Rewiring Automotive Retail

Speaker A: Welcome to the Executive Insights Podcast brought to you by aws, where we address vital questions and share unique perspectives from leaders at the intersection of business and technology.

Speaker B: Hello, this is Tanuja Randery, Managing Director of Europe, Middle east and Africa for Amazon Web Services. Welcome to another episode of Executive insights, our, uh, CEO series. In this series, I will be speaking with CEOs from across the EMEA region about what it takes to transform business and society, how they are leveraging data and technology to accelerate growth and innovate, and their insights on topics such as sustainability and addressing the digital skills gap. We will also be providing a glimpse into the personalities behind some of our great leaders of industry. Now, every time someone walks into a car dealership in Europe, books a service or signs a finance agreement, there's a good chance the software behind that experience has been built by the company. Led by today's guest, that company is Nextlane. Operating across 11 countries with more than 10,000 customers and over 70,000 end users, Nextlane plays a central role in the automotive retail ecosystem. It brings together systems, products and markets into a single platform designed to simplify how dealerships and manufacturers operate. And it is doing so at a moment when the industry is navigating a period of real structural change. Leading that transformation as executive with more than 25 years of experience building and scaling technology businesses across multiple geographies and markets. Hartman Wagner, welcome to Executive Insights, and thank you so much for taking the time to join us today.

Speaker C: Hi, Tanusha. Thank you very much for inviting and having me. Pleasure to be here.

Speaker B: Well, I'm really looking forward to diving into some of your experience in a very interesting industry. But before we do that, I understand that you are a marathon runner, triathlons, the whole thing. So you know what kilometer 30 feels like. And I'm sure the finish line isn't quite where everyone thought it would be. And in some ways, the European automotive industry right now feels like it might be somewhere around that mark. Right? Whether it's emissions targets or electrification or of course, the digital transformation we're living in. What do you, before we go there, tell yourself when you're almost there, what do you think the industry is also telling itself right now?

Speaker C: Yeah, I love sports and the 30 kilometer point is an interesting mark. But I have to say, 37 is for me actually the one where everything feels so painful and when you really need to go for plan B, C and so on. But first, talking about the industry, you are right. I mean, we all see in the last few years an interesting transformation. I would even say a disruption of that automotive industry. And I think it's driven by many external drivers. Obviously political situations are driving, I would say some unclarity. So there's not the ultimate clarity where things go with regards to electrification or the next thing of how cars will drive in the future. But even more important, you see that the strategy of many of the traditional OEMs or car manufacturers has not foreseen some of these new requirements. So they really are uncertain in terms of the direction they should go. And you have obviously Chinese OEMs that they're quickly rising, quickly developing, they have a long term plan. The others try to understand what the direction is and how they can react to it. But it seems they are not properly prepared for this.

Speaker B: Obviously you sit right in the center actually of the European ecosystem connecting these OEMs, two dealers. Is that position shaping in some ways the way you think about where the market's heading. Because you've got, you know, you've got really this very special role. What are one or two things that you're actually seeing here in Europe?

Speaker C: I mean we're like in the, how we call it in the ecosystem. Yeah. And the interesting thing is that while the OEMs are uh, in this transformation journey, literally figuring out where things go to, you see that also the relationship between dealers and OEMs has massively changed. So, so years ago we were used to the fact that there was like a dealer for one brand, another dealer for the next brand, another dealer for this. So there were long term relationships between dealer or dealer groups and brands. And in the last years most of these relationships have completely broken. They were made lots of acquisitions. Um, many of the OEMs even sold their complete go to market parts to dealer groups. So literally now you see one dealer is going for multi brand plus the new brands. So there's no long term standing relationship anymore. And every entity in all of this is literally thinking about itself. How can I survive, how can I further sell new car used cars and how to really drive the profit I need to survive in the long term to give my employees a good job and on top. And that's another angle of complexity is that in the past most of the new cars were literally sold via uh, a shop. You went to a dealer, you bought a car. There's now all around the direct sales from OI end to end customer. So they dream about controlling the whole process towards the end customer. Obviously they might like it, but dealers don't like it. Yeah. So you see there are a Number of trends and things going on which drive a lot of tension, uncertainty and the need for change within that industry. And especially in Europe where these new like Tesla or the Chinese and the traditional ones, especially the German and French manufacturers are literally colliding in the same markets.

Speaker B: Now you're right, the whole direct to consumer thing, you're not the only industry. I mean it's happening in multiple industries, uh, across the board. You know, when you think about European dealers, how do you think they are set up for success? Like I understand, by the way, a lot of them are still very much running on, you know, legacy platforms and technology. The shift to SaaS is a significant undertaking and of course with generative AI it's even more so. What does it take for them to actually go through that transition?

Speaker C: The first point is that when you talk about a European dealer, we need to be aware that this means certainly a small garage in Switzerland with three or four employees on one hand, on the other hand this might be a multi country group of 20,000 and more employees, a true enterprise. And they are obviously facing very different challenges and opportunities in this whole market context. So when you look into more the mid size and large dealers, they all serve multiple brands, they all serve multiple countries and that obviously means they need to adopt. Now when you want to adopt, obviously it plays a core role. You need to adopt via interfaces to the systems of the OEMs. Most OEMs have for the same use case different interfaces in each single European country. So there's no standard in place. So that means one brand and you sell uh, cars for that brand in five countries for one use case you have five XD interfaces. So when you think about this, a large group has hundreds of interfaces to be in place to maintain and support and that gives you already a sense for, for the complexity they have. On top of that, automotive is more traditional industry. So when we talk about the latest trends like AI, public cloud and so on, you still see that sometimes you need to really do an education, you really need to explain, okay, what are uh, the benefits from this? Because their reality looks around old systems, legacy software, isolated software, this is not all implemented, not all integrated to consume it easily and nicely, which obviously is a burden to maintain it, but it also a burden with regards to adopting to the latest trends and to be fast on reacting to market trends. And that's a core challenge that most of these top 20 top 50 European dealer groups face these days.

Speaker B: Whilst on the one hand you point out these challenges, you've actually adopted this incredible like sort of modernization agenda. Very much thinking about how you build scalable, more connected, more intelligent automotive software platforms. Yeah, I'd love to understand kind of your next lane strategy. Why is this so important, this technology transformation, which of course in the end underpins business transformation. It's not about the technology alone.

Speaker C: It's good to hear that you see us really moving fast on this. Right. It's also one of the reasons, I think, why we really built and extending this partnership with aws. Uh, because when you look into this, um, you see that on one hand you have legacy systems, then you see dealers or your customers acquiring other dealers, and they even try to integrate or making these legacy systems talking to each other. On the other hand, you have new cloud products, then you have, let's say, these big OEMs with large IT organizations across the globe, and then you obviously have your own products. Right. So it was like a few years ago a logical step to say we build a cloud integration platform in place where first we integrated our own products into it, but then also started whenever we sold a product, or we implement with dealers or OEMs, all implementations, all integrations, getting always done via the cloud. So you get away from this product to product integration, which can be difficult if a product is 15, 20, 30 years old and you get to a level of scalability. And the more you have connected via the cloud, the more you are in a position to modernize, but also to literally easy connect new cloud stuff, modern architecture with old systems. And at the end, if you then even are, uh, open for other partners, other players in the market, you build what we call an open ecosystem. So you make it easy for dealers to consume multiple products from multiple vendors in one way to the benefit that they can run their business better. We have to do it because the only way in the long term to be a good partner, to be successful in the mud, and to really show our customers that they are in a good spot, not just for today, tomorrow, but really for multiple years. I really believe if you don't do it earlier or later, you're running into an absolute problem. And then it might be too late, given everything else has accelerated so much and you are really behind your competitors, the brands and other dealer groups.

Speaker B: I do agree with you. I think it is not an option anymore, is it? I mean, you know, particularly now as companies, uh, and you yourself become more AI first, not even just cloud first. It's cloud and AI. We see a difference between those who use AI on a more basic level because they haven't done some of that core foundational work and those like you that are using it more in an advanced level, the difference in productivity savings is incredible. It's like between 40 and to 65%. So those savings can then be reinvested in really driving then the next stages of your growth. Right. I'd love to understand by the way, on that front, like how do you think about generative AI in your industry

Speaker C: in times like this where the industry is in a big change of transformation, in a big, I would say under pressure, cost wise, um, new car sales numbers slightly going down. You see that profitability is becoming a core need of most dealers. The bigger they are, the bigger the need is. And profitability comes via digitalization. This comes via uh, efficiency driving. And AI is a core element to do this. However, we also learned that if we meet dealers today and we talk about AI as like the new cool kit, uh, then they don't connect it with the value they really get from it. But we learned to not make this tech talk. But we translated into all, hey, look, value. Yeah, here's what you can do in selling more cars. Here's what you can do to literally do better used car business. So here's what you can do to sell and deliver more services to your existing customers. And how we do it is with this product or use case. And yes, this is driven by AI. And then they get the logic, they get this value chain and then you translate our, I would say tech driven language into more customer, um, business value, language and understanding and that flies. And I think the key learning is technology is one end, but the big piece is obviously the human beings, the people. Because there's a mental readiness I think you need to create that. People feel comfortable with it. They are getting curious, they start to embrace to better understand, playing around. And then you see this really accelerating like a snowball effect. And suddenly the central effort of oh, we want to get into better AI becomes into a decentrally driven model because people pull it in the direction they need it.

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Speaker B: now in next claim. As you're going through it and you are built up through many acquisitions as well, different teams, different ways of working, how are you creating that culture of innovation and that mindset within your own businesses?

Speaker C: You said something important beginning, right? We were grown, driven by uh, many acquisitions. So when I joined like more than two and a half years ago, the first Goal was really okay, make it one. So this is one company, one culture, one set of applications we use, one way of working, etc. I don't think we are perfect, but we are getting pretty good on this now. When we started with AI, I think the first moment was actually for me to really understand it. I'm always challenging myself to really understand, okay, what is the value. And I think the first thing I understood very quickly is that speed matters, right? First you tend to say, yeah, look, we have time, we will figure it out, let's see. But then everybody who is already on that journey tells you, hey Hartmut, that's the wrong assumption. It will always be faster than you think. That was number one, the big learning for myself. And then it was obviously around, okay, how do we get the company or the people getting into the same experience so that they act against it? I think it's really around, okay, culture. How do we want to work? We are a software company, a cloud company. We want to be curious, we want to be innovative, we want to empower. So we reconfirmed the values first of how we really want to act, how we want to serve our customers. And then we did literally a rollout. Leadership team, senior leaders, all managers, all people. And we started to centrally do some little experiments, pilots on a voluntary basis. We also explained, look, this is why we want to go on this journey. And it's not about letting people go and replacing a human being by AI. I said, look, this is really around enabling you to do a better job. It's enabling you to drive more success for yourself, but also for your customers. And then obviously you have to prove this right. And we then built up a few use cases, references we shared heavily, we communicated. And then you see more and more people buying into this, literally going also on the journey. And it's creating this excitement about AI and its value and it's not anymore something, oh, the company is asking us to do it, it becomes natural. Uh, and that's I guess a core next step in the evolution.

Speaker B: We probably don't even know what this new technology will create in terms of new experiences and new ideas. But you're right, getting everyone to really adopt, learn, use it, giving them the flexibility and the optionality to be able to try different things and at the same time also having one or three areas where you are prioritizing big, significant needle moving, impactful spaces that you're working on because otherwise you can end up also with too much experimentation, not enough as you embed the core culture across the organization, what are the one or two really kind of call it big areas that you as CEO are saying, hey, this is where we need to over rotate and put the resources to drive the impact that we need to have whilst we do all the rest.

Speaker C: Yeah, I mean when you simplify what we do, I mean we build software, we sell software and we deliver software. Right. So obviously building products, driving innovation is an absolute core element of every software and cloud company on this planet. And this is where we make really big bets. We are completely reshaping the way how we develop products now we have obviously core or legacy products, older architectures, and there, I would say there's a limited element here you can modernize, like AWS transform as an example. Why you can modernize, but then you have, obviously you build new products, new technologies and everything that is new is simply completely driven, developed by AI. So that also means we hire different engineers. Right. It's not anymore, um, around the engineer doing the coding. Now the engineer is becoming more a coach of the AI partner to literally get the software developed. And I think this is one big focus area with a lot of investment every single week. The other one is really, um, go to market, driving leads, generating leads, selling. Um, there is so much you can do around content, content creation, leveraging this content in a smart way. So these are two main areas where we heavily invest, learn, help our people to get better, we coach them because this makes a differ difference. Right. This is where you either win or lose. And that's the same for us like it is for a car dealer, like it is for a car manufacturer. If they are not stepping up heavily on these things, I don't think they will survive.

Speaker B: I think the two things you mentioned are so key. And by the way, I do believe that it's pretty reflective of most industries at one level actually because, you know, we always think there's three major areas where AI can make a phenomenal impact. The first is, as you see in the core of product innovation, engineering, coding, all that related to software development, you know, lifecycle management, et cetera and their tools today, whether it's cloud code or whether it's, you know, our Kira platform or any of that are uh, the way that people are completely rethinking the way they code. And then the second big one is as you say, the customer m experience transformation, whatever the channel is, however you approach that customer, how you rethinking that relationship in a completely different way. And then I think the third is kind of everything to do with the middle Office, Right. Knowledge management, there's compliance related things, regulatory documents your employees need to query, all kinds of questions. I mean there's just so much productivity. And by the way, not just productivity, I think for employees it's a simplification

Speaker C: given you to say it. I mean we are in the process of opening a new customer center in Portugal and every Friday we have like a drumbeat. And the core topic is knowledge transfer. Knowledge management, because that's the critical element in it, right? And there are already, I think six, seven AI driven agents initiatives, all under roof of knowledge transfer going on. So this topic will be pretty much driven by AI, I would say 80% plus already, I would say in four to eight weeks from now. And then you see the scope of content, the scope of work you can get done in a smart way, that you give the right content at the right time to the right person is just, I mean, almost undoable with a regular traditional approach. Or you would need a big team in place to really get it done. It's a wonderful example. I agree with you. I mean we see this coming to life still not fully there, but very soon. And um, can't wait to see the results of it.

Speaker B: You've said many times, and I think you're so spot on, I mean we all would agree with this, is that, you know, an organization's success is ultimately a function of its people. And you know, as a CEO leading dramatic transformation, how do you balance the uh, people side of these with the difficult decisions that have to also come with large scale change? You know, any advice maybe for other CEOs as they're listening to you?

Speaker C: I mean, it's all about the people at the end, isn't it? Sometimes we forget that because we are also driven by technology, by speed, by investors, by customers, by boards and so on. And sometimes I think you don't have enough focus really on, okay, how is all of this happening at the end? A, uh, big group of people like aiming to the same goal, the same North Star, working in certain agreements set by KPI's goals and objectives, helping each other every day so their customers are successful. So I think it's kind of logical that really people is the core element. However, especially with AI, I think then it also gets to the surface, uh, because you see the concerns, you see these fears of some people when it's around AI, uh, because they always wonder, whoa, where does this go? So from my perspective, the best thing is just being yourself. Don't hide behind a role or behind a title. Don't make it too artificial, don't make it too high level. Just explain why we do things, explain why it makes sense, explain what you expect, but also say, look, I think these are the opportunities. Oh, there might also be challenges, and today nobody really knows. But we will figure it out together. On one end, you build trust and you keep a, uh, respected relationship with everybody. But also you say, look, I also don't know everything. How could I? We are all learning. And I guess then you get a good dynamic in place where people feel comfortable, they understand, okay, I might make a mistake, fine, that happens. I learned from it, then I continue, and then the whole organization, I think, starts to go in the right direction. But it's not about titles. I think it's just about a group of people working successfully together and sharing learnings, insights and experiences. That's how I approach it. And for me, it's the only logical choice to act like that. But I guess we all have our different styles and beliefs at the end now.

Speaker B: I love that there's a lot you said there around, you know, earning trust, building psychologically safe environments, making it possible with mechanisms to encourage experimentation at scale. You know, I think there's just all these balances that as leaders, we have to make. Thank you, Hafmed. It's been a really fun and inspiring conversation and thank you for being so open and sharing, you know, about your own style and things you've done. Uh, I can't wait to continue what we're doing with you, you and see what's to come.

Speaker C: Tanusha, thank you so much. Big pleasure being here and can't wait to continue the partnership and going to the next level of adventures between AWS and Nextlane. Thank you so much for the invite for being here.

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