CR106: Changing nature of large scale apps with Timo Elliott SAP

The rise of structure software fueled globalization by streamlining operations across borders. Now, Cloud and AI are accelerating this momentum, enabling faster innovation, smarter decision-making, and scalable growth. By modernizing ERP with intelligent technologies, organizations can stay agile, competitive, and ready for the next wave of global transformation.

This week, Dave, Esmee and Rob talk to Timo Elliott, Innovation Evangelist at SAP, to explore how SAP is driving globalization—and how organizations can accelerate innovation through the power of Cloud and AI.

TLDR
00:55 Introduction of Timo Elliott
02:40 Rob shares his confusion about misleading online ads
08:06 In-depth conversation with Timo
46:32 Rethinking control in enterprise systems
1:00:00 Brunch at a Paris café or joining an event?

Guest
Timo Elliott: https://www.linkedin.com/in/timoelliott/

Hosts
Dave Chapman: https://www.linkedin.com/in/chapmandr/
Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/
Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/

Production
Marcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/
Dave Chapman: https://www.linkedin.com/in/chapmandr/

Sound
Ben Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/
Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/

'Cloud Realities' is an original podcast from Capgemini

Creators and Guests

Host

Dave Chapman

Chief Cloud Evangelist with nearly 30 years of global experience in strategic development, transformation, program delivery, and operations, I bring a wealth of expertise to the world of cloud innovation. In addition to my professional expertise, I’m the creator and main host of the Cloud Realities podcast, where we explore the transformative power of cloud technology.

Host

Esmee van de Giessen

Principal Consultant Enterprise Transformation and Cloud Realities podcast host, bridges gaps to drive impactful change. With expertise in agile, value delivery, culture, and user adoption, she empowers teams and leaders to ensure technology enhances agility, resilience, and sustainable growth across ecosystems.

Host

Rob Kernahan

VP Chief Architect for Cloud and Cloud Realities podcast host, drives digital transformation by combining deep technical expertise with exceptional client engagement. Passionate about high-performance cultures, he leverages cloud and modern operating models to create low-friction, high-velocity environments that fuel business growth and empower people to thrive.

Producer

Marcel van der Burg

VP Global Marketing and producer of the Cloud Realities podcast, is a strategic marketing leader with 33+ years of experience. He drives global cloud marketing strategies, leveraging creativity, multi-channel expertise, and problem-solving to deliver impactful business growth in complex environments.

What is Cloud Realities?

Exploring the practical and exciting alternate realities that can be unleashed through cloud driven transformation and cloud native living and working.

Each episode, our hosts Dave, Esmee & Rob talk to Cloud leaders and practitioners to understand how previously untapped business value can be released, how to deal with the challenges and risks that come with bold ventures and how does human experience factor into all of this?

They cover Intelligent Industry, Customer Experience, Sustainability, AI, Data and Insight, Cyber, Cost, Leadership, Talent and, of course, Tech.

Together, Dave, Esmee & Rob have over 80 years of cloud and transformation experience and act as our guides though a new reality each week.

Web - https://www.capgemini.com/insights/research-library/cloud-realities-podcast/
Email - [e-mail]

CR106: Changing nature of large scale apps with Timo Elliott SAP
[00:00:00] This is the 747 4 hundreds that, uh, a few airlines still fly, need to be updated with floppies as well as a sort of aircraft control system. You're like, do we still make floppy?
Welcome to Cloud Realities and original podcast from Capgemini, and this week it is a conversation show, exploring the world of structured software [00:00:30] and how it came to evolve and basically help the world's organizations become global, but what it also will become in the world of AI. I'm Dave Chapman. I'm Esmee van de Giessen and I'm Rob Kenahan.
I'm delighted to say that joining us today for this conversation is Timo Elliott, who's SAP's Innovation Evangelist Timo, how you doing? Wonderful. Thank you so much for letting me take part in this podcast. Delighted to see you. Thanks so much for taking the time. Just wanna tell us a little bit about [00:01:00] what the world of an innovation evangelist is.
So, my job involves working with our customers who are on the leading edge of innovation, trying to gather the lessons learned and then share that with as many people as possible so that we can all be more successful. Very much looking forward to getting into today's conversation with you. The, you know, kind of how linear and sequential process driven software is going to evolve is something on the show that we've, we've nudged around a few times and not got to a, sort of a [00:01:30] satisfactory, clear vector on it.
So, I, I can't wait to explore that with you today. Wonderful. Robert should be some opportunities for some, uh, architect chatting, all of that. Uh, it just, yeah. There's lots of potential, David, for you to glaze over. I love it. No, there is this quiet. There's quiet. We're gonna, I feel like there's, we're gonna just get to the root of a lot of the things that might be facing business and technology.
Yeah. It's, it's gotta be some of the bigger questions for investment, I think. Yeah. Wrapped up in all of this. At the core. At the core as [00:02:00] you ready? Yeah, I am. Yeah. Have you got the matchstick for your eyes for when we get into the, uh, the rough bit about architecture and that Oh, I, I think I'm just gonna use my poker face.
Yeah. And you'd probably think it's a still image. Yeah. It looks like you're frozen. That one. Yeah. Yeah. I like the way you pull this line. Do little, like the films where they take a photo of the hallway and stick the Polaroid in front of the security camera. Yeah. There's all whole school full of security card.
You, you're gonna do that in front of your camera, so we just see a picture of, [00:02:30] you think anyone would notice? I haven't noticed the times You've done that before, so kudos. I'm not gonna tell how many. Yeah, you're gonna keep that to yourself. Brilliant. Anyway, Robert. What's confusing you this week? I'll tell you what's confusing me this week, Dave.
You know we've had the conversation about optimistic spam and I don't understand it. Flag guy, and please flag guy, come back. We've been missing you. We want the cloud. We want the cloud. Give you some flags. But the, the one that got me this, uh, recently was ads that trick you. To going to their [00:03:00] website and then attempt to sell you something.
And I can't get why somebody who's been tricked to go somewhere suddenly thinks, ah, I know you've tricked me to get here, but I'm still gonna give you my credit card details to buy your product. And I'm like, what is the business model behind that? And who, after being tricked is going, yes, I want to enter into commercial relationship with this organization.
And I am deeply confused by this. 'cause these trickery ads, they're getting better in sophistication. And what now they make they look like other legitimate websites. Then you [00:03:30] click it, you go, why have I ended up here? And then you're like, you wanna sell me something? Go and do one. But there must be a valid business model behind it because it's a thing.
I didn't get it. And that's what's confused me. I got a new one the other day, a text message wrong about a parking fine. Oh yeah, yeah, yeah. They're they're more common these days, aren't they? Yeah. Yeah. Parking fine. But it was some, it was a parking fine from the UK government, which I thought, I didn't know the department for parking fines.
But that's, that's tri, that's trickery in the old sense that I'm pretending to be something you're not. What I'm talking about is you get, you get sent somewhere [00:04:00] and then they reveal their legitimate intention, and then they try and foggy something and I'm like, why do you think I'm gonna buy something from you?
It's like, you've only done that three or four times, don't you? You aren't gonna treat me again, time wise to their ways. Now, I've worked out what they're doing, Dave, I've got it, but it's this again, but the, the thing underneath it is, it must work at some level because. It's getting more prolific trick ads.
And sometimes they're like, you know, the, the, we've had the [00:04:30] clickbait sensationalistic headline to go through to the website for the news agency that then is a really dull and boring story. But this, this taking clickbait to the next level where it's click trickery. That's the phrase I'm gonna start to, uh, to use, uh, uh, painted.
You're gonna try and make click trickery work. Click trickery. But it rolls. It's, it's, it's a bit hard to say, but it's like a, a, you know, a nice phrase. Click trickery. Yeah. But it's the, um, it's the, it's that, which is the, uh. What was your motive to get that person to that website? Just apply? I just, I, it just [00:05:00] does at my core confuses me.
Sorry. So as, how do you feel about all this? Does it make sense? Trickery? Yes. Click trickery. Well, it's actually fascinating, right? I think it's a core combination of digital literacy, understanding how this works. Yeah. UX and uh, UI that is increasingly becoming like exactly the same as the original websites, and it's pure psychology behind it.
So I think that combination, that's like pure marketing, that it's, it's actually quite a craft. Mm. Click trickery is a [00:05:30] craft. Could we give your audience some very actionable information? Well, it would be a first team. It would be a first in my section definitely. We, we typically try to avoid that useful stuff.
My question to you is, have you chosen your AI safe word for your family yet? Oh, I've heard about, no, we haven't, but I, we, and we need to do that. So this, we to do that. So this, you and everybody's listening, you need to do this because AI is supercharging. Phishing attempts. So deep fakes a voice. And [00:06:00] increasingly video means that sometime soon you might get a phone call or a video call from somebody who looks like your son or daughter, for example, who says, I've just been in an accident.
I desperately need some money. Please, uh, let me hand you over to somebody else. He'll tell you the bank details. And what do you say? What the safe floor, oh, sorry. I'm sorry. Yeah, no, I've got it now. I'm in, I'm in. We're really bad at this. [00:06:30] So this is, this is word again, what? I was just like confused, like what it's like, alright.
Oh, sorry. Yes, I've got you now. Yeah. So this is two factor authentication for the real world and your specific family. So, uh, seriously, so if you have elderly parents, honestly get them on the phone. Uh, convince them that you are indeed their son or daughter and say, you know, Hey, we really need to define some code words because sometimes soon you're gonna get this phone call and somebody's gonna try and [00:07:00] get some money out of you and it's gonna sound like me.
And so I really want us to set this up so that that doesn't, I'm sure that if I, um, if I, I'd explain that to my dad. Like in, in, you know, this is what you use it for, blah, blah, blah. And then about five minutes later I'd say, dad, what's a safe word? And you'd go, what's a safe word, son? Or, or you'd get phishing attempts ringing up old people asking what their safe word was and then just put the phone down.
And then a week later the AI comes through. So it's like double trickery. It's trickery on trickery. Yeah. [00:07:30] Yeah, yeah. So you need to rotate your safe word every 24 hours, don't you? This is the thing. Oh god. Okay. Rotating safe words to avoid click trickery. I think that's a thing. I think that's a thing. I think you've kind a thing.
I. Are. Please tell us about passwords. Rob know. Oh, 16 billion passwords. Timo, did you read that article? Oh my God. That's gonna cause chaos. You triggered that as I blame you. Yeah, I know. It's just weird. Yeah, yeah, yeah. Anyway, anyway, even I'm gonna move it on from this point, [00:08:00] I think. Got to the bottom of that.
That was that. That was very successful. Keen team, red advice, everything. Let's get on with the show and get into today's main event. So why don't we start a little bit with your story, Timo. I know you're living in Paris these days, but you, you don't sound like you're from that part of the world. So how did you end up there?
I am a, an innovation evangelist for SAP, but I grew up in pool in Dorsett. No way pool the Hawaiian [00:08:30] part of the UK for those of you who don't know it. Uh, beautiful sunny beaches and it was a wonderful place to grow up. Right? Went to university in Bristol, but then I went to go and see the world, worked in Hong Kong for a while, New Zealand for a while, and I met so many people that spoke so many languages and I felt like, uh, the black sheep with only English, and determined that despite my almost failed French.
O level that I would have a go at becoming a better European and learn at [00:09:00] least one other language. And so moved to Paris and stumbled across a small French startup. There was a pioneer in business analytics called Business Objects, so I was the eighth employee, very junior. And uh, that was acquired by SAP in 2007.
So 34 years now without having to change job. I mean, that's pretty good going. It, it's almost like you, rob. I was just gonna say, the [00:09:30] first bloke I met at my job was a, a mainframe developer sat next to me and he got talking about his career and he started off by fitting wheels on Minis in Longbridge, and he ended up as a mainframe cobalt developer.
And it sort like track. He so, so, so sorry. Never been fired. Just transitioned jobs and ended up in something completely different at the end. It was, it happens. It happens. That's absolutely amazing. That's absolutely amazing. So Paris, paint a picture for us, Timo. Whereabouts in Paris do you live [00:10:00] and sell it to us a bit.
So I live in the center of Paris. Uh, you can literally see the Eiffel Tower from my balcony. It's a beautiful city. My God. Please come and visit. I hope you enjoyed the Olympics. It looked amazing on tv. Uh, come and see the real things. We actually, we actually need your tourist dollars because COVID hit us pretty, us pretty hard for a few years there, we didn't have the tourists that we would've liked, and so the, the company is, uh, the city's a little bit in debt, so we'd love you to come and visit.
It is the most beautiful romantic city in the [00:10:30] world. And, um, well, one of my, uh, favorite things to do in Paris is breakfast. You know, like sitting outside of one of the ca one of the street, that's just one of your favorite things to do. David, it doesn't need to be embarrassed. That's actually true. I, I mean, breakfast is gonna be the best meal of the day.
I think brunch, maybe brunch, maybe edges it, but, you know, say in one of those, one of the little pavement cafes watching the world go by. Paris has gotta be one of the best cities in the world to do that, isn't it? It is. Absolutely. Uh, forget about all of the, uh, tourist stops and, uh, just sit in a cafe and watch the world [00:11:00] by Yeah, just watch the world go by.
I think that's one of the best ways to sort of enjoy any city really. Paris in the spring. Paris In the spring. Robert was in uh, Stockholm recently. You went to the ABBA Museum, didn't you? I did, I did. I was thought, I thought to myself, I'm in the center, what do I do? And spied the ABBA Museum. And I thought, I'm gonna do that.
And I did. And it was actually quite interesting. I'm not a massive ABBA fan, but I do appreciate some of their music. But it was just cool to see the way they sound, all museum associates with them. It's quite a big [00:11:30] endeavor as well. I love Stockholm. I'm actually half Swedish as, uh oh. I mean, it's this international story can tell story.
It's not used, doesn't it? As you can tell from my very, uh, you, you folks can't see me, but, you know, look, obviously Viking. Yeah, with my dark hair. Um, but no, my mother was Swedish, so we spent a lot of time in Stockholm. It's a beautiful place to visit, especially in summer for the one week. It's summer, right?
Delightful. I it's on the harbor. There's lots of grand buildings and [00:12:00] there's like, it's like a nicely laid out city with lots of, it feels very calm and, uh, serene in Stockholm, I would say. It's not a, it's not bustling, but that's a good thing. The slogan is Beauty on water. There you go. In English, not in Swedish.
Interesting enough, there is no Swedish equivalent if they have an English slogan for their city and what was range. That's unusual, isn't it? That is unusual. I wonder if it's the only city in the world that has its slogan and its non-national. I would say London slogan is probably an English as well.
Dave, I'm gonna go with a bet with that non-native [00:12:30] language. You didn't put that. That would be the language. Anyway, let's get onto our main subject, which is going to be exploring SAP, both its history and today. So I hold SAP as being. A very significant component in how it, and then the businesses that it was serving were able to globalize over, particularly like the late nineties and the, and the naughties. It was, to me, the, a lot of the, you know, [00:13:00] beyond the infrastructure, it was sort of the business scaffolding that kind of helped organizations align and simplify and things like that. It it, do you hold it similar, Tim, or is that just my perspective? No, absolutely. In the, in the nineties, there was a period where people were moving from lots of different custom applications to a single integrated suite, uh, just in time for Y2K in many cases. Right, right. And SAP was lucky enough to ride that wave to become, to [00:13:30] this day, uh, Europe's largest technology company. Hmm. Uh, and this actually echoes of that same sort of momentum now I think it's coming back in some ways. Actually, I heard an anecdote the other day. This is Einstein in 1940 is teaching at Princeton University in the us and he's giving an exam to the students.
One of them stands up and complains and said, but professor, these questions are exactly the same as last year's exam. Hmm. [00:14:00] And he says, ah, but the answers are all now different. Yeah. Brilliant, brilliant. So this was the era where quantum physics was calling into question everything that people thought they knew about the discipline.
Yeah, and I think we're starting to face that right now with artificial intelligence. The questions haven't changed. The business challenges are all the same as they've ever been. More so in some ways given all of the, uh, the chaos in the modern economy. But the answers what we can do about it really is being called [00:14:30] into question because of artificial intelligence.
Um, and the para, the parallels actually go further because Einstein famously said, God doesn't play dice because he didn't like this notion that quantum physics is probabilistic and not deterministic. And yet that's exactly what we're facing now with this AI technology. I. It is we're used to asking the same question and getting the same answer every now.
Very deterministic process driven technology. It's very efficient. [00:15:00] But now we have AI, which is probabilistic, allows us to do lots of new things, but we do have to rethink a lot of what we think we've learned over the years. Yeah, it's a breaking the habit of, I think particularly in the IT world of having like a very set and ingrained way of doing things, which frankly was looking pretty thread bare even, even 10 years ago, nevermind today, and start to push into something new.
I think that the leadership challenge of it and why [00:15:30] organizations struggle to execute it is it's quite unknowable, isn't it? Like there, there are certain things that you can sort of frame it with, but what it actually is going to be like is, feels unknowable and it's it, it's discomforting. Absolutely. I think there's a lot of question marks out there on what, uh, technology computing applications look like in a few years time.
And that in turn is accelerating this process of people realizing they really do need to move to modern cloud infrastructures. Right? Right. So, [00:16:00] SAP, we have a huge installed base. We've been doing this for over 50 years. So, uh, we have lots of customers that have already made that leap to the latest cloud platforms with our SAPS four HANA platform.
Mm-hmm. Cloud, ERP. But, uh, there's still companies on that journey. I think this need for AI and the need for a solid platform around data is we're seeing that accelerate. So there's this momentum that has come back to SAP that is similar to what we saw in the nineties, and I think, you [00:16:30] know, the stock price and the ecosystem reflect that.
It is actually quite an interesting, uh, technology story for Europe. 'cause if you look at who won the tech wars with all the VC funding that went into Silicon Valley, American Tech basically won. And you can see where all the money went in at the right time and Europe didn't do it. But there's a few notable examples and SAP is one of them, the behemoths of tech that actually has penetrated globally around organizations.
So it is a, it is a great success story that says there are a few [00:17:00] instances of technology success from a European context. And I quite like that, that you still go in strong and you've been here for a, you know, a stall war for a, a good many years and it's going to continue. So, I mean, I, it does, there's, there's a bit of, there's, there's some nice stuff in that as well.
Just being proud of the fact that it's, uh, born out of somewhere a bit different from a tech perspective. I mean, all of those large American companies are our big strategic partners. I was just on stage in London, uh, earlier this week doing a keynote with Microsoft. We work [00:17:30] very closely because our customers.
Have both of us as big strategic platforms. Microsoft uses SAP, we use Microsoft. Yeah. Um, but at the same time, yes, I'm a very proud European. I like to think that we have, uh, things that we could bring to the world of technology. And notably, there is a lot of interest in the world for solutions that are a little more local.
We're seeing sovereign cloud being a big, uh, and obviously that's something where we feel as a European company [00:18:00] with the, the roots of GDPR and data privacy and doing things in a slightly different way from the US standard. I think we do have an opportunity. Just one example, I'm a. Proud Frenchman. Now, I became French a few years ago.
Um, one of the companies we're working a lot with is, uh, Misra. So they're one of the European AI model providers. Um, they're not necessarily the ones that hit the headlines, but in terms of the power of their models and the, the cost [00:18:30] efficiency, they're a really good fit. So in many cases, they're a default for when we are using AI internally.
So we embed ai. So it's just an intrinsic part of our applications. Mm-hmm. A lot of times people won't even necessarily know it's there. It just works. And, uh, Misra is a very good fit for those kinds of models to do one thing, do it really well, and, uh, make sure that we can rely on the results. Obviously, a company like SAP, we can't have hallucinated answers.
Sure. We, you know, when somebody asks for a number, it has to be the right number. [00:19:00] That whole sovereign space, I think I agree is, is really becoming clear and solidifying at the moment. And I think sovereign ai, funny that you mentioned that is really bringing it to a head. I mean, it was important before with, you know, data sovereignty and GDPR and the things that you said earlier and, and Sovereign Cloud was kind of a bit, almost like a begrudging.
Yeah, okay, we have to do it, you know, that kind of thing. But with some of the changes in the world in the geopolitics and also with AI coming along in the way that you said, and it [00:19:30] really does become an imperative to think about your digital supply chain, I think. I mean, it really is a reflection of people's realization that ai, although there's a lot of hype, it really is the third big wave of technology.
Yeah. Innovation disruption after maybe PCs in the eighties and the internet in the nineties. Mm-hmm. And because it is so strategic, it has become a geopolitical topic where everybody believes that it has the potential to give countries [00:20:00] advantages over other countries. So. Mm-hmm. Yes. Unfortunately, I think, uh, some of us in the corporate world are, are the sidelines of that.
Um, obviously we'd like to help everybody in the world use this, uh, technology better to improve their businesses. I think there's, there's, if you look at. Especially western economies. There's been a productivity issue for some time, some commentary on capitalism, et cetera. But it, it seems like this could be the thing that lifts it back up to where it needs to be [00:20:30] to keep going.
'cause whilst we seek a different system or a better system, and we haven't found one yet, capitalism requires never increasing cycle. And it's, I, I feel, uh, that this information age we enter into and some of the potential might be a big intelligence. Answers intelligence. Intelligence, age, Robert, intelligence age.
You said information age. It's the same difference. I mean, fundamentally different. But anyway, keep going. Keep rolling. I'll keep going. Alright, go on. You, you'll get there. Go. I think I'd like to think, yeah, our listeners are clever enough to understand what we're talking about. Don't need hide your [00:21:00] mistake and don't need your very in-depth guidance associated with that, though.
You know, they're smart. I'm going for our listeners to keep it smart, Dave, but if you wanna have a different opinion, that's fine by me. Just, it might cause a bit, a bit of a. Problem with that perception. Anyway, it doesn't matter. Talking about relationships, Timo, how important are those relationships, what you see in the ecosystem?
You were just talking about the other tech companies. What, what do you see happening there? Uh, uh, so I think it goes hand in hand with this notion that you need more of a [00:21:30] platform. So composable computing is, is something in the industry where instead of having sort of monolithic on-premise, you need to have, uh, lots of different technologies that you can bring together.
More, a little bit like Lego bricks, where you can build what you need from, uh, pre-com, from components that can easily fit together. So obviously we using that to design our software in the cloud. So we have a suite of business applications that you can start with. Success factors for human [00:22:00] resources or concur for travel and expenses or finance on our cloud, ERP, uh, and then build it out over time.
But. It's clear that we can only help you with, you know, the, your core applications, but every organization is different. In particular, your differentiators are by definition different from other people's. And this is where there's a huge opportunity for ecosystems of, uh, partners who have built solutions.
I know Capgemini is a, is among our [00:22:30] wonderful partners who have, who've done this where. Once you have a core platform, so for example, we have something called SAP Business Technology Platform. It's the the core foundation that we use for all of our innovation. As we're building AI into our applications, we're using the functionality of the AI foundation in that platform.
We also make it available to customers who can build their own differentiating applications and extensions, and of course partners. One of the best things about the new cloud world is it's much [00:23:00] easier and faster to innovate, to move to new cloud applications. You don't need all of that painful custom coding.
And for organizations like yourself, I know that that is a change to. Your business models a little bit. So we're seeing our partners move away from making lots of monies off custom code billing and moving towards to providing these Lego bricks of functionality in your areas of expertise for particular, uh, business areas or industries?
I. And [00:23:30] you've hit on an interesting point there. Um, the debate going on about what huge amounts of productivity gain in software development life cycles is going to do. 'cause there are some odd, there are some odd shapes being drawn of team structure and everything else, but there's a great paradox that sits behind it.
It's called Jevons Paradox. I dunno if you've heard of it, but it basically says, as you increase the efficiency of something IE you know, fuel demand goes up. So increasing the fuel efficiency of a vehicle actually increases, [00:24:00] uh, the demand for its use. So you, you, you get this positive feedback loop associated with it.
And some are wondering if that's going to happen to the software era, which is because it's easier and faster to do it, whereas the demand for software is going to go up and up and up and up and up. As we understand everything is software defined in the future. So there's this thing about, oh, the developers need to wear and you go, actually, this might be the golden age for them.
Did you know as that he was gonna drop the old Jevons paradox in there? It's absolutely what's happening. And of [00:24:30] course, Jevons Fam, the famous example of Jevons Paradox is, uh, light bulbs. So the price of light bulbs have plummeted with LED, and now you'll find LEDs. Everywhere. Yeah. Yeah. It's an excellent one.
There's more light than ever. And I, and I come from the city of light, so very appropriate. But, so yes. This notion of, uh, coding. So one of the areas where AI has proved its value the fastest is in professional development. Yeah. It works really well because there's a clear [00:25:00] answer, you know, if you're getting it right or not.
At Anthropic just recently, uh, came out with Opus four and they claim that it was able to do up to seven hours or autonomous coding, refactoring nuts, isn some code from one code base to another. Oh, for machine coding. That's a lot of lines of code. Yeah. And, and, sorry. So, but just to continue that point, so yes, you're going to get, developers are starting to worry about their jobs.
It's like, well, okay, you know, Microsoft and some other organizations have slowed down hiring because they believe their existing [00:25:30] developers are gonna be more efficient. But globally, the amount of coding is skyrocketing. Yeah. Because everybody, you and I can vibe code now. Mm-hmm. We can get onto chat BT or one of the other, uh, interfaces and just say, Hey, you know what?
I'd like this solution. And it could be throwaway. It could literally be just, I have one particular thing I need to do today. Mm-hmm. Write me the code to do that one thing and we'll never see that code again. And that was something that's unthinkable. The whole point of coding in the [00:26:00] past, our mindset is that we do coding when we have a repeatable problem.
And it's worth all of that effort to put the time in. To, to use the code again multiple times. That's a good example of a, something that we take for granted that is kind of going away. Anybody can code and it doesn't have to be reusable. Well, does does that mean that if you can create code that is either single use or is extremely bespoke for, for [00:26:30] whatever situation you might need, and that code might be an agent or something along those lines, does that mean that.
Sort of sequential process-based software is going to need to radically change to kind of exist in this world and be valid, or does it mean that we still need that kind of thing to create frameworks within which the other stuff can exist? I think there are two big things that are changing in the mindset.
One is we will always have business [00:27:00] processes, but the way we define and implement those processes is changing radically. So we're all used to very predefined processes, a series of steps with branching and logic to get a business goal. The business goal remains the same, but now in, uh, the agentic world, we can define the goal and give the agent a series of tools and ask it to optimize its path to the goal.
But I don't think it replaces. I. Existing processes, and this is where [00:27:30] I'm maybe different from some of the, uh, the commentators. Mm-hmm. I think it's very easy to say, oh, you know, we won't need processes anymore. The reality is that every organization wants people to do things in the most efficient way possible.
Right. In fact, a huge amount of the value that we bring to organizations is best practice processes. Why come up with something custom when Yeah. You can just do it the best way possible. So the idea of replacing the best way possible with [00:28:00] agents that are doing things more or less at random Mm. To exaggerate.
Yeah. Yeah. Um, seems crazy to me. But there are whole areas where traditional processes. Are just not very good. They're not flexible enough. They can't deal with ambiguity enough. So we're seeing a, a big opportunity for agents that can cope with the messy reality of a lot of finance functions. Mm-hmm. For example, I was talking to a customer the other day that is using one of our agents for a [00:28:30] supplier balance reconciliation.
So this is where you have your ERP system that has data about, uh, the information that you, um, you, that what you've received from suppliers. But their ERP system says something slightly different. This is reality of. Modern commerce. And so at the end of each period, uh, you have a bunch of finance people who are trying to figure out why the, the things don't match.
And in an ideal world, everything would be beautifully connected with APIs and we'd all be part of this fantastic, [00:29:00] uh, ecosystem based solution. But that's expensive as hard to put in place. The reality is it's lots of pieces of paper and emails and PDFs that are crossing over while people try and figure out what's going on.
So they implemented, uh, an agent that the first step is to analyze, you know, the PDF or the image extract the key information from that about the transactions. And then, uh, because this company is operating all around the world, it has to do things like, hmm. Are they using decimal [00:29:30] points or a comma for the fractions of the money?
And you can only redetermine that by scanning through a bunch of these different invoices. So the first thing has to do, it has to construct a data frame where it brings together the supplier information and the information from the your own ERP system. And it does that iteratively. So it actually thinks it reasons, it uses the latest models to construct that data flame and when it's confident.
That it has the data in a compatible format, [00:30:00] then it can go through and search through all of those different transactions. There could be thousands and say, out of all of these, here are the three or four that we think is causing this discrepancy that you see at the bottom. Then it passes it to a human being and who can go and check.
Or sometimes it's just, yes, this is clearly it. We're confident. This is it. And a human being can say, okay, given this level of certainty, we'll just, yes, go and do what we think. But many cases, it'll be, you know what? It's a mess. We couldn't really find out what's [00:30:30] going on. We think it's here. And then it passes it to the same experts that have always worked on this.
It just now they're only dealing with the things that the algorithms couldn't do. So it's getting rid of huge amounts of wasteful manual work. So to go back to the productivity thing, uh, the famous quick for quick for decades has been that the productivity of computing shows up everywhere except the statistics.
No, we can't rely on facts and data. Stop that. Right now. We're past [00:31:00] that age. We're past that. We don't talk about factual concepts anymore. We, we've moved on as a society. We've moved on. Just make it, you actually have a, a degree in econometrics. Uh, I've forgotten most of it, but the, one of the key things is really hard to measure, uh, better quality in productivity statistics.
It, it doesn't immediately appear in the numbers. So we do believe that a big part of it is just we're doing things better that can be hard to manage, but there's always a big lag between, uh, the technology becoming available and when it actually turns up in statistics. So, [00:31:30] FTCs, it took at least a, a decade, I believe.
Yeah, with ai. It might be faster because everything's faster. But I think the biggest issue we face in this industry is that the technology has accelerated so fast. It really is so powerful that it would take us at least a decade to get the most out of the new AI technology that we already have to adapt our processes and find new ways of working.
And of course, AI shows no sign of slowing down right now. So the biggest challenge, I believe, [00:32:00] is not so much implementing AI and finding use cases. This is something that people really want to do. Their, their boards, their CEOs are all going, you know, where are my AI benefits? But people are struggling because they have legacy systems.
They don't have the data quality they need. So one of the biggest things I'm promoting is. The ability of AI to transform transformation to AI standing for accelerating innovation. Mm-hmm. That we're actually using AI for each of those painful steps to move to the latest [00:32:30] infrastructures, move to the cloud, help us right, uh, code extensions faster, even help with change management and user adoption.
I think that's an area where people are underestimating just how much AI can help. I wanna take just a bit of a step back and just talk about the SAP product set as it's at, as it exists today. For those that are outside of the world of SAP, it can get quite confusing exactly as to, as to how it functions these days.
So I wonder if you could just paint a little bit of a pen picture about what, what the [00:33:00] sort of Cloudified version is and, and maybe how it differentiates from the on-prem version. Absolutely. So, uh, the current SAP offer is called the SAP Business Suite. It has three major components. The first is our suite of cloud native applications.
So again, success factors for hr, concur for travel, uh, Reba for, uh, procurement, and then the core ERP [00:33:30] functionality of finance and supply chain and so on. So those are all cloud applications designed to work together the same look and feel. They generate a lot of information. So we then bring all of that information together on a second layer that's called the SAP Business Data Cloud.
This was launched earlier this year, so it's a way to get a. Holistic view of all of your operations. Uh, we are working very closely with partners such as Databricks, right, to work on external information [00:34:00] because, you know, your SAP information tends to be among the most valuable data in the organization for companies using it.
But of course, there's also lots of other data sources, and we know that we need to be part of an overall data ecosystem. People already have data lakes, so that's the second layer. Business data cloud. Uh, our goal is to make it easier, simpler, faster, cheaper to use. Our consolidation layer to provide insight as a service.
Then the layer on top is, um, ai. So business ai, we're [00:34:30] using all of that data that we've gotten for our core applications to provide the grounding for business ai. So we're embedding AI into our applications. Mm-hmm. And then we have a Juul, uh, JUUL is our smart assistant front end. So it's, it's a window onto all of the functionality across all of the SAP business suite for anything you want to do.
It could be a transaction, create an open headcount and an invoice. It could be analytics, [00:35:00] you know, can you tell me the sales last week in Belgium for a particular product? So, does it mean that if, if I understand that that sketch. Correctly, sort of at the, at the sort of base layer, you've got the sort of main, uh, products, cloud native products, which, which are where you might have more structured data and more process built in, but then above that you've got sort of querying layers, effectively AI driven querying layers that then can pull all of that together and execute commands down at the [00:35:30] base layer.
Yeah, so the, the, the data layer is. Really important for that consolidated conformed view of everything that's going on in your business. Again, the key is that AI is useless unless it's based on real data in real time from your business operations. So we have all of the context of what people are doing in every particular business process, and we're using that to make sure that when you use artificial intelligence, it's actually, we have something called the UH, SAP [00:36:00] knowledge graph.
It's part of the business data cloud, and that is all of the existing relationships that you have in your organization. It could be product hierarchies or data tables. It's leveraging all of that information again to, to ground the ai. So instead of doing sort of simple rag. Type lookups. This was the first generation of AI where you'd give it a document and say, find the information you need in that document.
This is the next level where you use a, a knowledge graph. You interpret the question, you use the knowledge graph to [00:36:30] point you towards the, the real information that we then get in a structured way to make sure you actually have a right answer and then provide that to the users. And we're working very closely with other organizations like Microsoft, so that it's completely, uh, uh, bi-directional.
So if you're in teams and you wanna question that, the answer comes from SAP, it will happen, uh, automagically behind the scenes, uh, and vice versa. If you are in SAP and you want to organize a meeting between people to figure out who to hire. It'll [00:37:00] happen automagically through teams in the background.
The great thing about the data point and AI doesn't work without good data, for me personally, is the greatest I told you so moment for architects. So for years, architects have been banging on about keep your data in order, keep it well structured, understand it, tag it, make sure it's governed, you know, massive data.
Understood. Can, can't help yourself, can you? Yeah, I can't, I can't, I can't help yourself. 'cause I've been in those conversations and somebody went, ah, it'll be all right. Yeah. And then AI ros over the rise and they went, oh, if only we'd sorted out our data when that [00:37:30] architect told us, we should have sorted it out.
Well, I know the audience right now is saying, oh, you're telling me the data is important. This is not the first time I've heard this. Ah, yeah. We, we got something. It's gonna happen. It's gonna happen. And it has, and then there's a load of very happy architects walking around, going up. I did tell you, I did tell you if only they had the leadership prowess to have established it in the first place.
Rob. Oh, Dave, that's it. What it is, is the, uh, is the, um, cost. Driving the organization and not realizing the future vision. Isn't [00:38:00] it that, but it is a good point. That's true, right? The communication of the correct setup for technology to keep you in a good position for the future. This is a very so point is architects could do well to maybe articulate that better so that businesses understand the fact that if they do this, they're gonna save a lot in the long run.
But I do feel that that communication pathway is, is, uh, too complicated at times for many to be, it's like two worlds clash. Clashing together and both think they've understood it, but they haven't 'cause they haven't communicated it quite. The, the reality is it's extremely [00:38:30] hard to go to, uh, an executive, the CEO and say, I'd like several million dollars, several euros, pound to go and fix our data quality problem.
Because that's just, okay, well that's a technical thing. Where's my business benefits? I think the other thing that might happen that can change that argument, and it's driven by AI, but maybe in a slightly different way, which is I genuinely think we're heading into the age of being able to monetize your data.
So, you know, establishing yourself as an, an externally [00:39:00] queryable, but a clean and trustable data set and you sort of imagine a, an ecosystem of data sets appearing that you can then integrate, say, into your middle layer. It's, it's that, it's that we came, we're coming from a world of open data sets. I. An open connectivity for that and it's all gonna close down in the ecosystem.
So yes, it's monetization, but to what end? And are we going to lose out something because we lose access to data? 'cause somebody wants to get some money for it. [00:39:30] I mean, the reality is that, uh, right now all of the organizations that are building these large language models, they have run out of data. Mm.
They have used all of the data that is easy, accessible from public sources, Wikipedia, Reddit, everything else they can use. So the next big opportunity to provide better models is that data. That is, it's ours. It's the, the data that's in all of our organizations. Yeah. We are actually really interested in, um.
There's a, a [00:40:00] big opportunity. We believe we're doing some research right now, uh, we'll see something later this year where we're building, we're applying the, the principles of large language models, so the vectorization of the underlying information, but applying it to structured information in tables. So leveraging all of the SAP data across the SAP customer ecosystem where we have permission to create, uh, predictive [00:40:30] models based purely on structured data.
Mm-hmm. So that if you want to do things like predict whether customer X will be paying, you know, how many days late might they pay. We believe that you can do that with existing machine learning or something, but it's, it's a little bit painful to put in place. We believe that these new type of models, uh, will be a, another huge step forward in how to leverage data again overall.
So we have these three layers and we believe that there's a sort of flywheel effect where we can [00:41:00] start doing innovation faster. So because you have the great. Information from your operational systems, really good information, then you're consolidating it, make sure it's coherent, then you're using that to ground your ai.
But then the AI we allows us to create agents that improve every single one of those business applications, right? And then that in turn creates even better because we start getting really good at understanding supplier balance, reconciliation, uh, and we can make that more automatic, which we in turn [00:41:30] create a more powerful core application.
So we've got this sort of flywheel that we believe over time will help, uh, consistently improve our applications over time. I wonder if we can, um, bring our conversation today to a, a little bit of a close, but actually talk, just step back from that a second, talk about how you implement to get there. And one of the things that is difficult implementing any ERP style.
System is, has always historically been, you know, the business alignment that needs to happen. The [00:42:00] conversation around, are we gonna use it, vanilla, is it gonna be customized? What does that look like? And then if you're bringing in multiple business units or multiple geographies, everybody has a powerful opinion on what that needs to be because of what their heritage has been.
And it's, and it's historically a very difficult implementation. So it is great when you get there simplified, aligned, clear, but a difficult journey to get to it. Uh, you talked a little bit earlier about how you're using AI to implement things in future. Do [00:42:30] you see, uh, let me rephrase it. What's the path from, let's say I'm an install, I'm, I'm an installed base today.
I've got maybe last generation ERP, I've maybe got a bit of workday, a couple of other bits and pieces. How do I get from there to sort of the, the three layer. Innovation cycle that you were just talking about. Well, you know what, Dave, I really should refer you to, uh, some of our wonderful partners such as a French Hook headquartered, uh, strategic integrator that have [00:43:00] recently implemented, uh, our cloud, ERP very successfully.
You won an innovation award for it, so thank you very much for that. I'm a, I'm a judge in the SAP Innovation Awards. That's wonderful to hear. One, one of the best programs we do. Yeah, ask him for a friend. Ask him for a friend. Um, do you give out podcast awards? Yeah, yeah. Hang on. Yeah, let's, we're looking for one.
We're looking for one. Uh, so we work closely with, uh, partners yourself. So, uh, at the end of the day, we are a technology provider. We provide best [00:43:30] practice and so on. But when it comes to advising individual organizations on their journey, that's something very much that we work with folks like yourselves.
We do have two big programs, one's called rise, that's, uh, designed specifically for existing customers who have, you know, on-premise, SAP, they have a lot of existing custom code. They're trying to figure out what's the best way for them to consolidate existing systems and move to the modern cloud platforms.
And then we have another program called Grow that is focused on organizations that don't have a [00:44:00] core ERP. So this is for. You know, uh, fast growing startups or organizations that, for one reason or other, are able to move directly to the public cloud version of our software. We do believe that at the end of the day, that is the journey for all of our customers, that the public cloud version of the software is the way to go, because that's the only platform that gives you this flywheel of innovation and all the power of ai.
But for organizations with a lot of complexity, we understand that [00:44:30] that might take, uh, a while and a few steps. I was just at a. Conference we ran yesterday, business Unleashed in London, where uh, I listened to some smaller fa, smaller, faster growing organizations where, well, here's the anecdote. The, uh, the CFO, um, she had to persuade her, uh.
Uh, strategic integrator, one of the big four to that. She really wanted to go to public cloud, despite the protestations that, no, no, we need to do it. The old, the [00:45:00] the old way with, uh, we're gonna help you move your custom code to the new environment. So she insisted, and then they had the partner on stage who was able to say, yes, it was the right decision.
Clean core, as they say. So you move your code to the cloud in a way where you can then seamlessly upgrade. This is absolutely what the CFO was interested in. See, like, I don't wanna mess with upgrades, I just wanna have that all done for me. They don't have an ID it department. They rely on other partners.
They just, it's just, I want it to work. And that's very much the [00:45:30] philosophy of everything we're doing now, including, so business cloud, for example, it's not like the previous generation where E. It was technology, but you had to put it all together. We do all of that for you. So it's insight as a service where you just open it up and you get the, uh, what we call the intelligent applications.
So if you have success factors for your HR and you doing financial planning and budgeting, and you have both of those, then you click a button and it provides these data products, this sort of [00:46:00] notion of data, fabric, data mesh, and then provides you with just exactly the kinds of, uh, dashboards and report that you need as a finance person to see your.
Headcount and your financial aspects of your headcount in the, in the same interface. So that's, that's the, you know, one plus one equals three opportunity for these modular, uh, business applications.[00:46:30]
Where are you gonna go today? Well, I wanna rethink control in enterprise systems, you know, because these, these platforms have been always about stability, structure, control, uh, but if we now look into the world of ai, rapid change, growing complexity, are those still the qualities that we're actually looking for or that matter the most?
So, uh, a study of, uh, McKinsey like last year. The state of [00:47:00] AI actually shows that clear shift that we've been talking throughout the show, and I think the, the entire season already is that high performing organizations are moving beyond automation, rethinking how systems support, adaptability, trust, and collaboration between humans and intelligent tools.
But that actually sparked a reflection for me. What if enterprise software isn't just about codifying what we already know, but about creating space to respond to what we don't yet understand? And, and as, as Tim already mentioned, so maybe the business goal [00:47:30] remains the same. And I think in terms of figures, yes, we wanna growth and, you know, 10%, et cetera, et cetera, but you know.
This doesn't mean abandoning control, but it means comp, uh, complimenting it with flexibility. So not replacing ERP foundations, but evolving them to support emergence, iteration, and even vulnerability in how decisions get made. Uh, so maybe that's also where the real power lies in designing systems that not only run the business, but also helps sense what [00:48:00] business is actually coming or, you know, where we're heading towards.
Is this something that resonates Timo? How do you, how do you see this? Absolutely. I believe the future, uh, is no longer doing. And and orchestrating instead. Sorry. This is where we have a massive opportunity to accelerate innovation. Traditionally, it's always been the IT function. Who has to have, do the innovation, talk to the business people.
What innovation would you like? Okay, we'll deliver it. That is a paradigm that I think [00:48:30] is going away and we can let business people do more of the innovation themselves in their area of expertise without IT and technology being a bottleneck for the longest time, it's not like the business people don't know what they would like, it's just we haven't had the time and the skills and resources to actually deliver that innovation.
The good news is that all of these latest technologies from low code, no code now to AI allow individual business people to improve on their areas, individuals [00:49:00] as teams. And so I think that is a massive opportunity, but it's also going to be a big mindset change, as you say. People have to let go of control.
They have to let business people do this, but in a way that is governed, because otherwise it would be chaos. So finding that new balance, I think is, uh, is gonna be very important. Feels to me, like one of the things that's tricky about that unknowable future is how you, is, how you get your organization from where it is today [00:49:30] to be behaving like that and using tools in the way like that.
It's almost, you know, unless you've been thinking about this a lot and you've had the time in your day job, or you're paid to think about these things and you're just doing your day job, that's a big leap, isn't it? I wonder what sort of conversations you are having t or that is, you know, S'S concept there, you'd, you maybe just talking to a supply chain manager and you know, you, you almost have to conceptually get it over to them as well as then technically how you implement that thing.
[00:50:00] Innovation. And, uh, I'm an innovation evangelist, so obviously I talk a lot about technology, but at the end of the day, we all know that it's not about the technology, it's all about the people, the culture of the organization, the change management. That's always the hardest part. If you have time for a quick anecdote, uh, did you know that we put a man on the moon before we put wheels on luggage?
I have. Yeah. It's like, it's like such a, and, but one innovation has a lot more relevance to my life than the other. [00:50:30] Yes. I'd love to say it was the space race and that I'd done something for him, but it's not, it's four wheels on a suitcase. You know, it's just such an important, it's so he can take an enormous suitcase for a three day trip, isn't it?
Hey, yeah, let's like, but it's a very good point, isn't it? Something as simple as that occurred to us be after something so dramatic as stepping on another celestial body. It was absolutely a cultural issue because people in the 19, mid 1970s, it was mostly [00:51:00] men that traveled for business and it was considered manly to carry your own baggage.
Folks out there who have gray hair will remember that. Mm-hmm. Uh, if you didn't wanna carry your baggage, there were porters everywhere. You'd turn up at an airport and there were people who would try and grab your bags. Those of the days, uh, airports were not the beautifully smooth places they are today.
They've kind of evolved around wheels rather than the, uh, alternative. It took, it took 15 years for somebody to come up with the idea of a telescopic handle. For wheeled luggage and another 15 years after that to come up with these [00:51:30] spinner bags that you can easily work inside. I mean, I'm not a verse verse this, I wasn't expecting the, uh, the deep dive into luggage design.
I mean, you're bringing some new team, but what were people doing when it was on wheels? So just bent over pushing their suitcases. It was, it was just, so the original patent from 1972 is uh, four wheels, one on each corner, and then a simple strap and you just tugged it along behind you like a little, you can see where that would come from.
And somebody went, oh, look at this telescopic handle. Yeah, yeah. Look at that. You know why though, for tall people though, when you get a bag, maybe a small compact bi bag, the telescopic handle doesn't [00:52:00] quite come up far enough. So to go back to the point, uh, it's all about change management. It's all about people.
And as you're thinking about innovation and this moving to an environment where you are trying to get business people to think more in innovation terms and be empowered, then you have to change the way you work. So people have to feel comfortable doing that. It has to be, they have to be incented to do that.
Let's face it, most of us. They just do our job and it's, we don't really feel like it's our job to improve our job mostly. [00:52:30] Um, so there has to be incentives from outside there? Right. Especially right now. The biggest thing that leaders have to do in organizations is make sure that everybody is AI literate.
They have space spaces for trying this thing, these things out as part of their job, and that they're not, they don't think they're gonna get fired for telling their boss that they're using ai. This is actually one of the biggest things we're seeing is. There are a lot of CEOs and boards that are salivating over, uh, saving headcount.
And [00:53:00] thankfully, the data of the studies right now seems to show that the best way to implement AI is using it to augment existing people in teams of people. Because if you try and use it to replace people, guess what? Every person in that organization does not wanna take part in that, and it just blocks and you don't get the benefit just on that point of augmentation and whether organizations are yet understanding corporately the value that that brings or whether [00:53:30] they view it as cheating or whatever it might be.
I saw a great little Instagram video from, uh, some young woman who had been rejected from a job for using chat GPT as part of her application process, and, and her point was. I'm excellent at chat, GPT. It's like, I, her phrase, I use it right to its edges. Like the amount of value I can drive out of it is absolutely extraordinary.
And that's the thing mm-hmm. That you excluded me for. [00:54:00] You know, just, it just, it, I thought it perfectly encapsulated the point you're making there, Timo. So my, my daughter is 21. Um, she's at business school now and I purchased her for, for her an open, uh, open AI chat. Uh oh. Catchy BT Plus, uh, subscription.
Mm-hmm. Partly because it's a fraction of the cost of business school, but also because, uh, I really do think that yes, this next generation, they will have to bring their AI enabled skills in order to have a, [00:54:30] a place because some of the junior jobs that they would otherwise be. Planning to do is starting to be done by ai?
Very much so. Yeah. So there, it's really some big changes to demo demographics and how we do beginner work in white collar jobs. And there's, there's lots of articles out there. Nobody really knows what it's gonna look like, but it's clear that it's up to us to decide as a society. And this is perhaps one of the areas as well where I'm a proud European, where [00:55:00] I think we take a little more of a proactive approach rather than just going, eh, we'll see what happens.
I think that's spot on. I do wanna pick up on the point you were making though, about the, the implementation of these environments. Just finish off the implementation thread there in terms of how you get to the sort of environments that EZ was describing. So I think we have this wonderful opportunity for AI to stand for more automatic innovation where innovation becomes a core business [00:55:30] process itself that is optimizable and automatable.
I. So the analogy I sometimes use is right now innovation is a little bit like a staircase. You have to physically move up each step if you want to progress, and it is sort of hard work in the future. I think it will be a lot more like an escalator where you simply stand on the lower stair and then you get swept up towards the innovation future.
Because we have these massive amounts of data that are in our existing systems, it [00:56:00] sees everything that's going on in ways that people can't frankly. And then we can use artificial intelligence to make the system proactive. Tell us what we should be doing next. And we've been investing heavily in this area.
It sounds like science fiction, but we're actually starting to realize this. It sounds like a singularity about recur with technology driving advanced. Through itself. That's John von Newman's theory, wasn't it? We still believe in humans being firmly in charge, uh, with every aspect of ai. There always has to be a human in the loop.
But so for [00:56:30] in terms of products, um, folks might know SAP Signo. So this is our tool for doing process mapping. So the idea is that you can really, uh, use it to do process insights. You can run it against all of your systems. And then we have a lot of benchmarking information. So we can say, you know what, out of all of the things that you could work on right now across all of your different systems, here are the areas where you are relatively worse than other people like yourself.
So these are the areas where you can get the most ROI. [00:57:00] The quickest in terms of change. So help people create their, uh, their ROI for the business case for change. Then we have, again, best practices. So we have, you know, an S four haner and the cloud. We have what we believe the best way of doing things based on our years of like experience.
And then we have increasingly we can help use technology to implement that in the cloud. So look at your customer code. What is it doing? How much of that is do you really want to [00:57:30] keep? How much of it should is now replaced because it's now a standard functionality in the new versions and help you, uh, transcode it to the newer ways of working with, for example, SAP business technology platform.
We have cloud. A LM help you implement that. And then we also have technologies like, uh, WalkMe, a relatively recent trend, um, acquisition by SAP, which really helps individuals do use the systems to do things in the new way. And this is one of the areas that people have always struggle with. They do a round of [00:58:00] training to get people to figure out how the new system works, but it, it takes a long time and it's painful.
So Walkway is a sort of little coach that sits above the interface. Hmm. And so as people are going, you know, oh, but I've been doing the same thing for a decade, and understand the SAP, gooey, what's all this new stuff. WalkMe says here, what are you trying to do? Okay, let's step you through it. Here's how you do it, and it'll take you to the right screens and help you each step of the way.
So it really is a way of accelerating that [00:58:30] user adoption, not just for SAP. By the way, we also work with the other platforms. I think, uh, Salesforce was actually their biggest customer before the acquisition. Cool. So we have this circle of innovation that, again, it's like the escalator. Increasingly the systems are gonna help you do this more and more and, and, uh, automatically.
We also have Lean IX for the enterprise architects. So you've got the As is. Um, infrastructure, your two B, and it helps you map from one to the other. [00:59:00] Very good. Before Rob deep dives on current state and future state architecture. Let's, uh, wrap that up for today. Oh, Dave, I was in the wings waiting to come in.
You, you've denied me my opportunity. I could sense the level four energy. So Rob, maybe we can have another discussion sometime about the use of AI specifically for enterprise architects. I think that is a fascinat think, I think I'm gonna be ill that day about you. It'll be a separate show. It could be Rob's first solo.
See, see Dave, what you [00:59:30] can't get is the necessary evil associated with architects. That's the problem, isn't it? We are actually about that. We are actually pivotal to all of this stuff. You just don't like to admit it. Best pivotal. Anyway, Timo, thank you so much for, uh, joining us today and, uh, giving us such a thorough overview of the, of, of the current state, uh, of the world in SAP language.
So it was, uh, it was very insightful. Thank you for that. Pleasure for having the conversations. Thank you so much for letting me take part. Now, we [01:00:00] end every episode of this podcast by asking our guests what they're excited about doing next, and that could be a beautiful brunch sitting outside of a gorgeous little corner cafe in the wonderful city of Paris.
Or it could be something in your professional life. So Timo, what are you excited about doing next? So this is, uh, I'm right in the middle of the conference season for me. So this big, like two or three events every week. So the next event that I'm excited about is, uh, next week I'm going to Munich for an SAP financial services, uh, conference.
[01:00:30] So I'll be hosting and moderating and we get to talk about AI for fintechs, banks, and insurance. So that is what I'm currently excited about. I would've gone for the brunch at the cafe, but I mean, that sounds gross. I get to do that every day. I'm embarrassed. Exactly. Fair enough. All of your, if, if we just ask the sequence of what you're excited by this, all of them would involve food with you.
I mean, come on and drinks One of the joys of life, isn't it? Yeah. In fact, if there was a bar that only served like old fashioned and steaks, [01:01:00] yeah, you're done. You're done. Yeah. I mean, come on. You'd never see him again. Timo. You'd never see him. He'd never see the light of day. That'd be it. His end. His end game.
It would be terrific, wouldn't it? It would be terrific. Anyway, Timo, we wish you well at the conference. I'm sure is going to be a blinder. Thank you very much. If you would like to discuss any of the issues on this week's show and how they might impact you and your business, please get in touch with us at Cloud [e-mail].
We're all on LinkedIn and now also on Substack, where [01:01:30] we are extending the conversation with key takeaways behind the scene, reflections and thought experiments. So look us up and subscribe to get the latest insights. We'd love to hear from you, so feel free to connect in DM if you have any questions for the show to tackle.
And of course, please read and subscribe to our podcast. It really helps us improve the show. A huge thanks to Timo. As sound and editing visit Ben and Louis, our producer, Marcel, and of course to all our listeners. See you in another reality next [01:02:00] week.