst-performing companies.
Gero Decker: And the success of these companies can be measured by two simple metrics.
Gero Decker: metric number one is time to insight and the other metric is time to adapt how fast can companies understand what's going on and make sense of everything that's happening in their business across everything and see the dependencies and how it all works together and draw the right conclusions from that.
Gero Decker: And once you've drawn the right conclusions and you say, I want to act on it, I want to leverage this cool new thing.
Gero Decker: I want to do things differently.
Gero Decker: I want to leave things behind.
Gero Decker: The companies that are able to do that the fastest, they are the ones that will win.
Gero Decker: So three predictions.
Gero Decker: One, a frictionless world.
Gero Decker: I want that, I'm just being selfish here, I want that for myself. But I deeply believe that it's possible, and all of the tools in the world point into that direction. Second, going beyond frictionless is the path to win, and the companies that will see phenomenal growth rates, but that will also see sustainably high margins, are the ones who constantly are able to push the boundaries and are able to reinvent.
Gero Decker: And then third...
Lukas Egger: is the speed with which you can change as the determining factor driven by time to insight and time to adapt.
Lukas Egger: I think it's very powerful, those three parts.
Lukas Egger: And I don't even want to add anything.
Lukas Egger: I just want to Bring us back into the here and now, because we're always interested in, after discussing long-standing changes in the future, what is it that you would love to change in the here and now?
Lukas Egger: Like, if you could instantly transform a process today, which one would it be and why?
Gero Decker: My favorite process, to be disrupted, to be reinvented, to be solved for myself, is taking the kids to bed in the evening. That is consuming so much time. If there is a trick to that process, to free up some more time in the evening with my wife, I would gladly take it.
Lukas Egger: I love that.
Lukas Egger: And maybe that would be then some other conversation about processes that you don't want to optimize, right?
Lukas Egger: That are inherently enjoyable, that are outside of the scope.
Lukas Egger: Thank you so much, Gero, for the insights.
Lukas Egger: They were exceptional.
Gero Decker: Thank you, everyone.
Lukas Egger: And well, with that, Thanks for listening to another episode of Process Transformers.
Lukas Egger: This podcast is brought to you by the dedicated efforts and the hard work of our team.
Lukas Egger: So a really heartfelt thank you to Bezer Katal.
Lukas Egger: Regan Neandoro, Erica Davis, Cecilia Sarkees, Vazi Murad, and Julian Leveneau.
Lukas Egger: If you have questions or comments, email us at processtransformers at sap.com.
Lukas Egger: And until next time, for another transformative conversation.
Lukas Egger: For those who have listened before, welcome back.
Lukas Egger: If you're new to the show, thanks for tuning in.
Lukas Egger: My name is Lukas Egger.
Lukas Egger: I'm the head of innovation at SAP Signavio, and I'll be a host for today's episode titled Innovation Through Processes, Rethinking Transformation in the Age of AI.
Lukas Egger: And I'm honored to introduce today's guest.
Lukas Egger: Gero Decker, a pioneering voice in business transformation and the co-founder and general manager of SAP Signavio. Welcome to the show. Thank you for having me.
Gero Decker: Great to talk to you today, Lukas, and welcome everybody out there.
Lukas Egger: Wonderful. So our podcast is literally called Process Transformers. So let's start with that. What's your personal perspective on business processes today, compared to when you started, because you have been in the business for decades?
Lukas Egger: And it begs the question, what are you still excited about?
Gero Decker: So when I look back to how I even got into the process transformation space, this started with a project.
Gero Decker: I was a consultant with a large telco in Germany, and they were rolling out a new product.
Gero Decker: It combined DSL, it combined internet connectivity, and it combined TV access, a product that was new to the market and that was new for the telco. It took weeks for a customer to go live from ordering the subscription all the way to being able to watch TV and go online.
Gero Decker: Most people canceled their subscription even before going live. It was a disaster. So The consulting team and everybody gathering in that project to the rescue, and it was amazing to find how much complexity is in there, how many people involved, how many systems. We counted 120 systems involved from technology.
Gero Decker: submitting the order all the way to going live. We counted eight business units involved on that chain. And we couldn't find a single person who felt responsible for making this end-to-end chain work. We had to go all the way to the CEO of a company with hundreds of thousands of employees to say, there are things that don't match. And it was amazing to see how people didn't understand how their actions the things that they contributed to the process had serious downstream effects.
Gero Decker: If they fill the field incorrectly when submitting the order in the shop, it meant that field technicians, for example, had to go out to the customer three times more than necessary.
Gero Decker: So business process as a perspective and...
Gero Decker: end-to-end view to try to make all of these puzzle pieces fit and one step click with the others.
Gero Decker: This was the real beauty and the real relevation for me. And this is where I fell in love with the whole topic of business process. But if I compare how we did it back then, we had to interview hundreds of people to identify what was going on.
Gero Decker: but also to identify what were the things where people had completely wrong assumptions about how the process would continue.
Gero Decker: Today, 15 years later, we're much smarter because we tap into data, we look into systems.
Gero Decker: We can reverse engineer some of the things that are happening.
Gero Decker: So driving insights, it's so much faster today.
Gero Decker: So the amount of clarity or the amount of visibility that we find in organizations when using the right approaches and tools is so much bigger.
Gero Decker: And I guess we talk about AI in this podcast as well, which will put it all on a completely different level.
Lukas Egger: Before we jump in there, you mentioned something that I think still rings true for a lot of people.
Lukas Egger: We have high hopes for any change process, yet they still seem to fail on a rather consistent basis.
Lukas Egger: So why are we still under-delivering?
Lukas Egger: What is holding businesses back?
Lukas Egger: You gave a good example in the past, but...
Lukas Egger: What's today the issue that not every project to transform a process is successful?
Gero Decker: Well, there's a number of ingredients that all need to come together.
Gero Decker: One is visibility and tools and access to the right level of information.
Gero Decker: But even more importantly, it is the willingness to change, the willingness to challenge yourself and to accept that the way how you've done things in the past might not be optimal, that there are fundamentally different and better ways to go about what you need to do.
Gero Decker: But also, the priority it has in organizations, the level of funding, the level of attention it gets in the broader organization, this is often something where companies can improve on.
Gero Decker: So it's a number of things that come together.
Gero Decker: It's the people involved.
Gero Decker: It's the method.
Gero Decker: It's the tools.
Gero Decker: It's the budgets.
Gero Decker: It's the mandate.
Gero Decker: But it's also the success stories and how you communicate that to the organization and you drive excitement and momentum for other people to follow those footsteps and repeat those early wins.
Gero Decker: There's a number of things that need to come together, right?
Gero Decker: So it's really not just one thing or one button that you need to press, but it's a commitment that you need to make as an organization if you want to change, if you want to transform, and if you want to become better.
Lukas Egger: now everybody wants to become better and these days it feels like the conversations naturally gravitate towards oh the next thing to get better is we deploy ai it will be great but what you just described are things that could haunt us regardless of whether it's an ai project or not so i guess I'm trying to segue into the conversation with AI. Are you bullish on AI, despite what you just mentioned in terms of what the struggles still are?
Gero Decker: Well, the potential is massive, but I still remember those old Dilbert comics when the cloud arrived, right? And the promise of the cloud of cloud technology was, that from now on, everything is simple.
Gero Decker: So I still remember these spaghetti processes that were there in the old world, and then suddenly they were put into the cloud, and suddenly Dilbert proclaims everything is solved.
Gero Decker: So I feel reminded of that now that we talk about AI, that AI to the rescue, it will make sense of everything, it will automatically solve everything.
Gero Decker: And I just have to push one button and everything's done.
Gero Decker: So many of the principles that I shared are still true as long as we have many of the structures in companies that we have today, that we have decisions that need to be taken by people, that there is financial constraints that you're under, that there's dependencies that you need to respect in your IT landscape.
Gero Decker: That there are many things that contribute to whether something is easy or whether something is hard. An AI can connect the dots. An AI can uncover things that you didn't know. An AI can suggest solutions to you. An AI can even take over some of the work.
Gero Decker: that you need to do, but still it needs to fit into that picture. So it's not like a switch that you flip, that there is this old world where everything is complicated and impossible. And suddenly there's this new world where AI is switched on and you don't need to change anything but just switching on AI and the problem is solved. This is not the case. But let's dive into AI, I guess, and what some of the promises are. Should we go straight to agents or should we, what angle should we take, Lucas?
Lukas Egger: That's a good question. Well, agents are currently at a fever pitch of, I would say, like the hype cycle. But maybe let's start with a more general discussion, because in the past Being efficient and being on top of your business processes was definitely like a competitive advantage.
Lukas Egger: Now, I think to be true to the conversation, we first need to maybe figure out what will be so impactful about AI.
Lukas Egger: So what is it that you see, whether it's agents or AI or whatever you want to call it, That could be like this differentiating factor that companies are excited about and that really warrants all of the investments.
Lukas Egger: What is it that you see and is that the same that customers see or is there a discrepancy?
Gero Decker: So the one thing that most people look at when deploying AI is efficiency.
Gero Decker: Right. So they see all of the things that they do today. They see hundreds and thousands of people doing certain tasks and they say, well, if a machine could take over the same amount of tasks or at least half of it, how great would that be? Because it would be an immediate impact to my bottom line. Right. So the efficiency gain is in.
Gero Decker: Age-old principle for automation and technology in general that you think you just want to do the same going forward, but with less input and less cost.
Gero Decker: Great, let's do it.
Gero Decker: But the promise of AI is much greater.
Gero Decker: It goes beyond removing friction and it goes beyond removing manual work and introducing automation.
Gero Decker: But it also means that it opens up new possibilities and opportunities that you might not have had before.
Gero Decker: So first of all, one of the great levers that customers can have and some have with AI is that they can democratize certain pieces within their business. So certain tasks don't require an expert anymore, or that many experts.
Gero Decker: much of the task can be done with AI.
Gero Decker: So it's much easier to do and a lot more people can be involved.
Gero Decker: So, for example, if you look at social media, most of the social media posts that companies put out these days are actually written by AI.
Gero Decker: But what this leverages is that it becomes so much easier for companies to communicate.
Gero Decker: So you can enable people who didn't have a voice, who didn't have a say suddenly, and it becomes so much easier for them to participate in.
Gero Decker: in the conversation, right?
Gero Decker: So democratization and bringing in kind of less need for high skills or scarce skills to do certain tasks is an opportunity in and of itself.
Gero Decker: But there's also this knob that you ideally want to turn.
Gero Decker: So sometimes if you optimize things, with AI up to a certain point, suddenly entirely new things are possible.
Gero Decker: My favorite example is the recommendations that you find on e-commerce websites, right?
Gero Decker: So customers like you also bought this and this, right?
Gero Decker: Don't you want to buy?
Gero Decker: One click, add it to your shopping cart.
Gero Decker: We all know this, right?
Gero Decker: And sometimes the recommendations are pretty good.
Gero Decker: But now imagine Amazon can tune and optimize recommendations so much.
Gero Decker: that they can predict with 95 or 98% accuracy what product you want to buy at a certain point in time.
Gero Decker: You know what you can do?
Gero Decker: You can completely reinvent the process and say, let's skip the ordering step.
Gero Decker: We will just deliver because we know what the customer wants.
Gero Decker: We just sent the package to the customer without the customer having ordered it.
Gero Decker: And then at the doorstop, the customer can say, oh, thank you.
Gero Decker: I actually wanted it.
Gero Decker: Great.
Gero Decker: Thank you.
Gero Decker: Or it can say, oh, I didn't order that.
Gero Decker: I didn't want to go back.
Gero Decker: These are things where you turn the knob with AI so much that suddenly things become possible that were not possible before, right?
Gero Decker: But the biggest, I think that the biggest thing these days that companies find is the acceleration.
Gero Decker: That you can develop new capabilities, that you can introduce change, that you can experiment with things, that you can change the organization so much faster because AI supports you in doing so.
Lukas Egger: I mean, the obvious first reaction is excitement, right?
Lukas Egger: And that's what we see in the markets.
Lukas Egger: Everybody's like, oh, I want to be part of that.
Lukas Egger: But now how you explained it, it also sounds hard because AI is a different beast.
Lukas Egger: It can unlock new functionalities that we're not used to and will have to change more than we had to change before, which arguably was not easy.
Lukas Egger: So do you think overall business transformation or working with processes will get easier or harder?
Lukas Egger: Do you think it...
Lukas Egger: the democratization and all the other stuff will outweigh the challenges that companies will face by getting it to work for them.
Gero Decker: Look, we all know the chat GPT effect, right? You need to write an email or you need to, you know, send best wishes for a friend's wedding, right? And chat GPT to the rescue, and suddenly it becomes so easy to do these types of tasks. So even if, you know, deploying AI turns out to be hard and turns out to uncover all kinds of new challenges, the promises or the idea is there, the hope is there, that AI can help deploy AI.
Gero Decker: So everything that is introduced as a new challenge everything that appears, the assumption is, will become to a certain degree easier through AI.
Gero Decker: So my assumption is, even if you inherit new challenges, the net effect is it's going to be easier to change. And those companies who are afraid or who say, well, we don't need to be the first ones, we can wait a year or two and see what the others do, they will soon see that they fall behind because changing has become so much easier with AI.
Lukas Egger: And do you see, you have a lot of conversations with business leader and people who are actually in charge.
Lukas Egger: Do you see that there is a convergence of these topics?
Lukas Egger: Do business leader feel the same about the challenges or do you see like a divergence of, because there are so many topics, right?
Lukas Egger: There's AI, there's agents.
Lukas Egger: There are so many things one could focus on and businesses also feel squeezed, right? It feels like the competitive pressure is only getting bigger. What's your, I guess, also unique perspective of being able to talk to people who are actually in charge of creating change?
Lukas Egger: Yeah.
Gero Decker: Look, so I see that all the habits repeat themselves into the future.
Gero Decker: Certain rituals or mindsets that you have organizations that extend into the future.
Gero Decker: If you're an organization that was trained to look for efficiencies, for cost reduction, for takeout of complexity and so forth, they will see AI to solve exactly that challenge for them.
Gero Decker: If you have companies who have a problem with transferring skills or knowledge within the organization, they will see AI as the rescue for exactly that challenge that they had.
Gero Decker: And if there are companies who say, well, we maxed out on the things that we do today, we need to be creative.
Gero Decker: to find adjacencies or growth areas for a company to expand, they will see AI as the tool to do exactly that, right? So what I haven't seen yet is that AI suddenly changes the perspective entirely of what you want to do with your business. It is a tool for the purpose or for the challenge that you already had yesterday, but it's a very good tool.
Gero Decker: And it's very powerful and it solves a lot of challenges. Companies that drown in IT complexity, for instance, well, of course, they see AI as a phenomenal tool to do all of the plumbing for them, right? To be able to stitch data together in a much easier way or to build applications in a much faster way than they ever could.
Gero Decker: because AI, with all of its statistics and heuristics, can connect the dots much faster and more efficiently than people.
Gero Decker: But those on the creative end who say, well, I feel there's wide open opportunity for me as a company, what else could I do?
Gero Decker: Well, they will use Gen.AI and its ability to hallucinate and generate ideas to say, here's everything that we do. Here's everything that we own. Can you combine it in novel ways? Or can you connect it to something that you've observed out there to give me ideas what else I could do? So your innovation funnel suddenly becomes five times, 10 times bigger.
Gero Decker: Compared to just asking smart people about what they think or what the ideas are that they have, right? So depending on which direction you want to move into, AI is a phenomenal tool.
Lukas Egger: I love that perspective. And it goes back to maybe the old adage, with a hammer in your hand, the world is nails and not nails, right?
Lukas Egger: But now I'm curious because your personal perspective, what is it that keeps you curious?
Lukas Egger: Like, are you excited about the efficiency that we will drive in the near term?
And that's amazing.
Or are there certain aspects and...
whether it's agents or some parts about what AI can do, which was never possible, whether it's emotions, whether it's like unique kind of processes or whatever it might be.
Is there anything that you feel like coming back to that you are drawn to?
Gero Decker: Look, I'm a software engineer by background and I'm a product person, right? So all my life I've done nothing else than thinking about what type of software products can we build out there. And what you can build in terms of product has dramatically changed over the last two to three years.
Gero Decker: Until three years ago, you needed to have a very good understanding of what you wanted to do. And then you had to have, you needed to do all of the translation yourself, all the way to the technical level, to make that solution come to life that you wished for.
Gero Decker: So now with Gen AI, this is expedited, and you can sometimes take 60, 70, 80, 90% out, and this makes you so much faster, but it also allows you to build products that can take over a lot more.
Gero Decker: that only very skilled people could do previously.
Gero Decker: So maybe now is a good time to move into the area of agents.
Gero Decker: So I come from academia and multi-agent systems, autonomous agents.
Gero Decker: They were a concept for 20, 30 years out there in academia, like a dream of dealing with complexity, giving certain autonomous units a task and a goal and let them figure out how they best solve it.
Gero Decker: But there were no means to actually program these agents in a smart way.
Gero Decker: So they just ended up taking inputs and producing always the outputs.
Gero Decker: And you had to program all of the logic of that agent.
Gero Decker: So they were not doing anything surprising.
Gero Decker: They were not doing anything sophisticated.
Gero Decker: They could calculate A plus B equals C.
Gero Decker: Right. But not much more. So now with Gen AI, you can build agents that are vastly smarter that can take over entire tasks. You can give them a challenge and say, I have a business trip coming up. Can you please do everything required?
Gero Decker: to make that trip worthwhile and make it smooth for me.
Gero Decker: And the system will be able to go ahead and seek all of the context.
Gero Decker: Ah, okay, so you're going to a conference.
Gero Decker: It starts on that day.
Gero Decker: It ends on that day.
Gero Decker: It's actually in a nice location.
Gero Decker: And I actually understand from your previous behavior that you might want to add half a day to do a little bit of sightseeing on that.
Gero Decker: are and you try to travel in a sustainable way this is what you've done in the past so I prefer a train ride versus a plane and I give you all of the options right and I try to anticipate everything for you and decompose and do all of the steps required to make this worthwhile I even enable an out of office email because I've seen that you've done that in the past right this is an example for how an agent can take over responsibility or can take over quite complex tasks end-to-end and do all of the things that are required along the way. And they can hyper-personalize. They can understand the context very deeply in which they sit, in which they live, in which a task exists. So they can change and adapt very, very quickly to the specific context that they're in. But here is the interesting thing.
Gero Decker: So if you have a system of agents or you have many agents doing all kinds of stuff, it's like having an organization with many different people, right?
Gero Decker: And in fact, there will be a coexistence of these agents that are able to take over more and more complex tasks themselves.
Gero Decker: sitting and working alongside and with humans around them.
Gero Decker: So now the question is, how do you translate the strategy or the objectives of your company to what all of these people and agents are doing on the ground?
Gero Decker: You know what the trick was that has been applied for decades?
Gero Decker: business process, right?
Gero Decker: You need a viewpoint, you need a perspective that allows you, that gives you an organizing principle so that all of these constituents can work together, that all of the handovers work, that expectations are clear, that it's clear what are the two to five KPIs for a given process to estimate whether things are running in order, right?
Gero Decker: What are the boundary conditions for that?
Gero Decker: Right? What are the decision points that are there? And how can we best split up work so that we get the job done? Right? Humans are creative and they find novel ways. And of course, they provide their feedback and say, this process can be improved. Why don't we eliminate that step? Or why don't we create a third option? The same thing agents will do. They will say, why do you even give me that task? I found nobody's actually using what I give you back.
Gero Decker: Or here's another option, and maybe you want to develop a new skill or onboard something else to get that task more done.
Gero Decker: But in the end, it's all business process management.
Gero Decker: We've done it for many, many decades, right?
Gero Decker: It's trying to understand how all of these things work together that are inside of my organization, right?
Gero Decker: but also the flows that go across organizations.
Gero Decker: And how can we best organize that so that the outcome is great every time?
Gero Decker: So this is the exciting piece of our business process management in the world of agents, that it has at least the same relevance like it had before in human-centric organizations or where humans were the only ones who performed work.
Gero Decker: Now with the age of agents, where it's so much easier to deploy an additional 1,000 agents, it's not so easy to deploy an additional 1,000 colleagues to a task, but it's very easy to deploy another 1,000 agents that you onboard.
Gero Decker: Certain limitations are removed, so the degree of understanding is amplified.
Gero Decker: The need for understanding is amplified.
Gero Decker: And also the governance and the steering of this all becomes even more important because this whole system is now able to evolve much faster than we've known in the past.
Gero Decker: So this is what I'm really, really excited about, that when you discover that something that you've done for 20 years is still very relevant or is even more relevant as you go into the future.
Lukas Egger: Yeah, I would say you gave a very good argument why it should be even more relevant. Yet at the same time, whenever we're facing like a hype, there is disillusionment, there is a period where it gets overhyped and then needs to pick itself up.
Lukas Egger: Now, do you think we have already all of the parts for agents to be successful? Or do you believe that in terms of the process management, what you said is still relevant or relevant anew, that there also needs to be an innovation like how we manage processes?
Lukas Egger: So essentially, Is it straight cruising or do we need fundamental innovation in what you laid out, right?
Lukas Egger: Understanding my business, seeing everything, calculating values, impacts, and so forth.
Lukas Egger: Is everything there or do we need parts?
Gero Decker: Look, I like to compare this with technology waves that come in the past. One big wave that came was mobile, right? So suddenly everybody had a smartphone in their hand. And everybody, I think, and most likely remember the moment where for the first time you zoom into Google Maps with two fingers.
Gero Decker: It's a magic moment, something that you simply couldn't do before.
Gero Decker: It was only possible because of the device of its form factor of how it was built and how it was ubiquitous with you all the time.
Gero Decker: So very soon, once people saw the first apps, they asked themselves, well, I have this other task or I have this other thing to do.
Gero Decker: Why isn't there an app for that?
Gero Decker: There should be an app for that. So there was this, first of all, very quick understanding of the potential that everything, potentially everything that you do can be done on the mobile phone much faster, much smoother, which is two clicks. But Still until this point, I mean, when was the iPhone launch? It was 20 years ago, probably, when it was launched with the apps and everything. So still new apps come where you say, wow, this is doing something that I didn't expect an app to do before. Wow, there's something cool that just came around. So it's a gradual process until it's all there.
Gero Decker: The wonderful thing is, similar to mobile apps, now we have this moment where people can't imagine everything.
Gero Decker: They've used ChatGVT or other tools or image generation tools and so on and so forth.
Gero Decker: And they say, wow, this is so phenomenal.
Gero Decker: And suddenly you can imagine all of these use cases, all of these things that Gen.AI can do for you.
Gero Decker: And you're even disappointed if the system doesn't do it for you, right? So you open up an application and you still need to do all kinds of manual stuff. And you still have to know it in detail to work yourself through it and complete the task yourself. And you kind of just tell the system, solve this for me? Isn't this what Gen AI is for?
Gero Decker: it's going to take time, it's going to take years until, let's say, 80%, 90% of all of the usual things that can be solved through Gen AI will actually be there and will be readily available, right?
Gero Decker: Yeah.
Gero Decker: But this is just the first step.
Gero Decker: So we've seen with mobile apps suddenly your behavior changes a lot, right? Suddenly something like social networks become ubiquitous because everybody can take pictures all the time. Suddenly a significant part of your life goes into that and you start to define yourself as how you are perceived within that. How crazy is that? That you change your perception of your identity because there is new technology and that allow you to interact with people in a novel way.
Gero Decker: And the same will happen with Gen AI.
Gero Decker: So can we all predict it?
Gero Decker: You know, when the iPhone was launched, could people predict that the power of Instagram and TikTok on the world and how they can change elections and how they can change how people see themselves?
Gero Decker: I guess not.
Gero Decker: And this is the interesting path now for the coming years, where we will have to discover all of these things, all of these side effects that might be unexpected that come through Gen AI.
Gero Decker: So what are the parts that are missing?
Gero Decker: You know, I wish I had the crystal ball to see it all.
Gero Decker: I don't.
Gero Decker: It's going to be a gradual process.
Gero Decker: But what's different this time is that the speed is higher, right?
Gero Decker: So in the past, you could go offline for like three months and still...
Gero Decker: you didn't miss a lot, right?
Gero Decker: Or you could even go offline for six months or nine months and you could still catch up very quickly.
Gero Decker: Now, if you look at AI and what's possible, and if you don't look for three months, it's like, oh, it's like time travel.
Gero Decker: Suddenly you're in a different century.
Gero Decker: This is how it feels.
Gero Decker: So it challenges people in their ability to adapt and absorb all of the new stuff that is there.
Gero Decker: So the one thing, if you ask me for one thing that people require, more than ever, more than before, is the willingness and the ability to absorb change, drive change and transformation and make this the main muscle for yourself and your organization.
Lukas Egger: So adaptability as a superpower.
Lukas Egger: But while you were explaining very beautifully what is coming, I realized that a lot of the examples you brought were from a B2C perspective, from a very personal perspective.
Lukas Egger: I kind of want to throw a question out there because we're always talking about processes from a very business-centric perspective, which it always has been.
Lukas Egger: But agent technology could as easily be perceived as very B2C, just like mobile, right?
Lukas Egger: Do you believe that process management in the end could end up as a B2C product instead of a purely B2B thing?
Gero Decker: Look, with most technology, B2C, the consumer world is the first one to adopt it at scale, right? Because the cycles are shorter. You can make a decision, you see something today, and you say, I want to have it. I will take half of this month's paycheck to get this piece of technology because it is so cool.
Gero Decker: This is the beauty of the consumer world, that decisions can be made a lot faster, and the complexity is typically less because the products only need to take care of that one person.
Gero Decker: And complexity is higher once you go to businesses because you need to factor in all kinds of things and all kinds of requirements.
Gero Decker: But it's a natural path that first...
Gero Decker: You do things on the B2C world, and then you transport it to organizations. I mean, your question is interesting because it asks the question, will businesses still exist in the future? Or will we organize the world in a very different way? This question comes and goes, right? Think about the gig economy or other ways of organizing the economy. Look, After all of the technology, after all of the things that have happened the last couple of decades, companies are still the organizing principle for a lot that's happening in this world, for this economy, because it's a nice way to deal with complexity and to provide efficiency at scale and make things accessible to a very large number of people.
Gero Decker: And there with accelerating the usage and the potential of technology that exists.
Gero Decker: So business processes, they were born in the business world.
Gero Decker: Why?
Gero Decker: Because it's exactly back to my example of the telcos.
Gero Decker: It's about organizing things that are inherently distributed, that are inherently complex, that inherently have many people involved, many systems, tons of different types of data that all need to come together to produce an outcome.
Gero Decker: In the private world, yes, of course, you will see things that will help you organize your day, that will help you develop the right routines, that will take over tasks for you. We always see that. But business process management inherently, I think, is a topic that is applied by organizations.
Lukas Egger: It makes perfect sense. So you're saying, regardless of how much you push the hype, the most likely scenario will be coexistence of the new value propositions created by AI, not a complete reinvention.
Lukas Egger: And because of it, a smooth transition if you focus on processes, which sounds like a very encouraging message.
Gero Decker: It sounds a little too simple, I think, how you phrase it, because change is difficult, right?
Gero Decker: And smooth sailing is smooth.
Gero Decker: It's probably the wrong word because we talk about disruptive technology here that is turning certain things on its head, that is taking people by their pride, things that they have learned for 30, 40 years, and suddenly you have a machine that can do 70% of that twice as good as you can.
Gero Decker: Man, that's a change that is hard to digest.
Gero Decker: So smooth, I wouldn't dare say.
Gero Decker: There is a trick to all of this.
Gero Decker: And this is the ability to change, to adopt, to be willing, and to be capable of deploying change to an organization.
Gero Decker: But.
Lukas Egger: Yeah.
Lukas Egger: You caught me there because I was trying to set up the question.
Lukas Egger: If everything sounds smooth, I wanted to ask you what are the really bold parts or the bold predictions that you have?
Lukas Egger: because you have incredible insights in how it has been in the past.
Lukas Egger: And I'm sure there is a couple of things that you're excited about that might even sound too big right now for people who work in the field of strategy and so forth.
Lukas Egger: So I was curious to ask, what are your really bold predictions for the future?
Gero Decker: So one prediction is we're moving to a frictionless world. Okay. And I give you examples of frictionless already from the present and from the past. If you look at how you can buy stuff, the degree how easy it has become to buy stuff is, You know, at any time of the day, wherever you are in the world, a phenomenal choice, a phenomenal quality with high efficiency is just mind-blowing. And the same effect will happen to all kinds of things that we have around us.
Gero Decker: we will have so many people and we will have AI that will remove all of the friction points out there. That in the end, everything that can be done with a click of a button on your mobile phone will be done with a click of a button on the mobile phone. This is my one bold prediction.
Gero Decker: And of course, the companies that are the fastest to get there will win. But There's a world beyond that. And that would be my prediction number two. My prediction number two is that those companies will see the biggest success that not only focus on the pain points, the friction points in their business, but that also reserve a certain portion to reinvent themselves and look beyond success.
Gero Decker: what they're currently doing.
Gero Decker: And they see the strengths or assets that they have and turn this into opportunity for them as a company.
Gero Decker: Because frictionless alone will lead to a world where you have a shark tank of companies competing at minimal margin, right?
Gero Decker: Back to my example with buying stuff on the internet, the margins are so thin because everybody has moved in that direction and has made buying stuff frictionless.
Gero Decker: So it's other things that make you win.
Gero Decker: These are things like trust.
Gero Decker: It's things like choice.
Gero Decker: It's things like personalization, intimacy.
Gero Decker: There's many other things that you can optimize for as a company and where you can ask yourself, what can I do?
Gero Decker: Or what are completely new types of offerings that I can bring to market that go beyond what's possible today or even beyond what can be imagined?
Gero Decker: And my third prediction is, We are going to see a distinction between well-performing companies and worst-performing companies.
Gero Decker: And the success of these companies can be measured by two simple metrics.
Gero Decker: metric number one is time to insight and the other metric is time to adapt how fast can companies understand what's going on and make sense of everything that's happening in their business across everything and see the dependencies and how it all works together and draw the right conclusions from that.
Gero Decker: And once you've drawn the right conclusions and you say, I want to act on it, I want to leverage this cool new thing.
Gero Decker: I want to do things differently.
Gero Decker: I want to leave things behind.
Gero Decker: The companies that are able to do that the fastest, they are the ones that will win.
Gero Decker: So three predictions.
Gero Decker: One, a frictionless world.
Gero Decker: I want that, I'm just being selfish here, I want that for myself. But I deeply believe that it's possible, and all of the tools in the world point into that direction. Second, going beyond frictionless is the path to win, and the companies that will see phenomenal growth rates, but that will also see sustainably high margins, are the ones who constantly are able to push the boundaries and are able to reinvent.
Gero Decker: And then third...
Lukas Egger: is the speed with which you can change as the determining factor driven by time to insight and time to adapt.
Lukas Egger: I think it's very powerful, those three parts.
Lukas Egger: And I don't even want to add anything.
Lukas Egger: I just want to Bring us back into the here and now, because we're always interested in, after discussing long-standing changes in the future, what is it that you would love to change in the here and now?
Lukas Egger: Like, if you could instantly transform a process today, which one would it be and why?
Gero Decker: My favorite process, to be disrupted, to be reinvented, to be solved for myself, is taking the kids to bed in the evening. That is consuming so much time. If there is a trick to that process, to free up some more time in the evening with my wife, I would gladly take it.
Lukas Egger: I love that.
Lukas Egger: And maybe that would be then some other conversation about processes that you don't want to optimize, right?
Lukas Egger: That are inherently enjoyable, that are outside of the scope.
Lukas Egger: Thank you so much, Gero, for the insights.
Lukas Egger: They were exceptional.
Gero Decker: Thank you, everyone.
Lukas Egger: And well, with that, Thanks for listening to another episode of Process Transformers.
Lukas Egger: This podcast is brought to you by the dedicated efforts and the hard work of our team.
Lukas Egger: So a really heartfelt thank you to Bezer Katal.
Lukas Egger: Regan Neandoro, Erica Davis, Cecilia Sarkees, Vazi Murad, and Julian Leveneau.
Lukas Egger: If you have questions or comments, email us at processtransformers at sap.com.
Lukas Egger: And until next time, for another transformative conversation.
