TomTom N.V. (AMS:TOM2)

Investor Day 2019

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Sep 24, 2019

And I'm also just seeing So we have a a tighter surgery. You have to get a red light on it. That was speakers. I I believe it was a good idea to get the offer we have souls. Locations that come in. I think you do moments in time to, give you are and tell the We are a and what simplifies the business model. I think what was uniquely positioned in that you can feel the central role locating the home's text. You go with that. We have been beating our customers. We put a camera to the daytime. We don't lose data the what the location tenants wrote? So, for example, explain where trading the business protocol and how we're going to exploit the big trends that have not been in location. And as a subset of the location, what happens in the middle of the military. We, So with the application there. We were marched hopefully instead, after this forced, we're using our states, our health care services systems. Make sense and amendments to the mid to wrap it up. And we can play this role because we have because it hasn't had we lost 5 news in a very efficient manufacturing platform. It's a setting on the agenda that we can continue to be updated and that does not have to do best processing or having to release data non translational services. It didn't fit the state and that's, completed risk of software, risk he needs to be done at some time until we do the same programs. I know because it's just faster, and this continues. The way for automation. And that's the next phase in our mapmaking journey is to automate more and more of the manual labor. So if you go back 10 years ago, then you could say map making was a very laborious, exercise. It was a matter of bumps on seats, more maps, and better maps meant more people. There was a, a straight relationship between that. But increasingly, we start to dig into all sorts of data sources that are there in the public domain, to be generating ourself, And we write all sorts of software to extract maximum value of that. And that allows us to get better maps, make them fresher and reduce our cost. And I think that's a very critical component. It is a, it's a, a way of, you know, if he spent less money on maintaining and building the map we can spend more on innovation and differentiating technologies and applications. We can only do that because of our people. We understand, like, all leading and success to take all the companies that you can only be as good as your people. And we can go to great lengths of making sure that the talent we, hire, that we retain them, and we train them, and we advance their careers, help them to get better at what they're doing, but that's not only it. We also have a organization structure that is flat, as flat as we can possibly get it. And we try to make an effort of putting the decision making power as low in the organization as possible. So we give leaders control over the input and the output, within boundaries, of course, you need to earn that trust. You need to earn that capability. But if you do, can go a long way within TomTom without being slowed down by red tape or all sorts of things that are non value at And I think that's one of the reasons why people like working for us and coming to TomTom. We have, every year, we get about 80,000 applications people want to work with us. That doesn't mean it's easy to attract talent, but we are an attractive employer. And I think we are enjoying, very good attrition rates as well. So certainly compared to the industry averages I think we're doing better than most. And when you ask people what, you know, what they like about talking to women and why they recommend other people to work for us, then the first thing that come up is culture. People like the culture. It's an entrepreneurial, fast moving, culture where you can actually make a difference and where you can get stuff done. And that is important for a type of people and the type of talent we want to attract. I think the other thing that is really important and not very well understood, is that we have a strong heritage in consumer applications. We know, and we've learned early on how to talk to consumers, how to develop applications that are charming, that are engaging, and that are, you know, that are fast and that meet end user requirements. And we've learned that obviously in the personal navigation device market, and we are making a point to keep and hang on to that knowledge and that experience, in order to test, hardware, to harden hardware, but also to see what works and what doesn't work. And that's a very important part of our DNA and of our heritage. And we use that knowledge and that experience to very good, results in the automotive industry that typically is a little bit behind cutting edge technology, but are also looking for partners that understand end user behavior. And end user products. We, we, we try to do the same thing with, products that are less that don't have an end user interface, but where we also want to learn how our customers are interacting and using that. And that is especially true for HD mapping. HD mapping is a new technology. It's it's got actually, it's a different representation of reality of the world, It's high fidelity. It's 3 d. But end users don't see it. It's somewhere in the silver box in a car, driving, being, and it's part of a larger, system. But in order to understand the working of that system, We've also also invested in our own self driving car, and it's parked in front of the building. It's a fully fledged, certified, level 5 self driving car. And we have built that, not to, build, autonomous driving car ourselves, but really get a good and deep understanding of what it takes to build those cars, what the sensors are giving you how our map interacts with that complete system. And we can, and we use this car, and the test environment that comes with is also to counsel our customers in the automotive industry to tell them what works, what doesn't work, and tell them results about accuracy, reliability, and so on and so forth. So again, we're not building our own self driving stack, but we've gotten a great length of testing our own products eating our own dog food, if you like. That, you know, that being at the front, the cutting edge of technology has helped us in the last 5 years or the last 10 years, I would say, to build very strong relationships with cutting edge companies, leading technologies, mostly on the West Coast. You see the logo of a few of them, Microsoft, Uber, Verizon, Apple, and there are more. And those companies are at a strong line of technology, technological development. And to be honest, they don't suffer fools easily, and it helps us to keep to, to get on our toes, to work very hard to keep up the pace and learn and understand what's happening, especially on the West Coast. So we can separate the hype from what's real. We can understand trends at an early stage, and, and have good visibility privileged visibility on what's happening in the industry at large and in the location technology industry in particular. And it's not only that we learn, from those customers, but those customers are also actively contributing to make our products better. We'll talk about that later, but for most of our customers, we get a form of data, that we can process and extract value from that data. And we've also entered recently with a number of our customers, editing partnerships where they can directly added content in the map database that will then become available to everyone, and everybody wins from that. We have a better product at lower cost. I think it's a very important flywheel effect that we will encourage in the years to come. There's a lot of companies who want access to location data, build location applications. And it's a, one of our strategic objectives to make better a lower cost in order to save those customers in a very efficient way, and we want to put ourselves in the midst of that location evolving location, ecosystem. We can do that again because we are norm threatening we are independent. We don't compete with our customers. We don't use data. From our customers to fuel alternative business models and that makes us a trusted partner. As a result of that, we've also managed to expand our market share in the automotive industry very significant over the last couple of years. So we've won businesses in North America, Asia, Europe, and so on and so forth. We have a couple of very strong including traffic information where in Europe, we have about 80% market share and 40% market share in North America, which is growing and we've won significant deals for traffic information in North America in the last couple of years. So that is all heading in the right direction. If I look at the, at the markets that we're operating in, it doesn't come as a surprise to you that the world is happening now. And that is, exciting. It's also guess, of course, there's a lot of fluidity, a lot of uncertainty in those periods of transition. But we feel we're very well equipped to deal with whatever that's thrown at us. That is because our technology is in very good shape. We have a strong balance sheet and we already have leading positions in some of those markets. The 4 themes where we where we are playing, obviously, in the mapping ecosystem, where we increasingly want to partner with customers or clients, not only to generate income, but also to collect data and put ourselves in the midst of that mapping ecosystem. And I think that's a very exciting opportunity, and we're making good inroads there. Alan will tell you later how that translates in efficiency, productivity and costs for map making. In the car is a little happening, as you know, I don't think I tell you a secret when I say that the embedded software that is now being shipped in most cars did not quite live up to end user expectations. And the industry is understanding that is making up for lost time and understand that in order to keep up with the smartphone world and user expectations, things need to be different, and that means that cars will go online. That's a big trend that we're seeing and our technology is different, user interfaces for, for the radio and for the HVAC, for the anti collision system, and for the, you know, the overtaking, warning and so on and so forth is all separated and distributed through the car. That's out. What is in is a more unified, consistent clear user interface that takes all that sensor information and all that information to the car and present that in an ambiguous UI that is easy to understand, that is not distracting, and it's adding to safety. We understand that We are working on products that we will show and Kaes Van Duck, our chief, product officer will show you some of the thinking that goes into these type of products. And getting a unified and safe user interface in the vehicle. The other trends that we're seeing is is automated driving. And and although the the the hype has come down a little bit and the noise has come down and expectations are now a little bit more realistic. Don't make any mistake. Automated driving is happening. It's here to stay there's an enormous amount of effort being put into technology together to work, and we are playing our role in that system with an HD Map product that is leading. We have proved that system is leading because we won 2 big deals from large, carmakers, 1 in Japan, 1 in North America. And we will shortly see our first commercial products for HD mapping in the, installed in the vehicles. But before that, there is ADAS, of course, assisted, driver, assisting systems, that train that, that train has really left the station, and we already started to generate significant income from ADAS capabilities that are part of our map content. The last area where we want to play is to map API business. And that's based services delivered to software developers who want to location enable their own applications. That's for us still a small market. And we are quickly maturing our product portfolio. But it's important to understand that most of the technologies we're developing now are developed in the forms of APIs and where they end up as an end user facing product in a vehicle, or as a more naked API in a third party application, doesn't make that much difference. So there's a, a, a, a, a big, synergy between our core technology development that's taking place and being able to serve the developer world through Maps APIs, and we talk about it in more detail later as well. And I'm very happy that Chris Pendleton from Microsoft this year to show you what we are doing. The, there are, you know, that so, so I want to spend a little bit of time with some proof points to show you that that strategy is really delivering business result. So in our connected navigation space, electric vehicle solutions, we have announced earlier, this year, deals with Volkswagen, with Nissan, with FCA, and with MG. As a clear sign that there is traction in the marketplace. We are integrating our in vehicle technology with, Microsoft connected vehicle platform. And in combination, we can offer the full stack of the end car user experience and, and, and what's happening in the cloud for authentication for data analytics, and so on and so forth. And I think it's a very promising partnership that we will develop over the years to come, where we, in combination, cover the whole range technologies to make that connected car a reality. As I said earlier in automated driving, we've won 2 deals, And that is at this stage of the market development very important to us, because for the first time, we will get real user feedback from commercial available products. And that is, helps us to understand how our products are used and harden the technology and get better based real user feedback in the marketplace. It's also a very important proof points to other carmakers that need to make a decision about the deployment of HD maps in their vehicles. There's a tendency, of course, to go with what's proven in the marketplace. And the third reason why this is really important is that it will give us for the first time, sends our data that will come back into our system at scale. And that will help us to keep those IG maps fresh, over high quality, and eventually, it will lead to self healing, aging maps, where the whole process of change detection and fixing maps can be automated to a large degree. MEMF's APIs, I spoke to that as well. There's also proof that that's starting to work with our partnership with, Microsoft would also throw our own API store where we are serving software developers who want to location enable their own application. So I'm very proud of what we have achieved as a team and as a business. We've gone through multiple changes. You've seen that. But I feel that we are in a very good position. We have a strong product road map, and we have a fantastic team and a strong balance sheet we generating cash, and I think we are at an excellent position to capture the opportunities that will open up over the next years, both midterm, but certainly in the longer term. The independent nature of our company allows us to put our customers and end users first. And again, the data we are collecting is solely used to improve our own products and not to feed alternative business models. And that is why we are trusted partner with so many AAA companies in the world. Throughout the rest of the day, we will elaborate on this topic, so we'll go deeper on every vertical. So you get a better idea of what's going on, and you can visualize the progress that we're making. Very happy that some of our customers will give you an outside perspective of what we're doing. And what it is, what it means to work with TomTom as a partner. My name is Art Fitzgerald. I've been with the company since the IPO in 2005. And, I want to take you through the financial model. We'll start with revenue. Then touch on the, gross margin. The next step is to look at the balance sheet also following up on what Harold is talking about about the facets of content and continuously releasable software. And the implications that that has on our capitalization amortization practices, then, look at are spent, how do we spend our money, what are the trends, where we will spend more, and where we will spend less, The next one is to look at, automotive, backlog. It's a new KPI that we have introduced today. Also touch on enterprise and then conclude, with the outlook. Tontum acquired T Laddlers in, in 2008, we announced in 2007. We acquired in 2008. And if you look at, where we were in the 1st year, where we had fully integrated TL Atlas then, a lot has changed. So if you look at the revenue perspective, 10 years ago, almost 90% of our revenue was, coming from hardware. And today, it has flipped and, morning and then 70% or 2 thirds of our revenue is coming from software. And why is that important? Because software tends to be more sticky, where we sell software, we do that with long term contract and we have a deep integration into our customers' products. And the other thing that comes with software is that it has higher gross margins mostly, and that is also the case with Tungsten. So 10 years ago, we, our gross margin was, south of 50% and today, We expect the gross margin to reach, north of 70% for 2019, and we expect that trend to continue. The technology that we are developing and also the product that we're selling is changing. So the freshness of content has materially changed and not only because, we are able to do that, but also the requirement of our customers is changing, for for the pure driver navigation, the freshness is different than where we look into the future where you have autonomous driving where it refreshes and the accuracy of the content needs to go up, significantly. Not only the content, but also on the application layer, we are making changes. So we are moving from embedded software to continuously releasable software. And that has had its effect on our capitalization practices, which we announced, during our Q2 results. So we will capitalize less, a lot less. And what we capitalize, we put, shorter on our balance sheet. So the longest, is now 6 year where it used to be, beyond 10 years. So we will capitalize less and we will, amortize it also quicker. And there's a bit of a catch up to be done, where that's related to detailed Atlas acquisition, where we were still planning to amortize for another 10 years, we'll do that in an accelerated manner in the next 2 years. You can see that in this slide. So our, intangible asset position, was, just shy of 700,000,000, but through the, false amortization of close to 300,000,000, we think that we can end up just under $500,000,000 by the end of the year. Next year, we'll do another, acceleration of our amortization So it will bring us just above 200. And after that year, you will see a new normal of the of amortization and capitalization. The D and A will obviously continue to decline and will, at a certain point, find the same value as a CapEx. So how do we spend it? If you look at, the slides on, on, on the left hand side, you see what we are expected to spend in cash, from a cash point of view. This year. That's an increase of 17%. There's a disclaimer on this slide that we don't think this trend will continue, so don't worry, we will not increase with 17% every year, but we've seen this increase, we have made the necessary steps that are, required in our application layer and also in engineering. If you zoom in more in this cash spend, it's 500,000,000 plus, then roughly 2 third of that is, coming from R&D. The remainder, 30% is SG And A, and then, 5% for, marketing. Zooming in to that, R and D spend you could divide that in the application layer that is 30% and 70% coming from content. And within content, and that is what's held already told us, this morning. There's also a trend towards less spend on, the sourcing to getting, the sources, processing the sources, less human touch, more automation, for faster cycle times, lower latency and more spending on the engineering to make all of that machine learning, learning, learning from artificial intelligence and the possibilities that, that can bring us. On the right hand side, at the bottom, again, cash spends will is expected to go up in the coming years, but that's March slower space than we have seen. Then automotive backlog. So, when talking to investors and our analysts, we we've learned that, just refining the, the 1 year guidance and also the order intake, is makes it difficult to predict the future. So today, we have introduced the Automotive backlog. And this will replace the order intake going forward. So today, we will announce the, automotive backlog. And, in February, we will give an update, and we'll do that every February when we, publish our full year results. So what you can see here is and, a number of caveats. So when we have an award, if we have signed a contract, it almost never happens that we have, committed purchasing, in there. So also not volumes. This is an estimate, of the automotive customers of the car sales, coupled with the take rates and the agreed pricing. So the actual results that we will present, for example, in 2021 will differ. And why we'll differ? Because on the one hand, we will reassess the future recordly at least once a quarter. So what we see in our backlog can change. And the other thing, and that is positive, obviously, is that we will add deals to the 2021 picture. And it's less the case, obviously, for the H2 2019, because that we're, we're almost done for the year. So this is a fair estimate of, where IFRS revenue will end up in 2019. If we then, publish the update in February, how to interpret the update is that if you compare it with what we said today, and you look at the delta, there are 3 trends. 1 is the, reported revenue in between, so in H2. The order intake and the number 3 is the contract reassessment payer contracts. Related to IFRS 50. Enterprise revenue, we don't have a backlog, as already explained by Harold This is very sticky business, long, long tenor, tends to be, all you can eat, fixed contract, based on the size and based on the value that we bring to, our customers. But you will see shifts, on one hand, because lots of these customers are, in the U. S, and it's, their contracts tend to be dollar denominated. So there's a four x angle, but the other difference can be if we lose a client or if we expand or introduce new clients, what we have seen this year with Microsoft. So, that's also the reason why the the new normal of revenue is, trending towards 160 for this year. And today's revenue is is the best indicator for future revenue, due to the nature of the contracts. Then to conclude, we're, we're looking at the outlook. So, to start with the the revenue picture for 2018 until 2021, we expect a CAGR of 10% bringing us to half a 1,000,000,000. This is location technology only, so it's excluding the revenue that, that will come in from consumer. And beyond that, and that will be underpinned by the presentations that you will hear today as well, we see an acceleration of growth, towards 15%. So 15% is the midpoint of, of the $1,500,000,000 $2,000,000,000 that's displayed on this slide. On cash flow, what's important for our business, also important for our customers is that we remain profitable due to all the accountings going through the P and L, the accelerated amortization defer in revenue and will have you, we focus on, free cash flow. And our long term or sorry, our midterm aim is to bring that to a double digit number. Also at the balance sheet, our balance sheet is fairly healthy. Combined with the addition of the free cash flow, we are constantly reassessing that position. 4 months ago, we gave back $750,000,000 to our shareholders. We will reassess that again next year, And that can lead amongst other things too in, in the share buyback. Hi. Good morning. I'm a member of the Managed import, but more importantly, I make maps. I have been making maps for over 35 years. I'm still very passionate about it and, especially because, the evolution over the past 5 years has been tremendous. There's a lot of technology that came in on mapmaking world technology that has one aim only and that is to make our maps better, to make sure that we can deliver them faster and to make sure also that we deliver those maps at low cost. What you see here on the screen is not an animated map. And it's key from our presentation to explain briefly what is this. This is probe data. It's the amount of probe data that we collect. And in this case, Amsterdam, and you see actually the map building up of Amsterdam. And this is played a bit faster than in reality. This is normally 24 hours. And in 24 hours, you cover the map of Amsterdam multiple times. Times. We are in an age of big data. And big data is hugely important for mapmakers like us. As you know, the applications that use maps have, grown tremendously in number in nature and so on and so on. We're not talking only about navigation applications. We have application in fleet management. There's also pretty traditional. We have applications that are developed by, developers that are using our MAPS APIs, and those can be any kind of location applications that you can imagine. And on top of that, we have new kinds of applications where the map is not necessarily not used by the humans as such, but by robots. And I'm talking about ADAS, advanced driver assistance systems, and I'm talking about autonomous driving, the self driving car. Now all of that had has made sure that there are a number of things that have changed. First of all, the quality of the map needs to be much higher than it used to be in the old days. Secondly, the time by which the map is updated needs to be much faster. We sometimes call that the cycle time. We want that cycle time to be as limited as possible in time so that you have always the freshest data, that you can have. And to do all that, you need the amount of resources. And because of the cycle time that is so limited, you need to have a very high level of automation so that your cost per modification in your database is pretty low. And I must say that we do that all quite well, at, at TomTom. And that's one of the reasons why we have an independent map maker or one of the few companies that do that at scale. There's a couple of things which I would like to discuss with you and that, I think it's worth remembering. First of all, map making is complex. It's not that complex to us because we have the expertise. We have the technology to deal with it. But for any company in the world, it would be very difficult to produce what we already have in house. It's not that difficult to make a map of Amsterdam. But if you imagine that there are 68,000,000 kilometers of road in our database, and then you imagine that you have to keep up with street names, with, street limits, with house numbers, with postal codes, with TMC codes. And I can go on for quite a while, and all those things need to be updated quickly and without that many mistakes, with the least mistakes possible. That makes map making at scale, very difficult, and that's also the reason why we're one of the very few companies that do it. And how do we do that? Well, we actually created a number of very specific technologies, in front of the building, You see one of those technologies that is the Moma vent, that is the mobile mapping vent, actually pull up T. T. It's very important to understand that that Moma Vam didn't come out of nowhere, and it wasn't invented by Google. It was invented by us. In, 1989. There was the 1st mobile mapping van, and it drove around in Amsterdam in this city. So in the meantime, I don't know which version we have today. It's it's version 50 or something like that, but we perfected moment vehicles, and they are very instrumental to capture images and to capture lidar data, which in turn is instrumental to make our HD maps and our navigation maps. That's one of the technologies we use. I will later on tell you more about artificial intelligence, machine learning, which we apply to automate our map making, and I will also talk about transactional map making system. It's quite a unique system that we have developed, and that was taken into production in the year 2016. And we developed before that for a number of years, and I think that's a unique system. I will explain you what it is all about. And Harold also already mentioned that we go beyond that, and we make actually sure that we create a map ecosystem with our customers. So our customers demand fresh data, high quality data, but they also imply that that data is used by their users. And their users give feedback. And because of that feedback, the map can be improved, and we actually enable our customers to do that themselves so that we create around, TomTom, a number of very important customers that actually contribute to our map database. Let me go back to, the world of big data. Prope data is definitely one of the examples. More and more cars are equipped with sensors that sensor information is incredibly important for us to make our maps better and to do that faster and at lower cost. In that world of, big data. I'll, I'll give you one example, which is, I know you know, you like numbers, Right? And, so here are a couple of staggering numbers. So we collect probe data from 600,000,000 devices daily, right? And those devices include mobile phones, navigation systems, telematics systems, you name it. 600,000,000. Now, if you want to have kind of an idea what that means in terms of, how much data we get on a daily basis, right, we cover about 3.5 1,000,000,000 kilometers of roads every day. I don't know what it is. It rings about, but it's about one times, one time around the earth per second, right? So that data is incoming and actually enables us to use that data to compare it with our map and to do all kinds of stuff. Here you see, the probe data of a number of cities, and you see differences in the buildup, in New York, for example, we get the data about fifty times a day, fifty times enough data to cover the whole of New York. All right? Singapore is even, is even worse. It's more dense traffic. There, it's about six hundred times a day that we can actually cover the whole of Singapore. Per day. Right? What we do with those data is we take that probe data, we compare it to our map And we can find a number of things. We can find where there are new streets. We can find where the turn restrictions or the one way restrictions have changed. And in this way, we can update the database. We can also compare the probe data of today with the probe data of yesterday to find out what has changed. So we can really play ball very quickly with regard to updating our map database. Let me get back and why is it unique? Right. There's most mapmakers in the past, and most mapmakers today produce maps in a batched system. What that means is you take a map, you store it in a map database, you make all kinds of edits in that map database, And then once every month or once every week or once every quarter, you basically make a release of that map database So you have stored all those edits. And in the release process, your quality check all all the edits you have made. And that is done in a batch process. There is fallout. You correct the fallout, and you go back to the release process. And at the end of the day, you release your map once a week or once a month or once every quarter. That's the traditional way of doing things in, in mapmaking. The transactional map making system works differently. What happens in the transactional mapmaking system is that any change in reality can be taken through the whole process, including the quality checks, and immediately be available for as an update of the map to the application, which means that your database is actually continuously releasable. And what that means is that, which every change of your database, you create a new release, and that happens continuously. So you don't have to wait for a week or a month or a quarter it happens continuously, and your applications can immediately use the freshest information that is in your database. That's quite a difficult system to make. And we were very successful doing so. As I said, we introduced it in 2016, and I will show you what the results of that introduction are. What that did to our database and to our productivity. Here's what we have today. And it's, again, a staggering number, but in, we broke the record in, in August, with 2.35,2.35000000000 modifications, in our database in 1 month. That's an enormous amount of modifications in our database. 85% of those modifications were automated. So 85% of those modifications went into the database in an automated way as a result of what we sometimes call fusion. Fusion is actually nothing more than combining all different sources that can be probe data, that can be aerial pictures, that can be images and lidar data from our moma, moma van, infusing those to create transactions that in itself have multiple modifications that 50,000,000 roughly. We are now at the level of 2,350,000,000, which is almost tenfold. And what happened with the costs because that's even more important. In the same period, we lowered the cost by a factor then. Which means that with the same amount of money compared to 2016, we can do ten times more upgrades of our database, 10 times more modifications in our database, which is kind of a fantastic result that and the foundation of that is our transactional system and a much higher level of automation, driven by the usage of machine learning. How do we use artificial intelligence? Well, I can give you plenty of examples But I'll give 2 examples, which are highly relevant. In the HD map making world, but also in the ADAS world, it's very important that we capture the sign posts. And the sign posts are captured by our moma vehicles. They drive. They have lighter information, and they have visual video information. That lidar information and video information is checked for a reflectivity And as you know, the signposts reflect a lot. We identify the signposts fully automated, and we can actually recognize whether it is a speech extriction, whereas one way restriction, whatever. So we have a number of signposts that are, that are in the catalog, which are by machine learning detected in our database. That's one example. Another example is Through the probe data, we will know, for example, where there is a new road. But then we need to pick up the geometry of that road. Well, the way we do that is we use our, satellite images. And with machine learning, we can actually pinpoint first, based on the probe data, where that new road probably starts, and then the new road is fully automatically created in terms of geometry. Those are 2 very simple examples of how we make a higher level of automation in our map making world possible. Let me come back to the map editing partner So what it does, all the previous things I talked about, what it does to our database is indeed that we have a higher quality database, that we can deliver very fast to our customers, which integrate that database in their applications. Their applications are used some cases, by thousands of people, take Uber as an example. Uber, Uber is using our maps, and there are many drivers that basically know whether there is a mistake in the map or see whether there is a mistake in the map. And traditionally, what happened is we got that feedback through Uber, towards us, we put it in our production process, and then basically, we provided them with an update. The way it works today with those map editing partnerships is that they don't have to return us all that information. We have given them the tools and the training to, on their own, be able to correct immediately the database. So you can imagine what that does. It increases the quality, and again, it lowers the cycle time. So it makes sure that we have better maps foster. That's what we do with the editing partnerships. It gives short to cycle times, and it makes the map better, which is crucial for all the customers that quality of the database and reduce that cycle time. So I think, as a conclusion, I hope I have given you a glimpse of all the, technology we are using and the processes we are using with one goal in mind, you know, to make maps better higher quality, which in robotic worlds, is even more important, and WILA will talk about the HD map in more detail. But also for navigation and other applications, the quality is increasingly important. The cycle time reduction which means that you can have much faster updates that you can incrementally update the applications is crucial in an online world. And as Harold talked about, we are more and more use, going into the direction of online applications only. And that means that the expectation of the end user is that your map is just continuously up to date. With our transactional system, we can make that a reality. Online information available, and we can do the same thing for many attributes and content in our database. And at the end, we do that all for a much lower cost per transaction and per modification than in the past. Thank you, very much. It's Francois Xavier Bugini from UBS. A couple of questions. So you talk about, your back load, that's going to be your new KPI, removing the order intake. At the same time, you say that you expect product user growth to accelerate beyond 2021, which would imply probably the order intake to increase in the coming, couple of years. So my question is, what is the main driver? I mean, if it's the case, is it the case? First, if it's the case, what is the main driver that prudes increase your order intake in the next few years. And the other question is if your backlog is 1,600,000,000, and you have a take rate assumptions, you have, the volume assumptions, what is the take rate assumptions you have today for 2021, given the visibility that you have. That's the first questions, if I may. We'll we'll we'll discuss takeaways, in, in in detail. Later, today. The take rates now are so what what we have for the contracts that we have signed ticklets are anywhere between 30% 40% that depends on brand and, car type. But we foresee take rates to go towards 80% in, in the next decade. But that's not so much. That's not the driver of, that's not the explanation of the backlog because the backlog we see today is take rates. So that's, again, that can be low 30 or can be high, high 30. But the acceleration of growth One of the drivers, why we expect acceleration of growth is take rates. On 12, our Head of Automotive, and Kees, our Chief Productos. So we'll, we'll talk about that. Yeah. I think, and I think the other thing that you see in that, in that forecast is, over time, take up of, technologies for automated driving and ADAS. That will really start to kick in, in the midterm. That's not for this year or next year, but certainly maturely that will become mainstream application for most vehicles. One of the things that we will see is that regulation also helping in our favor, in a couple of years, the EU wants to make it mandatory for European cars. To, to see, speed limits. It can be done by camera, but it can also be done by, a map. And especially for the less expensive cars that will, the latter will be more the default solution. And that could also increase the take rates at different price points, obviously, but that will, generate new income streams. Hello? You ran out of batteries. Yeah. And yes? Yeah. Yeah. So a 2 quick So on your market share, so obviously Android Google made a lot of noise last year, with, with, with, So given that you have more like, long term assumptions now, do you expect any change of the market share in the next few years? To justify this 15%. I mean, is it based on, like, stable market share? Do you expect some disruption there? And the last one you talked about, all of you talked a lot about cost reduction in your map making platform. So I just wanted to know how is it translating in your operating expenses, or how should we think about the profitability of TomTom in the next few years? We see that sourcing and, is going down in terms of cost processing as well, but engineering seems to offset all these benefits. So I just wanted to double check with you. Thank you. Yes. So there is, I think we're fairly disciplined in how we, run our cost. We are at that tipping point where we are generating Sears cash this year for the first time. Longer term, I think we will continue to, to generate, cash as a, and we see it also a bit as a boundary factor that we want to run a show where we have positive free cash flow. And I think we can do that. There is one, you know, and, and, you know, I don't think that's that's that's a bit in our DNA and that's how we, how we see the business going forward. Those map adding partnerships are important, but they're not in itself. Reducing our cost base. They're making for better maps and better customer service, and that's a selling point in its own white. But you don't see any meaningful, at this stage because of the volumes that are happening. Don't see a meaningful reduction in cost base It's a, really, a, an, given our customers, the ability to inject data into the database that matters to them. And that is a, an important capability that we can give to our customers. And as a result, the map will get better, and that will raise the appeal for doing business with TomTom as a lower location technology provider. But you will see a massive, or massive, but you will see a very firm transition from a, from manual labor to automated processes. And for that, we need engineering. And, in the HD mapping space, you also need engineering to do that cost effectively into a high degree of automation. Yeah. I'll I've been touching on the market share as well. So what what the Harold, expense, in this presentation as well is that for traffic specifically, we have 80% market share in Europe. I don't think there is a law a room to grow that further. There is room to grow our market share in the U. S, and that will happen based on the order intake. So We've signed, let's say, 2 of the 3 major American OEMs, and that will, increase our market share for traffic. On the mapping side, today here is the incumbent. And we have been gaining market share and we will continue to gain market share, but we are the, the follower there. And then on software specifically, software today is, or software is a bit of a generic term, but let's say the navigation tree or IVI, that is very scattered, area. And so no one has more than 15% market share We are, we have a double digit market share. We believe, and again, on Tom and, Casey will talk about that We believe we can significantly grow our market share in the, in the application layer and what we can, can do there. Marcus Link, ING. I would like to come back on that market share, because, obviously, a lot is changing in a competitive environment. And, Google now coming into the picture, maybe if at all, everything that's being announced, if they would move everything to Google, maybe they have, like, 30% market share. So is that your assumption in the long run that there will be those 3 players yourself, Google, and here, and all three of them taking that that one third of the market, is that your assumption behind the 50% CAGR in the long run? Well, we, in our, in our Kekka, we don't anticipate a massive increase of our market share. It's not what we think by 2030, we have 90% market share. That's not what you see in those pictures. What you see in those pictures is a stable, have slowly growing market share. The much broader applications and a higher attachment rate and new applications coming in, specifically for ADOS, HD, but also IVI. So a more integrated approach to the user interface in the vehicle, case from Gokhar's Chief Product Officer will talk about that And we see, great opportunities there as well in gaining market share. And if you do that, then you have a much broader part of the whole software stack in a vehicle. It makes a huge difference, of course, if you only provide traffic or if you manage the whole, stack, especially when it goes online, which is what our expectation is. But it doesn't also imply that, because the other one could, could also happen, like, Reno or big clients of yours, moving away to Google. Because that's good in actually embedded over time than your market share on the session that price goes on. We we need to see how that, how it will pan out. We need to see how all that will pan out. We are obviously aware of what Cook is doing. They have some early success with some OEMs. We don't think that, the whole market will go to one player. It's just simply not how it's going to work. The industry, we always want alternative solution and alternative vendors. And we are, we believe you're very well placed to, to be that better. And there's a number of drivers there. So first of all, we see higher degrees of integration, in vehicle, all sorts of silver boxes that need to talk to a unified user interface. And that is very difficult to, to do that with an application that's basically taken from a mobile phone and put in the dashboard. So the integration is is important. Electrification plays an important role. So that's from a product perspective. But also from a business perspective, We just do not think that all carmakers will hand over the keys of their user interface. An important part of real estate to a company that sooner or later will start competing with them, both in self driving or for, or use data for alternative business models. That is all the healthy situation, and we don't think that it will happen. Now, at the same time, of course, I think there's a, there's good news as well. We have been arguing for a long time with our customers that we need to change the way we're working. That the applications we are currently, that are currently in the market, don't live up to end user expectations. And you see that a lot of customers who paid for a navigation system or an infotainment system in the vehicle are actually not using it, but are referring to mobile phone that's more trusted. Well, that is multicloud. And we need to fix that. Our customers understand that they need to fix that. And there's a big drive to going to an online mobile where you can deliver an end user experience that is compelling. And that lives up to expectations of a, also a younger audience, more modern audience, and so on and so forth. So we, we think there's a great opportunity now to, to step in that void and offer a great alternative to a, a product from a vendor that is not fully trusted. Okay. Thanks. And maybe a bit more on the short term, you explained the part on the, on the automotive, and Evolocation technology percent, but there's also big moving parts always in the deferred revenue. How will that be in the next coming years? And obviously, there from, on your free cash flow in the coming years? You're good at that. And then no. No. I'm about maps. You do map you do the eye for us. Thank you. So, no, yeah, so for this year, what we've said is that, we we we we expect roughly a net additional 6,000,000, 11,000,000, being deferred in automotive. 25, released in, the consumer and 15%, also 15 1,000,000 in, in enterprise. For next year, that that number will be a bit different. So Automotive, again, a net defer maybe not 100, but 95 consumer will also go from, 25 to 15 because the installed base is declining. So, and also term of, deferring and releasing has shortened. So we'll go more to 15. And again, in enterprise, we see something like, 25. Now, so these trends will continue. I think that, for Automotive, the net amount that we put on the balance sheet, will decline. Where we see 100 will go into 95. And as soon after that, further decline, the net release of consumer will decline as well. So 15 towards 10 and going forward. Enterprises is a bit bit different beast because that's more related to, larger customer, additions etcetera. So after 2021, I don't expect huge differences, etcetera. So, with the knowledge that we have today, it will be driven by automotive and consumer. To anywhere like, we $60,000,000 to $70,000,000 from 2021 onwards. Okay. Thanks. And then the final question is on the, you gave the, the first step towards maybe cash returns in, in, in the next year's file buyback. So what are the things behind it? And is it then something if I reach next year? Is that something that you discussed at the full year update, the full year 'nineteen updates, then probably starting in, in, in, in, in 2020. And so what I said, what I mean with, with what's behind it, like, is there a sort of minimum cash level that you would like to have on your balance sheet? Is it dependent on the free cash flow that you're going to generate in the next couple of years? What's behind your thinking there? Yeah. It's more an April thing, so with with our ATM. So, So I want to push it out, a number of 2, 2 months, but, it is what it is. Yeah. So there's the the investments that we need to make towards, it's the mapping and the acceleration, that we see there. Or the pace of investment, together with, the free cash flow that we see. It's a combination. It's not a, it's not an hard science or what have you. We feel that 4 months ago, we did what we had to do. We gave vaccine 150. If we go over the half a billion of cash on our balance sheet, that is kind of a moment, to reflect again. Or but, again, with the ATM, we will give an update on that. Do we know more about, you know, about all businesses and store budgets a bit better? And I think it's a good moment. There's no right number for how much cash you want to keep on your balance sheet. You know, it's it's a bit of I think it's the right number at the moment. We have, as you know, there's a law of turmoil, there's a lot of change in the industry, great opportunities, but also that brings if that's needed, and we don't want to be forced to do dumb things because we, we elect fire power or we We can't do what we want. I'm not ready to draft market opportunities. I think, right, that number, you're, you're kind of okay. But again, yeah, I also said we want to be, disciplined. We want to generate cash. I think we're well on our way. Our longer term plan shows there's also the ability to keep generating cash. We feel good about that. We strongly, we can, we can't move as needed if the market opportunities open up then we have fire power to do things. There's nothing on the agenda, but just to have that flexibility, I think, for this type of business, is is Gucci. Okay. Thank you. B. Michele, ABN. Two questions. First of all, IFRS is doing you guys a lot of favor in of revenue recognition, but also the IFRS definitions of backlog can, can be quite harsh on you guys. So the backlog definition that you use is that pure IFRS definition, or is it that you have constructed a TomTom version, basically adding up all the IFRS or expected IFRS revenues and come to that number. And the reason why I'm asking is because, obviously, depending on the contract structure, Ipress is a tendency not to account for stuff, which is actually going to be there. So that is my first question, probably for Taco. Then I've got a question, for Alan. Yes. You guys made a great progress in the transactional mapmaking business. Do you guys have any feeling on how you stack up PSAV to competition? So where is here going on this particular topic, whereas Google on this particular topic, do you guys have a view there, how far advanced you are, and also how difficult this is to replicate for a number of, startups, which are basically just coming around the corner and and, you know, some of them are quite well funded. Do they have kind of, a fighting chance in getting to the position that you guys already have. You want to take that? Yeah. So first of all, what we have in our annual report The backlog is something different. It's a combination of enterprise and of motion and does not include all the contracts. Because it's only the IFRS 16 contracts that are in there. So, a very relevant KPI for the regulator, but not for the analysts on the investors because you can't do anything with. So What we decided is to focus on automotive only and just look at the, awards and the contract And based on the assumptions made on the, the tenure and the, the car sales and the take rates, and apply the, committed biases. So if you look at the total order intake, operational IFRS will be the same, but only the spread over the years, obviously in IFRS is different so less, early and more, at the end. Does that answer your question? Or Yes. I think on top of my mind, you have a backlog of around a 1,000,000,000 or so in your annual report. That's kind of a completely different number, different definitions. And we should continue to ignore that number. Yeah. Please do. Thank you very much. So with regard to the map making platform, we we think we have a pretty unique platform. Now, let's talk about Google. I don't know what Google has in the kitchen. Right? So it would be wrong to say that they don't have transactional system. I don't know that. Right? What I do know is that here, does not. Right? And what I also know is that you absolutely need to turn actual system if you want to have, a future, right, because as the world is moving online, cycle times, updating information, so critical that you can't get away with batch systems in the future. So how much time it would take them to, develop it? I can tell you that it took us 4 years with a lot of people, it was a big investment, maybe they're more clever, maybe not, right? And with regard to your question on startups, most of the startups in the, in the, in the mapping world are one trick pony's. Right? So what they, they have one specific area of map making, and they demonstrate that they're really good at that. What we're talking about in, in the environment of the Google here and ourselves is mapmaking at scale, which is completely different game. Right? So before a startup, and if you say well funded, most of those startups are funded with 900,000,001,000,000, and maybe 200,000,000 but that's, by far, null and off, to get where we already are. And actually, a proof point of that, there's 2 proof points of right? If it would be easy for a startup to do what we do, you would have plenty of them that already are somewhere in competition with us, and they're not right? That's one proof point. Another proof point that is even more impressive at a certain moment Google decided to make their own maps. Right, before that, they were using teleatlus maps or quantum maps. Right? It took them 7 years to achieve what we had. Don't forget, it's 68,000,000 kilometers of road that are kept up to date. Small little startup. Never say never. You know, we also it as a start up many years ago. So it is possible. Is it possible? Yes, it's possible. But we're not talking about 100,000,000. We're talking about way more before they are where we are. And in the meantime, as you have seen from the grass, we're moving really fast. Right? So it's, I think it's not very likely in the foreseeable future. We would see that coming. You're allowed to throw with that. Andrew Gartner from Barclays. Just to follow-up on that question and then some of the points you were making earlier, I think both of you, Harold, then Taco on market share. I mean, if we go back a few years, you were willing to talk about you having 20% market share of maps in car and here at about 80%, TakuU sort of didn't really want to touch on a number there. It feels like it's been moving in your favor, but perhaps not dramatically. So given how long the development cycle product cycles take in the automotive space. But I'm just wondering why, given what Alan just described in terms of the strength of the transactional database and particularly relative to here, who is seemingly the primary legacy competitor. Why are you not more optimistic in terms of the potential for market again in automotive? Well, we are. I think the lead, so so I think the leading indicator, really, on the West Coast. Those, they, they are faster. They're more they have a deeper understanding of technology and how it goes. Compared to the West Coast company, I think the Carmakers are typically a bit behind, a bit slower. And for all the right reasons, that's all the criticism that's just the nature of that business. It's a different business. You want to be a fast fall or you don't want to be an innovative problem, if you are karmic. But if you look at what we have achieved on the West Coast, we're very proud that we are now really embedded with kind of the leading technology companies there and have entertained very good relationships. And that's a mutual, mutual benefit. We learn from that. We get faster we have good visibility on what's happening. I think that will translate also, and it is translating already in our fire power in the automotive industry that will trickle through, but it takes more time. In the last couple of years, we've seen market growth market share growth in the automotive, space with some very significant wins that have always been customers of our nearest competitor and decided to, to shift their business for a large proportion of our business, it's not always everything, but at least a large proportion of our business to TomTom. And I think that's a good sign we are confident that we will continue on that path, but we're not putting in, as I said earlier, 40five percent market share in our longer term plan. It's just simply not enough evidence to say that, that that's going to happen, and we want to be cautious, and we want to be careful, and certainly not how we are planning our expenditure. But I think, we are well placed. To take advantage. We have a lot of cooking in the kitchen, really cool stuff, really excited about that. And we lift a little bit of of that later today, you get a bit of feel how this thinking is developing. But we want to really reach out, not just to the Carmakers who are paying the bills at the end of the day, but over the half of the Carmager also the end user and make sure that we can supply our customers in the automotive space, there's an end user application that really cracks it that people actually use, and that they find charming and entertainment and fast and, and, and, of great quality. I think that's the challenge that we have defined for ourselves to be able to be able in that position to help our customers to keep control over their dashboard with end user applications that really matter in our 1st class and can compare favorably you have on your smartphone, whether it's from Google or Apple or any other vendor, you know, our target is to put something in screen, it is as good if not better and better suited, for use in a car environment, then a application is typically developed for mobile phone session. That is the that's a longer term vision. If that sticks, if you can't get that through, then we have we have all the underlying technologies of vision. The end use the experience with end users to be able to play that role. And I would find it very exciting if we, if we can get there, together with our customers, to start delivering products that are really top notch, that are charming, delightful, and, and, and, and do what it's, what, what customers are expecting them to do. And that's a great challenge, and we know, I think we've got what it takes, to take that home. And I think that customer see us also in that respect as an alternative to taking a full package from someone else that have limited influence on customization, product roadmap, and so on and so forth, with a supplier that could potentially sooner or later, start competing with them. So I think that's a, that's a great product proposition and a great business proposition. And, you know, and now we need to, now we need to get on in, convincing and working with our customers to, make that vision in reality. And in the meantime, of course, you have a lot of stuff already now ready to ship, ready to move. And that's our current business, and that will keep going. There's all new clouds of products and user experience that we want to bring to the automotive industry. It's a whole new thing that we want to bring to our enterprise customers with you know, a more collaborative way of making top notch maps. Again, with a view to kind of circle those customers who have, for one reason or the other, do not want to commit to the, to a platform of one of their competitors. And I think in that space, in that sweet spot, there's a great role for us to play. We have what it takes to heritage culture, output looking customer focused development. Excuse me. I think that's where we that's where we want to hone our skills and want to progress in the years to come. So and I think that will work. If you looked at the, at the, at the, at the, at the outlook for the next 10 years. You see very significant number. That's partly coming from that integrated, product in the dashboard. Partly coming from new products like, ADOS and HD, where I think we're on the right track as well. And also partly coming from, of course, what we think we can achieve in the enterprise world. Just a quick follow-up. You you mentioned the success with the West Coast Companies and the, that's, giving you, you also highlighted Apple on one of your slides. So I'll ask the question. I'm not sure whether you can answer it, but they themselves are also doing some map development. What type of visibility can you give us into the strength of your relationship there and longevity given that potential conflict? Well, you know, the only thing I can say is, is, is Apple has been a fantastic partner for us. Absolutely, we've, we've, we've done a, a long term deal that will run for years, still, and they kept their part of the and weakens a part of the bargain, there's law of trust and collaboration going forward. There is an end date to this, contract, of course, But I am committed and hopeful that there will be something, in the future with Apple as well. And I can't guarantee that. That I think if I read the Tlease correctly, I think there will be a future, after the expiration of, of the current context, it will have a different nature, a different role will play. But I think there is a, there is, hope an opportunity for, for a long, for a new type of relationship, very much along the lines, what I just said, being in the middle of that ecosystem, for everybody kind of looking for a good alternative, an alternative map that is of high quality, with where they don't have the burden of collecting the data due to policy control and so on and so forth. That's that's a space that that I think we can occupy. That will take some time. That is clearly, part of the strategy going forward. So I'm Amanda Towson. I'm heading up our business unit enterprise. I'm based out of San Jose of the heart of Silicon Valley. And over the next 15 minutes, go through with you what we opt to in, in the enterprise business unit space. In, in our business unit enterprise, we work with a lot of different type of companies, and we are extremely pleased and proud that so many companies have selected TomTom as their trusted location partner. Whatever that is for fleet logistics, web or mobile applications on demand or ride sharing, applications. What a lot of people are not aware of, if you put all that usage together, it basically means that over a billion people can access our products every single day through all these different types of partnerships we have created over the years. And that, of course, in itself, is pretty amazing. So I want to go through with you to, you can say, high level go to market product area. So the first one is on compiled maps and traffic data. And then later, I'll go through our other product offering, the Maps API space. So let's start with uncompressed maps and traffic data. And I think the best way of looking at that and explaining that is you look at our maps in different layers, whatever that's base map, street maps, street names, point of interest, like hotels, restaurants, traffic, or navigation, all that comes together. But as an application developer, you don't have to use all the different type of layers. So let's, let's take an example. So if you want to create a stall locator, you probably wanted to take the base map, the whole street network, You probably wanted to take the street names. You definitely want to take your own store from a part of interest, and you put that together as your application for store locator. Let me give you another example, and in this example, I will use So Uber is taking all the layers we have in our own compile maps and traffic. We put that into the phone. That Uber have decided that they wanted to create kind of how their own map looks in terms of callers and how it behaves. They've also created, you could say, some interface between the driver and the rider to have some kind of interaction, also get some stickiness for the driver to use the Uber application. So we put that in as well. And basically what comes out of it oh, sorry. What comes out of it is oh, not working. Anyway, what comes out of it is the Uber driver application which has been used by millions of drivers every single day. When we ask our customers what is really important? That is map freshness. And then, and we can tell our customers that we are doing 2,400,000,000 modifications every month is absolutely helping our story towards our customers. Of course, there's a lot of other things, which is important, as you can see in the slide in terms of different sources, which is coming into, to our map database. And as you heard previously also from my LAN, that we have all these type of partnerships, which basically means you have access to 600,000,000 live devices, which is providing us with probes every single day. And that in itself is a very unique proposition to the market and to our customers, and it's actually helping us a lot winning deals out there, but we didn't stop there. So we were kind of sitting down and say, Hey, How can we help our customers, helping their customers even better than what we're doing today? So, basically, trying to delight, you could say, through the whole channel, And that's basically how we came up with what we called, and you heard before, the map editing partnership. So we basically been taking our tools giving them to our customers, our strategic partners, and letting them edit directly into our map database. And of course, the whole idea behind it is that we can turn these edits around much faster, and we can have a much pressure product. And of course, our partners are very interested in having that freshness so they can provide the best product to their consumers and, again, in the market they are in. So again, what you see here is the tools, just an example, we're changing a street name, which you can do directly into the Thompson map database, we're using the Chump sum tools. And again, we have trained our partners as they were exactly Chump sum employees. So, all the quality rules, all these type of things, of course, is in place. In the beginning of the slide, you saw a lot of different type of logos. And again, as you heard, been talking about in the beginning, like some of the segments we are active in, like, fleet and logistics, web and mobile and analytics. Let me run through with you a couple of example how our maps are being used, with different type of our partners. So the first one I want to show is PTV, based in Car's room. PTV is very strong in what we call traffic management solutions, So, of course, they what you see here in the picture is the traffic center. And, of course, Maps traffic is extremely important for all these type of traffic management solutions. And again, they're using 100% TomTom for all these different type of implementations. Another example I want to show you is Apple. So Apple and TomTom have been having strategic partnership for many years and for many years to come. And, also, if you see here, if you take Apple Maps and you open it, you click in the upper right corner, the information, and you go to the next screen, you will see a TomTom logo So also, Apple is very proud of showing that I'm working with TomTom and showing that to all of the users of, of Apple Maps. The next one is SAP. So SAP has been taking all our base map and addressing and created a global geo corridor, which both can be used by SAP themselves internally, but they're also exposing that global geo corridor, to SAP's users, and then you can basically get access to it and pay via SAP if you want to use that global, geo code. The next one is Pitney Bowes, an American company, but they're very strong as well in Europe under the brand of mapinfo. Which is being used a lot with different type of municipalities for role planning and these type of tools, but they're also very strong in the insurance space. So, basically, what they're doing, they're taking all the map and traffic data from Thompson, And then they're conflating on tops. Again, if you think about the layers, they're basically putting their own layers on top of different type of information. Let's take an example, an insurance company, you want to put a price to a business or real estate or your own house, then basically combining even with flooding, crime in the area, how fire and police station and fire station, they conflate all that data together and bring that solution to the insurance companies. I also have a small video there I want to play, basically explaining how we're working closely together with Pitney Bowes and why that relationship is important for Pitney. The Pitney Bowes mission is to organize and manage global address data. And to be able to then provide attributes and enrichment data around those addresses. Pitney Bowes has made the decision to do business with TomTom a number of times over the last 20 years. The decision came down to very complimentary business models. TomTom enables Pitney Bowes to execute our strategy because of the investment that Tom Tom makes in building and maintaining global maps. We work in a number of key verticals. Our primary one is insurance. So our insurance clients use address validation and cleaning, being able to manage so they have a single view of that customer, but even more importantly is our geocoding and our location and data. TomTom collects really, really valuable data around addresses, around streets, around points of interest, and the fact that it's global coverage, and it has a consistent data model is really, really important to that relationship. At Pitney Bowes, one of the most exciting things as we look forward, is working together with Tom Tom to build out a complete and current highly accurate and precise global addressing data set. I really think the most exciting time in our relationship is ahead of us. Okay. So that was kind of a little bit about our product offering in the un compiled maps and, traffic area. And then, as I mentioned in the beginning, I'll go through our offering for the Maps APIs. But let's start asking the question, what is an API? Is the application programming interface or API. It's the engine under the hood and is behind the scenes that we take for granted. But it's what makes possible all the interactivity we've come to expect and rely upon. But exactly what is an API? It's a question everyone asks. Okay. Not really. But we're glad you did. The textbook definition goes something like this. In computer programming and application programming interface API is set with teams or calls Okay. To speak plainly, an API is the messenger that takes requests and tells a system what you want to do. And then returns the response back to you. To give you a familiar example, think of an API as a waiter in a restaurant. Imagine you are sitting at the table with a menu of choices to order from. And the kitchen is the part of the system, which will prepare your order. What's missing is the critical link to communicate your order to the kitchen and deliver your food back to your table. That's where the waiter or API comes in. The waiter is the messenger that takes your request or order and tells the system, in this case, the kitchen, what to do, and then delivers the response back to you, in this case, food. Now that we've whetted your appetite, let's apply this to a real API example. Yes. So what is a good example of real examples? So look at it like that. We have the kitchen and basically, we now take the on compound maps and put it into the kitchen. We then have hired the best chefs in the world, which, of course, is our engineers, and they're doing all that cooking for you So, basically, what it means for you as a developers, it means much faster time to market using the APIs versus taking and using the own components. Of course, the unique thing for Thompson is we have both, right? So we are both offering for the market, whatever you think, whatever company you are, whatever application you want to build or solution you want to set up, we have both offering for you. But again, with the APIs, it's a very easy way to get to market very, very quickly. We are estimating that the overall, the total market of Maps APIs is around $1,000,000,000, and it's growing, as well. We started recently as Tom Tom with our MAP APIs, which basically means that our market share is, is tiny to, today, but we definitely have high expectation in the overall Maps API space. So if you look at our product portfolio on the Maps API, so we have search, but of course, on the search, you have different type of functionalities like geocoding and reverse geocoding, routing, different type of functionalities as well. I'll come back in a second and show an example of EV routing, which we released recently. And you have map tiles, you have the traffic. And in the end, you have the maps SDK. So, let's take, again, the example I used for the uncompiler Maps for a store locator. So, in this case, you just hit the search API for your store, and you hit the map tiles and basically, already there, you have your store locator. So again, hopefully, there's a good example of showing that with the Maps APIs, it's very simple and very easy to use and fast go to market. But let's go into the routing and show you an example for the EV routing. So here we're calculating a route from our office in San Jose through Los Angeles. You're driving a BMW free and the blue polygon you're seeing immediately is the range you're having for your EV car. And you can see that, of course, that when you're getting to the range, out of range of the blue polygon, then you have to find a search for an EV station. That we're also providing part of our EV off So you can search for the EV stations. We will tell you if the EV station is open. We will also tell you if the EV station is free so you can get there and start charging your EV vehicle. So with that, of course, we're helping all the EV dryers getting from A to B in a very smooth and easy way. If you look at our Maps API channels, we have high level 2 channels how we go to market with our Maps APIs. We have our own developer portal, and then we have our enterprise unit for the mall, you can see larger strategic deals, for going out to the market. If you start with the developer portal, so you just go to developer. Thompson.com, and you get access to our developer portal, Look at it a little bit like a, like a store where you can go and browse around and figure out what you want to buy. So you can go in, sign up, test and play with all our APIs. The business model we have introduced here is what we call pay as you grow. So you start free, but when you start growing your business, you start paying for the API and the usage. And again, it's super simple. You can just put in your credit card. You don't have to talk with us. You can do anything on your own. If you want to talk with us, we like that as well. You can, of course, contact us and we can do that online and help you build your application. It's, again, very easy and very simple. The other areas, as I mentioned, is the enterprise area, and, one, specific, contract I want to highlight is our contract with Microsoft. So we started our contract with Microsoft. A while ago, where we, as TomTom, announced we are putting our Maps APIs in Microsoft clouds, ASH, which basically means that all the Microsoft, internal development have access to the APIs, then we also agreed with Microsoft that they could bring it to the market under their own brands, so they bring our Maps API under the Azure Maps brand. Microsoft is then adding some other interesting things in the product offering them themselves. We recently also announced between Tom Tom and Microsoft that the Bing Maps and Cortana will also move to TomTom, So I think it's fair to say that, our relationship with Microsoft is very good and very solid. And wherever Microsoft have a need for any type of location, maps, traffic, they're using, TomTom. But instead of I'm continuing, it explaining what Microsoft is doing, it's much more interesting to hear it from Microsoft themselves. So I would like to invite Chris Penelson, head of ASHEMAF to state. Thank you. I wanna thank, Tom Tom for inviting me at this stage. This has been a very lucrative partnership for Microsoft. I've, I've been in the map space for 20 years now, varying degrees of impact across the company. I've been at 7, micro Microsoft for 17 years, 3 years at a company prior to that. And so I can fully appreciate Elon's presentation, like the the ability to make maps is hard in it of itself, but the ability to make them fast and keep them fresh it's exorbitant in terms of resources, cost, and, the amount of data required to actually keep them up to date. And so, a few years back, just to give a little bit of history a few years back, I, I ran the Bing Maps data ingestion team. So I was responsible for keeping Bing Maps data up to date. And, we would take quarterly drops from our provider. It would take us anywhere from 6 to 9 months to get that data out. And so if you do the math, it you gotta drop every 3 months, and then it takes 6 to 9 months to get it out. So we missed 1 or 2 drops in the process. It didn't work for us. And so, the the, the the, the product of Azure Maps was created, effectively for two reasons the first of which was to bring location natively to the Azure cloud. And so in, in, in our conversations in, at Microsoft in terms of competition, we talk about the 3 clouds that are currently in competition with one another. Azure Maps is natively integrated as a 1st party product of the Azure cloud. And so when we talk about Azure and all of the Azure wins, we're talking about location through Azure maps. Okay? And so as you start to see these wins and announcements coming through Azure maps or through Azure, that include location and effectively Azure maps, we are effectively talking about TomTom. Right? So as Anders mentioned, we struck this lucrative partnership that brings TomTom's APIs to the Azure cloud, and we wrap those up and made them a part of our platform. And so, this is the definition that I wrote, for our documentation. It's it's super nerdy. But basically, Azure Maps is a collection of location technologies for Azure customers. As Azure grows, our location capabilities need to grow and keep up with our customer needs. Okay? And we wanna make that simple for our Azure customers to use. And the way that Azure works is you actually subscribe to an amount, a pre committed amount of Azure, and then you start spending against that commitment. And when companies start to look around over the 1, 2, 3, 5 year commitments and they see maps there, it's a pretty easy decision because they've already precommitted for amounts that they need to spend. And so they just go to our portal, and they start using Azure maps. In fact, somebody on my team is dedicated to every morning looking up and seeing who our new customers are, because every day, we, we actually don't know until we look up the report. And, there's no negotiating for us. We, we don't get pinned against Google Maps anymore. It's an Azure discussion. It's higher level. And so Azure Maps is the native, location platform for Azure. And the Azure ecosystem. We actually sit inside of Azure IoT organizationally. And within Azure IoT, there's a group called Azure IoT Mobility. Azure IoT Mobility is made up of the Microsoft connected vehicle platform, and Azure maps. Okay. So that gets me to the second part of why Azure maps was created. And that was to power a direct vertical integration into the automotive space for the Microsoft connected vehicle platform. And, last week, 2 weeks ago, 10 days ago, we announced that, TomTom's native integration with their, navigation kit would be part of the Microsoft connected vehicle platform. This is a significant move. Right? The connected vehicle platform brings edge computing into the vehicle. Okay. Edge computing means it runs in the car. It can actually run AI in the vehicle. It can make decisions in the car. Right? And it's trained by cloud computing. Get data, put it in the cloud, you train it, you install modules in the car, and now things are happening in the car. We call that the automotive edge. Okay? And Azure Maps sits quite nicely, right, in that ecosystem as well. But it is an ecosystem play. We are inviting other partners to participate the Microsoft connected vehicle platform, TomTom being one of the most prominent. Okay. And so Azure map is a horizontal set of location APIs or services for Azure customers and a vertical integration for our connected vehicle platform. Inside of Azure IoT. I I've decided to include the customer presentation deck that we give at executive briefings. We have an executive briefing center at Microsoft, every day, dozens of executives fly from around the world to Microsoft, and we treat them to a day of the products they want to hear about. And so this is a significant portion of that deck. It's really long and technical. But I decided to focus on some of the more important facets. I've been speaking about, I mentioned, we're an Azure IoT. I've been speaking about this location of things concept for the last year or so. And it's effectively IoT plus location. So IoT has this proliferation of devices. And when we talk about IoT inside of Azure, we talk about these 3 stages where you've got device sensors that are the actual devices that are sensing things and that data comes up into the cloud. And with that data, you can generate insights. Okay? So you've got present sensors in rooms so you can know that certain rooms have people in them. You've got, thermostat systems and houses. You've got thermometers out in fields. There's a slew of Azure IoT scenarios that generate a number of data insights And what we do with those data insights, our customers are doing with those data insights are then making data driven decisions. Okay? And if we do this fast enough, there's a 4 stage, and that is predictive. Okay? So once we have enough data and we've generated enough AI, we can start to predict what's going to happen, based on machine learning. And so the location of things gives you that important piece of information as where is it happening? Right? I can tell you that there's a field, out in, Eastern California that is too dry. Based on the thermostat and the weather patterns, and the sprinkler system needs to turn on. But that's just one piece, right? Like, Where is that sprinkler? Which one is it? What field does it cover? And that's where the geospatial facets come in. When we talk about mobility, we talk about fleet management. Managing where trucks are at any given time. These are IoT mobility scenarios and how they come to life. And this is an actuation. So this is, I think this is as technical as I'm gonna get for you. But the idea here is that if you take telemetry from a vehicle. Of course, that means the vehicle is connected to the Internet, and the Internet can publish that data to the cloud. You published that those messages up through IoT hub. IoT hub is one of the core products for Azure IoT. It basically can receive messages from devices. Okay? From IoT hub, we have a listener on event grid for changes. And in this particular scenario, what we're looking at as a geofence, geofence is an invisible fence around a particular area. And, we've just fenced off this particular area so that when the truck leaves the fence, we get a notification. It sounds simple, but it's actually built in geography. It's built in mathematics. And so we need to know where the truck is. At any given time, we need a pulse for where it's going, when it's where it is when it's there. We get a pulse reading, And then as soon as it is no longer inside that polygon, an alert kicks down through an Azure function, kicks off alerts through event grid. These alerts could be text messages, or a sequence of events after that in programming languages that can then do other things. Notify the driver that he's off route, whatever other things you want to cascade after this. And Azure maps brings the canvas. Which is powered by Tongtop, and it brings the geofence, which is the geospatial representation of that invisible area. And then the data gets dropped in blob storage, blob storage basically means I'm going to use that later, probably for training purposes. Okay? I wanna train some ML lay machine learning later, create some AI. So I have an iconic slide just like Andrew did. Mentioned we've done some things as well. So when I present this slide, we've got a robust offering for Azure Maps and Azure customers. Right? We've got maps and satellite imagery. The maps are powered by TomTom. Every map Tom Tom has, I have coming through Azure maps. The SDKs, our SDKs, we actually built based on open source. So we took web SDKs and rolled them, and we're pulling in TomTom services through the web SDKs. So as Azure customers are taking Azure Maps SDKs, they're pulling through TomTom Services. Routing, anders covered this, didn't do it justice. There's so much complexity in the routing API that TomTom provides. Shortest and fastest is sort of the simple ones, but also, route optimization. So give me a bunch of points. Tell me the order in which I should go through them. The isochrones, which is how far can I get in 1 minute from here, and 5 minutes from here, in all directions, ends up creating a polygon, electrical vehicle routing, all of the turn restrictions are included? There there's a multitude of scenarios. In fact, I have huge slide that has all of the routing capabilities, taxis, HOV lanes, vans, bike routing. All of this is included in the in the routing API. Powered by TomTom. The search API is everything that Tom Tom has their data corp in their data corpus, I could search for it. Every address, every point of interest, business listing, every landmark available to Azure customers. The spatial operations is a unique thing to Microsoft, We actually built this, and it includes our geofencing service. So we're rounding out the portfolio of offerings from TomTom with some additional capabilities. This gives us spatial analytic so that we can plug in different datasets and do analytics based on spatial information. Anytime geography comes into play, we use TomTom. The traffic data, best of breed, across the board, powered by Tom Tom, we get this as flow and incident data. We also get some measurements. So if you're in the if you're approaching the back of the line for any port of congestion. It'll give you a measurement distance and time from where you are to the back of the line. Once you're in the line, we can actually calculate once you're going to get out of the line as well. So time, it's great insight for time management. Time zone API, this was actually a pretty popular API for Microsoft, We built this for the windows team who wanted to get off of their own time zones. But, this gives you, given a point in in the world. We'll tell you what time zone you're in, the offset the offset to GMT, as well as, the time, the actual time there, the wall clock time. We just introduced sunset and, Sunrise times so you can automate IoT scenarios. As a part of that too. We have a geolocation API, takes an IP address from a computer that could be a phone, that could be a PC, and we'll tell you what country that, location is coming from. Mobility is actually an additional partnership we did with a company called Moveit out of Israel, So now you can see there's a partner ecosystem at play. We are very partner led in Azure Maps when it comes to this rich deep content and intelligence within the industry. And so, while TomTom brings these rich data and services, the freshest maps, Moveit does the same thing for transit and mobility. And so, in fact, our partnership has extended beyond, and now the three of us are talking. And so We actually announced earlier this year, the 1st multimodal system that crossed both transit and road graphs. And so a unique offering powered, coming through Azure Maps. And then data storage, if you wanted to store your data in the Azure cloud and use it with Azure Maps, you can use the Azure Maps data storage. And so there's a myriad of applications. You can imagine Microsoft has access to quite a developer ecosystem, And so this developer ecosystem is building a multitude of applications, ranging anywhere from mobility, fleet, and logistics, to IoT scenarios, inclusive of indoor maps, facility management, cloud, mobile edge computing, All of this is happening, through the power of Azure Maps and location. And then spatial analytics and AI. This is also part of what we're seeing is the developers who are building on Azure and using location are building out super rich cutting edge type applications and technology. And as we go along this journey, Tom Tom is just coming with us. And so these are just some of the headlines that have come. I always, I want to always, confirm and reinstitute the fact that we decided to not make maps It was really hard. I've been at Microsoft 17 years and was I was in charge of MattPoint web service. I was in charge of MattPoint, the DVDs. I was actually responsible for killing those. I'm sorry. A lot of people love those. But it we had to change our business model. DVDs were going away, and we needed to keep up. I was with the virtual earth team when we built 3 d and had weekly reviews with Bill Gates. I was part of what became Bing mats, and to this day, you know, the Bing team is still licensing data ingesting data. And now they're working on how we ingest Tantom data to make Bing search rich, to make Cortana smarter, right, So we're actually using both products, the uncompiled maps for Bing, because they have to ingest it and train, ranchers inside of the Bing search engine. And we're using the APIs. Directly for Azure Maps. And we're also very enterprise ready. This is an important facet in 2019, and it will get even more critical moving forward. We talk about enterprise ready. We talk about enterprise scale, right? As our customers grow, we grow. We have, elastic scale is not a real thing. It's just a concept, but with our partnership with TomTom, we've been able to scale I say we wake up every morning and see who our customers are. Our customers could unload on us a 1000 QPS, 2000 QPS overnight. And we need to be ready for it. And that's the enterprise scale we're talking about. And so the infrastructure that TomTom has built on Azure is actually scalable to They have to scale with us. We treat them as a back end engineering team, right? Globally available. So this is accessible to all the customers that Microsoft has around the world. And then we talk about trusted security services. When I joined Azure Maps and I launched the product, I had to go through a plethora of, trials by fire, if you will, 375 different tasks for compliance. Security, accessibility, usability, privacy. We are fully supportive and checked down all the boxes for compliance in Azure. And then the pricing itself, super competitive. I mentioned we can lean on enterprise agreements So as customers are signing up for Azure, they have a menu of options that they can go choose. And Azure Maps is right there waiting for them. They can select it and start using it immediately. They don't have to talk to me. I'm much like Anders, you don't have to talk to me, but you can if you want. You can just start using the service. And so, it's been a big win inside of Microsoft. We are we are Our growth is significant. It's 200 percent month over month in terms of customers, for Azure Maps specifically. And so we and we only GA general availability, May of last year. And so, the uptake has been significant. We're gonna continue to grow going to continue to innovate, and I will continue to push requirements on TomTom to, keep their engineering team on their toes as well. Yes, my first question would be, the mapmaking, basically partnership that you have with your, your clients. When was that introduced, and, how often is it, is it used? So can you give us a bit of feeling or how big this is within, within enterprise, or maybe, as a measure, you know, out of doing roughly 160,000,000 revenues what portion of revenues to the partners represented the total pool. Well, so okay. So in on the mapping partnership, I'll say it's less than a year. We introduced it. Of course, you always start with a few to kind of like be one of the essential things are working. But I think what's important there is that if you want to go that route as one of our partners, you really need to be super serious about it. Meaning, as I said, the trading part of where you have to have certain number of people, because otherwise, it doesn't really scale for you. So that's working fully now. It's implemented, and we have a number of strategic partners working on it. And we allowed, in this case, to mention Ubers working and using it, but there's others as well. But it's not reflected to our revenues, reflected to the modifications we can do on our map database. To basically making our maps fresher, much faster, and more efficient. Hi, Francois Xavier Brunney from UBS again. Quick question on the, enterprise, specifically on the indoor data. And as we see in the in the market, Apple, probably one of the main rational for for moving into its own maps is to have more information like street, street view, probably indoor maps. Here is offering the same kind of of solutions. Is it something that Tom Tom would look at, in terms of detailed demands for this? In the medium term. And maybe we can ask as well if from, Azure because of perspective, is it something, you know, that is needed as well from your perspective. So you mean indoor map specifically? Indormat or street view, you know, kind of, additional solution that maybe? Yes. So it takes 3 views to look around as privileged calling. And so, again, of course, that the advantage that I explained with Hong Kong delayers. So in this case, Apple had been building, look around, as they call it, on top of our data, which is kind of similar to Google's street view. For that specific, you can say, Kate, we don't have any plans to jump on at this stage to, to build a similar product as, as Apple. Yep. I could answer it from Microsoft. The so the street side or street view, we are we did a collection back in the day, gosh, 2010, 29, with the virtual earth and and Bing Maps. And, We still have the data. It wasn't widely used, and that could be just a reflection of the product itself. We haven't had a lot of customers ask for it. A lot of the scenarios are consumer based. There are some B2B scenarios or even B2B2C scenarios. But we haven't had many customers ask for it. I could tell you that in, 2019 asking for that and the level of investment it would require from our management team is not gonna happen at Microsoft. So, we're very stringent on our finances and keeping track of Azure specifically. So given the requests, their lack of requests, I should say, it's not terribly interesting the indoor maps is interesting to us. And so, there, there are some things that if you look across Azure IoT, if you look the digital twins, for example, and Smart Buildings investments that we've been doing. There's some interest in doing some indoor mapping and understanding what that technology looks like. We announced, Azure spatial anchors, prior to this. So there's there's some things happening that would force us force our hand a little bit now. Currently, Azure maps actually would support the, the integration of an indoor map. We have really, we have proof of concepts and actual customer applications, that we've demonstrated at shows. It's natively integrated in you could take a raster layer and integrate it in our DK. You can take vector data. You can do these things, but today, we, we don't have an indoor maps platform. But it's certainly something that's really interesting for us. Yeah. Marcus Inc. ING again. First question is on, How should I think about the market growth? Because it feels like this, the market itself is growing and potentially you're taking a larger share of that market? So what kind of potential, would that be for you on, on a growth level? And the second one maybe meant for Chris, when you took the decision to go for, for a tone tone. I assume they're also looked at alternatives. So what kind of, you know, what, what, what, made you finally decide to strive for TomTom as the best solution for for Microsoft. Yes. So on the so as I said, the our estimate is that that the market is around a $1,000,000,000 today, but but growing. And we, we crunching through all these numbers as, as we speak, what kind of growth we are seeing because, of course, it's not always that easy to, to track these things. So, I think we'll have to come back on, on that one until we have some more cloud because, as I said, also, that we're relatively new in, in that space. There are still some some things, yeah, we need to figure out before we can kind of make it more public in terms of the growth. We're also working with Microsoft there to see what kind of trends they're seeing, of course, because we are, of course, helping each other in this last year. So, hopefully, in the near future, we'll be able to, get some more clarity on that. Yeah. And our decision, for Tom, Tom, became very evident. I mentioned that I ran the Bing Maps data ingestion team. And Part of my job was to actually look at the data in different data providers. Bing Maps uses a number of different data providers. And, we looked at the raw data We actually looked at the raw data and found it should be better. So regardless of the services that were being used, where most people were testing, the actual data itself, and we did ground truth thing for this, turned out to be, better than what we were currently using at the time. And so that's one piece. The second was, you know, this this editing partnership, is is humongous I can give you an example in that it would take anywhere from 12 to 18 months for an edit to be fixed previously. And that is from the time of submission to a review process, to a field, true thing to an actual fix submitted into a quarterly release. And then, of course, our 6 to 9 month release cycle. It it was painful. And so having the ability to, stand up services that will receive our feedback immediately It gets reviewed by their data team immediately. There's prioritization set to all of this. I guess in the end, it comes down to TomTom's willingness and flexibility to partner. They are just a solid partner for us. And their data is better. Yeah, Ivan. Again, maybe can you elaborate a little bit on kind of the the the partnership between the two companies? I mean, is it, is it for a very long time, or is it kind of that you can cancel it potentially immediately, and also suppose that as you were gonna grow tremendously, and, potentially, you know, capable maps of the panel. Google Maps of the, the Theroniski being the number one map, will top down, a benefit in, in equal amount, I. E. If you grow or to grow along with you? Yeah. So we we now, it was it's it's a, yeah, it's a multiyear agreement we have signed with Microsoft. Right? So we definitely have a number of years to partner. That was kind of the whole idea also with, of course, us going to that cloud and putting our products there and for Microsoft being able to go to. I would, of course, take some time, right? So that's definitely, definitely multi year contract we have signed with, Microsoft. And then your other question, Elias, sorry? If, if Azure Maps is going to grow, the way that's probably you guys are expecting it to grow, will don't benefit in equal amounts in terms of So so when I get a call from TACro, I need to grow the revenue. I call Chris. True. That's that's that's just a routine. Right? I was wondering where those calls came from. Yeah. Yes, as we grow, Tom, Tom grows with us. And so I should be explicit about that because the maps, the search, the routing, and the traffic are all core to Azure maps. As Azure maps grows, TomTom's use of through Azure maps grows as well. And so TomTom grows as well. And maybe, from your perspective, I mean, Google Maps has been very dominant in the, in the consumer space. What will it take for you guys to actually beat Google Maps? That is a that is a hard question. So Google is a formidable competitor. You know, they've, effectively dominated the market for some time and especially in consumer mapping. But they're not impenetrable. Right? I think it's going to take a number of years, and a different position entirely, to basically change the way Google has won the market today. If you look and uplevel this to what folks are calling the cloud wars, Google's a distant third. And so we focus on that perspective, and that applies to maps as well. We're part of the 1st party Azure ecosystem. And as Azure grows, Azure Maps will grow, Tom, Tom will grow. But it's it's it's tough. Google's raised the bar to be extremely high. I think it's just gonna take a combination of partnerships, and a new strategy of how we go about doing maps. I think the map visualization and what exists what exists today. People are finally starting to appreciate and understand how great it is. Like, there's, generations now who didn't understand what it was like to have a phone without a GPS on it. Right? So they're kind of spoiled in that way, and they actually want more things, which is great. So they're pushing the boundaries, and that comes into this invisible part of the map as well. Like, you need to understand what's there without being able to see it. And this is that's remote monitoring and being able to control drones and other mo mobility, and and, like, ride sharing scenarios, things like that, where you're not on the ground. You actually don't know, but you need the information to be there readily available. And I think that that perspective in changing it through IO the IoT lens for us, the Azure cloud lens for us, it actually just kind of permates into a different strategy, that will just be different. I, I, I have no plan or intention to go meet Google Map especially not by myself. And even in partnership with TomTom, like, that would be really, really hard to do. I think it'll, it'll take a group of us to basically go out and create a new market, to change the game. Good afternoon. Welcome back. My name is, Antoine Toshi. I'm running the automotive business, at TomTom. And I want to give an overview of where we are today, but also how we see the, the market, megatrends as a, as a great opportunity for TomTom, in the automotive business. And it starts with our product portfolio. You've heard about map software and services already this morning. Yes, we're a map company our transactional map making process, produces, navigation map, high definition map, but also ADAS map. That are increasingly relevant in the automotive business. We're leading in navigation software with more than 25 years of experience in the, in the user experience and ease of use. And traffic is definitely, our leading products, we're leading on the markets in automotive with traffic information, but that is basically us being a big data company processing massive amounts of data, and that capacity, also works with our products than traffic, and that is recognized across our industry. How did we start Basically, we, introduced, back in 2009, a product that dramatically changed the landscape of navigation in automotive. Based on the contract with Renault, signed in 2007, Geneva 2009, we introduced, this coming at TomTom Products below €500 best in class in terms of navigation features and completely changing the game in terms of in car navigation take rates. If you look at where we are today with some of our biggest customer, the take rate is between 50% up to 80% depending on the CAL lines. By that time, you were talking more 5% 15%. So we completely changed the game by introducing this innovation. We continued, in 2010 by connecting those devices, actually providing this same device, but with the SIM card in it and introducing real time traffic information in the automotive industry. That also was the starting point, and we became the market leader that we are today in traffic information. We also, introduced, 1st electrical vehicle navigation that was in the Renault Zooey, one of the very first EV car being produced at mass market size. And we launched more recently ADAS based, level 2 system in a couple of cars, but also trucks. We also expanded on a geographical, coverage. And so what we announced this year with, MG in, India with this Hector car, is actually, the 1st navigation system for us in, in India, and they also take us to other regions. So altogether, technology coverage and user experience has been one of the, have been the major drivers for our developments in the business. That growth of the automotive business is also supported by the, now well known case megatrends, so connected, automated, shared, and electrified. Connectivity is an interesting topic. You could say today in Europe, all the cars are connected. They all have equal. Equal is a connectivity that is only activated, either if you crash or if you press this little red button. If you think about connected services, how can we update our software, how can we update our maps, this type of connectivity is not going to solve the problem. So what this connectivity is about is really, bringing decent data, exchange in the car. Allowing for software updates for real time maps access, but also to get data back from the sensors being increasingly included in cars. And since this connectivity is also a cost trying to monetize what comes out of this connectivity to compromise, compensate for some of that connectivity cost. In automated driving, Obviously, you know, ADAS and HD content, is getting, market attention. We also see safety services being now, requested. So what is the connectivity coverage of this or that particular location can we offer connectivity type of map, or, can we think about, what is called road clearance which is a service that would tell OEMs, well, in this particular location, autonomous driving is allowed. Or you should put this feature on hold because of weather condition, accidents, animals, or any other hazards. We also strongly believe in and the navigation space. If you look at how our business develops today, we're basically talking to different engineering teams. Navigation is more in the infotainment engineering department at our customers. ADAS and AD is more managed by chassis control. Ultimately, if you talk about user experience, how do you bring this technology into cars so that people understand it, use it, are delighted with it, it means that you merge the, the navigation content with the map and you're able to represent your ADAS features or your ADE functions, at the same location, the same style as you represent navigation. Finally, electrification, a very good case for us as well, because EV cars, bring a lot of advantage, but they also bring a ranch anxiety. Ranging society is a problem that's location technology can really help to solve. And that is because we know about the map. I'll come back to that. But we can bring electrical vehicle services. We can deal with charging stations. And, over time, organize that, you know, not only you know where the charging station is But when you reach that charging station, it is available because you've booked it in advance and the transaction can also be taken into account by the car. Those trends can dramatically boost the navigation take rates in automotive. If you look at what has happened in the previous years, we've been growing steadily but slowly, from, you know, 29, 30 and plus, if we would project, that's a trend towards a 2030 we would be around, 45%. We strongly believe that whether it's the connectivity moving towards more automated driving cars, shared mobility or electrification. All those trends, generates, real use of in car navigation, real demand for something, some system, that addresses those features in a proper way. And that can really boost the take rates in, in navigation. Now This will only happen if the expected user experience from the drivers from the end users, as Harold mentioned already, this morning, is taken into accounts and is actually addressed. And I think we're at a turning point today where most of the, in car, systems have limitations because the, the software is not decouples from the, the hardware, there for it's not easy to, it's outdated when it's launched, not easy, to update. Map is not online and also not easy. To update. Ultimately, the resulting customer experience is not at the expected level. That has generated reactions from some of the OEMs. You've seen bigger screen, coming up different layouts, vertical screen, horizontal screen. I could say Python is going horizontal and vertical, right, in all directions. Or a dimer are trying to better integrate, the cluster display, together, with, the central stack But ultimately, what is beyond that, so how can we help, those, OEMs is more behind? The screen and is in helping them in the bringing the connectivity, connecting actually those devices developing the software more independently from the hardware and moving into navigation as a service much more than navigation as a product that would be developed exactly at the same pace as the car is being developed and not updated after its, its deliveries. The fundamental change is really in, in this, software decoupling from the rest of the car and update through connectivity. So how can we deliver that ourselves to OEMs, how can we support this transition? Well, first of all, it's in the, it's in navigation. Right? So what we think in terms of what we call best in class navigation is not only what I already mentioned, So software, fresh software from the start and updatability, but it's also getting data on the, on the actual usage. That was also something that we've demonstrated in Frankfort Motor Show together with Microsoft's getting data from the actual usage, what are the features that ultimately drivers are using, how many clicks are they, pressing on the, on the screen? How far do they go? When do they drop this or that feature? What is the, the pattern? That, that they have in their behavior, learning, all of that can dramatically change the view we have on how navigation works and how want to bring digital that feature back in the car. Autonomous driving So ADAS or AD also needs to be better integrated into that experience. We're ideally positioned to deliver that. EV, I'll come back on that later on, but I think that's also a very good case. Also, connected to the digital life. I was, talking to Chris last night, he was telling me how he implemented Alexa in, in his car. So I was very interested. I thought this would be a fantastic software experience. It ended up ordering a small Alexa box on the web, plugging that on the cigarette lighter or the USB plug then, bridging it to your, to your smartphone, Chris, correct, right, to get connectivity, then bridging this device to the car through Bluetooth to get the sounds over the speakers. Now I thought there must be value in having Alexa in your car, if you want to, go through all of that process, and that is what Chris explained as well that once all of that is done, he has access to everything in his house. And his life, that is Alexa connected. So there's real value in bringing Alexa in the user experience of the overall infotainment. It changes the picture in terms of voice recognition and so on and so forth. But definitely, the value is not there in terms of, you know, how do you all that in your car, at the moment, but that tells us there's market demand that needs to be taken into account and addressed in the way we develop our product. And overall, right, whether it's, voice recognition, destination entry, digital life integration, ADAS or AD integration. It's all about a user experience. It only works if you move from the current onboard to more online, more connected. And by the way, you don't want to address Alexa only because then if you're a Google, home customer, you're not satisfied either. So it means that we're able to have our software evolving, and taking into account all those different offers from, end users. Now if we zoom into, some of those opportunity and and, I'll stop here with the, the connected services. We've been very successful, in, in that space. I mentioned already, traffic information. You see, a fantastic, growth, forecast here. I think navigation system without a proper traffic information in the future will not survive. And therefore, you see a strong growth for traffic. You also see, that the, the number of services that will be integrated in the packages that we deliver is increasing. Right, and where we started with traffic, we quickly also introduced, speed cam, parking, I think today, we're looking for parking spots, but tomorrow, we're going to look for parking plugs rather. And that continues ADAS and AD also requires more hazard warnings, weather is also important in certain conditions. And the moment you go into EV, but also parking, it is the same space. We're interested in you know, how do I make sure from a user experience point of view that's my charging stations available or my parking spot is available? Therefore, we talk about the capacity to book those things and then to, to pay for them and just making everything smooth along the experience for the, for the drivers. So the, the, the, the level of services is, is increasing, but also the number of services that are in these, in these packages. On AD, we've been also quite successful. I think you've heard a couple of things on the strength of our maps. I think that also has played a role in the businesses that we've won in the, on the HD Map market. It's a new space. There is no legacy. There's no existing market share. So we see our customers deep diving in the technology and then, making their choice. And a significant portion of them have decided to go for Tom. So I think that's the best proof of the, the quality of our technology. It's true for HD. It's also true for ADAS, as an extension ADAS attributes have been in our maps for a while, but they're increasingly being used by customers in, in ADAS context. And that can be driven by new features, coming in, but also, Euro end cap in, in Europe is driving, for speed limits and speed assist system is driving an increasing adoption of ADAS data. And also, Europe is, talking about regulation around those, intelligent speed assist system. That is a very good opportunity for us. We also expand our portfolio of, of services. I mentioned that already. That's the road check or road clearance type of product. And again, we strongly believe in the, ultimately the merge of, navigation and ADAS AD features. Into one customer experience. Moving towards EV, This is where our complete portfolio, completely fits the market. It starts with maps, of course, we, you know, you drive your EV on the, on roads. You want to know where the charging stations are But we will also use the consumption model coming from the car, and therefore, we need curvature, and slopes or gradients from the map. So there's a lot of map data that has specific use in the EV space. Charging station, I think we have still 23 different types of plugs worldwide. So making sure that you have a charging station is an important point. Availability of that particular plug is also is also crucial if at the end you reach the station with a low level of battery. And again, you want to be able to book you want to make sure this station is going to be available and you're going to charge safely. On the software side, we're looking at, what is called multi stop routing. So I think in this example, it's a drive from, yeah, Amsterdam, maybe to, niece or, Marseille, quite a drive. There's a bit of strategy to decide where do you want to stop? How long are you going to stay? And that depends on what is your battery year type and what is the best consumption charging cycles. That you want to, that you want to follow. So there's a lot of interaction between the OEM on the consumption model side but also the configuration of your journey what is your destination? Also, temperature, will, will have to be taken into account if you need climate control or heating, or not. And also, at some point, you know, your digital life is going to come in if you, if you prefer to stop at some friend's location instead of, spending an hour or so in a, in a service, station. So all of that comes together, again, in, in the resulting driving experience is in those electrical vehicle cars removing the, the range anxiety from customers. And finally, this EV experience doesn't, own, is not only limited to the in car, right? Most of your trips, you prepare them. You want to check before you depart. You want to make sure your car has enough battery to reach your destination. All of that should happen on your smartphone or on your laptop or screen. And nobody understands anymore that, there is a clear separation between what happens in your car and what happened, in, in the rest of your digital life. So as you can see, EV is a fantastic use case for the complete integration of our product portfolio, but also to push OEMs to better consider the integration between smartphone and in car, experience, and that's also where TomTom can support. But ultimately, it should look, like this. K. And, yeah, last, last, but not least, is the, the digital life part. So I already mentioned the, the example, of Chris. I think that is something where also, we need to help OEMs to, to open up, and make sure, you know, whatever is your digital life, content. You know, if I'm a teaser, user, I want to get in my car, be able to use that without having to do all sorts of clicks and plugs and things that, that are mandatory today, voice, I think, is a, is also a fantastic example and, and use case for us to get OEMs to change. They've been trying to get voice recognition working in cars. It has never really been amazing as an embedded feature and completely changes when you move to, to online. And the result of that is, the Alexa's and others are obviously looking into what's happening in the automotive. And again, you cannot be exclusive to one or the other. You want to be able to address that. Whatever your user is, using, and I think that's part of what we need to support as well. In terms of business updates, in the, in the past month, we've been announcing quite a bit of news, navigation we launched, with, with Jeep, Renault and Nissan brand, I was talking about 2009, you know, that was the first, Clio for us to go with our navigation. 2019, 10 years later. The nuclear is also introduced also in Geneva and still, with TomTom. Data in it. So I think that's, quite impressive. Our customers, they tend to stick to our technology, continue to trust our teams, and our capability to move them to, the future with their customers. We also introduced IQ Maps in India. I already mentioned that IQ Maps basically make sure you drive the freshest map available, wherever you go. And if you're in India, it's, quite a big amount of data. So you don't want to have the full of India updated, every time, but just the portion of that map that are of interest to you, and that is what IQ Maps is delivering. We're also preparing a big, launch for, for a big OEM in North America. I think What you've seen is over the years, we've completely changed our game in, in North America. We're delivering Nissan. We're delivering Subaru. We're launching with another OEM. So our business in the U. S. Has dramatically changed. Connected services, Volkswagen, renewed, our agreements, together with them. MG, I already, already mentioned, and we won, a couple of, of, major deals. So traffic has been a fantastic door opener for us in the automotive industry and continues to drive, discussions. But we also delivered those services part of the, of the full package. Evie, as I mentioned, we pioneered that technology with Zoey and Renault. We're We've extended that to Nissan LEAF. So I think with that, in terms of volume segment, we're definitely leaders BMW also trust us to deliver online, this type of service to, to their cars, also routing And, and for Jeep, they introduced, hybrid versions of, renegade and Compass, and those are powered by TomTom Technology. In the automated driving space, it's been managed already, we've won multiple OEMs again. I think technology, and trust have been the key driver for those decisions, at OEM. We've launched AutoStream. I think William will tell you everything about, what that technology is about, basically, how do we distribute, maps, HD maps into cars? And, with our ADAS map, we're already, in, in business and our customer base is growing, fast We have now more than 1,000,000 cars and trucks driving around, on a, on an ADAS. Map from TomTom. I think that's it for me. What you can see is that through our portfolio, our capability to breach together navigation, which has been, our world for, for a very long time now, and ADAS and HD features that are now, vastly developing we're best positioned as company to help customers going through this transition from onboard to online securing that they can deliver the user experience that customers expect? Thank you. So I'm Kaes, Kaes Van Dock. I am a Chief Product Officer at TomTom. I've been with the company for about 8 years and have always been deeply involved in the end user experience of, both automotive as well as, consumer, consumer products. And I would like to spend, the next 15 to 20 minutes to give you a heads up, a view of how we feel, how we think that customer user experience will, will evolve and also how we think we can take a differentiating, position in, in navigation comparison to the, to the competitive field. But before before I do that, let me, kind of zoom in a little bit closer on what what Antoine already described that the, the automotive industry and especially software and automotive is, is in, in, in times of, of disruption. And there are a couple of, couple of key kind of, enablers that are, that are happening in that, in that space. First of all, I think we see, automotive software makers struggle, if not failing to meet, customer expectations. And customer expectations have rapidly evolved because of mobile phone usage And this is a quote from, JD Power. JD Power is a well respected, automotive consultancy, voice of customer company in the in the U. S. And they reported last year that about 20 percent of new car owners with navigation, in their car actually never uses, navigation. And an even higher percentage is stopping the use of embedded navigation in the 1st 90 days of their new car usage. And instead, people flock to their phones. So they trust phones for navigation and other kind of, digital life experiences that they expect to be able to continue to use in the car when they move from all these other contexts into their, into their car. And that obviously is because the experience delivered on phone is, is by far superior to what, you get in most, most cars in terms of up to date software. In terms of fresh content, speed of, of user experience. So that's the first, first point. Another point is that, the paradigm shift that happened in the mobile phone industry about a decade ago is now happening also in the automotive industry. So where you see the replacement of a lot of feature value and end customer value through hardware controls, shifting to a software first, way of delivering that value is a paradigm shift that is now happening in, in automotive. And that delay is obviously because of, the nature of the, of the industry where development cycles of cars are taking taking a very long time. But also because these kind of disruptive elements are, are happening, And what you see in the car space is that the environment becomes more familiar to what users expect from their daily life experiences, right? So the car becomes more like how you interact with your phone, your TV, with your, your home automation, software. So we see a vast reduction in hardware controls and buttons and levers and, and, controls, as you see on the left. And a much more kind of software centric, user experience driven by voice, by touch and by, a limited set of steering wheel steering wheel control. So then, obviously, a third disruptor is the entrance of, of Google in the in the car. So Google Automotive services went from mobile first to Android auto to becoming really embedded in the car, bringing the just quoted before phenomenal Google Maps experience in the, in the automotive environment, which is obviously a big shift from where most carmakers are today. Now the question is how are we, as TomTom, how are we going to deal with that and how are we think there is a path, forward in our, in our navigation software use experience. And we identified kind of 4 different pillars which we, which we base our our strategy on. First of all, is to to be really mobile competitive and to embrace the the practices, the best practices of the phone industry and the mobile industry more, applied to our own, full stack of navigation products. So rather than having embedded maps and having software that runs in the car, we're currently in transition of shifting all of that to an online reality and make sure that part of our navigation software is all running in the cloud. We had a lot of, proof points this morning about maps to Maps moving to the cloud. So embracing that paradigm and being online first is currently happening, and I'll show you some, some proof points of that. Integrating with users digital life is, is part of that. So how can we bridge the, value and the service that people trust on their phone how we can bring that into car and make that transition as smooth as, as possible. Connectivity is obviously required, And that has always been a, yeah, kind of a difficult, discussion with automotive makers broadband connectivity delivers the best user experience, but it also comes at a cost, right? So is that cost being transitioned to the user? Is that taken by the OEM? It's a difficult, position to move forward, but it's essential to deliver a, a strong user experience. And lastly, being voice centric, is key. So in the car, safety is what we are all about. And, interacting with, software and features through a lot of kind of manual actions is, is quite unsafe. So we're building, we're creating, we're preparing ourselves for a voice first, user experience of our, of our navigation software. The second part of the strategy is to really differentiate in navigation itself. So rather than, relying on kind of mobile derived smartphone based navigation only, we feel there is a position for navigation to be more integrated in the car itself. And it was mentioned a few times, like taking AddAS as an example, and I'll show a few more examples of that later in the presentation, like taking All of the data that the car generates, the sensor data, what the car is observing in its environment are perfect, kind of data points and feedback mechanisms for drivers to integrate in the navigation experience. And I'll show a few examples of that. Thirdly, we feel we need to kind of also zoom out from navigation only. So currently, our our navigation software is often part of a, in vehicle infotainment system where many other applications are kind of, collected in order to deliver an end to end user experience and all those cases often have their own kind of user interface paradigm, their own way of working, their own way that, that, their information is being organized and being, being accessed. And we feel strongly about kind of creating a more holistic, way of interfacing with that software in the car. So how you control software, how you control it by voice, and by touch, and by other ways of input, we want to create a view where moving from, say, communication to entertainment, to navigation, to controlling features in the car feels much more the same across all those, across all those applications. And that's obviously zooming out from navigation only, but we feel by only focusing on such a more holistic user experience, we can actually deliver a more delightful and better user experience for car drivers. And lastly, we don't do this alone, right? So it was mentioned, MCVP is an important technology partner, so having a robust scalable cloud platform that enables, a great in car use experience where you have authentication, a good data collection in the cloud, lots of services with high quality and high speed delivered into the vehicle is, is essential. But also on the voice assistant angle, is not technology that we would ever develop within, kind of our own company, but relying on right, the right complementary partners to, to provide that more holistic, user experience is the way to go and redeveloping those, those partnerships as we speak. Close collaboration with OEMs is another important angle. We are, I think, like, OEM friendly, right, like we work with OEMs. We we create, we have deep engagements and partnerships with OEMs to together build, build solutions. And for our next wave in navigation or IVI that is not any, any difference. So understanding OEMs needs and requirements when it comes to customization, to create a use experience that feels authentic to their brand, rather than a, a broadened solution by, by a third party is an essential, element there. Now, zooming into a couple of, a couple of proof points. So we're moving our navigation stack to an online, online first, reality. And, TomTom Amigo is the first, proof point of that. So we are developing, as we speak, a lightweight, navigation application where all of the navigation software runs in the in the cloud, runs online. So all your maps, search and routing and all those aspects around navigation are coming from, from the, from the network, and there's only a small lightweight application footprint happening on the client. And what we're trying to do with Amigo is to kind of extend the already great presence that we have with, with end customers because we believe end cost and the relationship with end customer is the way to, ultimately deliver kind of the most delightful experience as possible that we that we then bring to, to our automotive, automotive customers. Amigo is in open beta on the Android form. It was released, a few weeks ago. So if you have an Android phone and you have the, the Tonto Speedcamp app on your phone, you can upgrade to Amigo to experience, this lightweight turn by turn yourself. The second initiative that we've started is product concept development around what I mentioned is broader scope of, of IVI. So we're currently doing a product development, concept development, around a end to end infotainment or in car vehicle infotainment system. Again, also taking a view on how communication would work in the car, through your phone, or through, conference calling, how end payment would work. So the ability to play music either streaming from the internet, streaming music from your phone, or from, from connected, music services and how that all kind of interplay also with navigation without any application switching and context switching. And redeveloping that view in order to to, again, have a view towards, towards OEMs of what we feel an integrated experience could, could look and feel like but also to have a, a product that we can test with, with end customers and test with OEMs to, to see what kind of kind of features would, would really stick and work for people. But let me dive in a little bit into the, the navigation opportunity itself. As I mentioned, we also feel that in navigation software and based on the stack of technology that we have from MAP to add us to, autonomous driving HD data to live services. We feel that on top of the stack, we can actually also play a larger role in the in car vehicle experience by bringing those technologies together into into a driver experience that is more front and center than what navigation is today. So this is a, this is a demo that we built a, a few years ago, a real, a real world working proof of concept. It's based on HD data. So this is an HD map rendered in 3d We take the camera, camera position from the car into account in the navigation experience. So we see the accurate lay position where the car is in, and we give kind of this yellow bow wave nudge to, move the driver into the, into the right direction. So rather than giving navigational instructions like take the right at the next junction, we can actually much more smoothly guide the user through the right lanes in order to, yeah, make their navigation experience kind of much, much more natural and much more fluid, compared to, compared to today. And it can only be done by taking not only the map data from our map service and integrated in the navigation experience, but also take information from the car sensor data locally in the car and bring that together into one unified user experience. Technology already. So this is not only concept work. It's in our most recent, version of the TomTom Go navigation application, which is more like our, embedded Maps, premium navigation application where we brought this whole concept of moving lanes into the, into the user experience. And this is actually one of the differentiating features in that, in that application. And again, by bringing in sensor data, we can enrich it, that even further. And that's also trying to address a real world problem. Because if you take a driver in a modern car, today, they're quite a lot of different places in the car where they get their feedback from in order to take navigation and driving decisions. For example, they may have a screen or a phone with navigation software running on them. They may have, a next instruction panel, right in front of them or a center, center stack, display. There may be all sorts of warning mechanisms like gentle warnings coming from a life, service. That can be, specific hardware based features like, collision detection, blind Bot detection that can sit in the mirror or in the, in the, the display right in front of the driver. There can be collision warning, little LED screens and yet another location are on the steering wheel. We're getting all sorts of kind of, cryptic visualizations about more advanced the features. So for example, this is the user feedback for, l 2 driving, where the car kind of sticks to the lane and keeps this to the car in, in front of it. Sometimes it's even more cryptic, little icons that, that light up somewhere. And then as the outside, kind of world information that the user also needs to kind of digest and understand in order to take decisions. And that can be a simple message that can also be part of the ADAS map or it can be a much more complex message that is quite difficult to parse when you're driving by quite fast. We believe we have a position to take all that information and kind of, bring it all together into a unified driver centric user experience. Because this whole hodgepodge of features that is sprinkled across the car feels a bit like a bunch of ingredients where the chef and the rest fee is, is missing. And, and we think we can, can play a role there. So this image brings a couple of those items, together. Where we see a view on the road ahead, and that is not an unfamiliar view from what users expect from navigation today, but it has a lot more information. So this is not only a green line that gives you guidance, but it's also an HD map that gives you a real world view about what you see out of the, out of the windshield. It gives you sensor feedback. Right? There is an, an a car in the on the right of me that is trying to merge to the left. The the the car actually observes that maneuver and, and warns me for it. So it's a much richer experience. So we bring in this kind of setup together, our map obviously ARAS data, routing and guidance as we know it. It also brings in information that is coming from the traffic service, life services doing a gem tail warning with a gem that is around the, around the corner is, is integrated. But also, as I mentioned, this the sense of feedback from the car itself. So imagine my car detecting a car, another car in a blind spot, or there's a collision warning, or, as I have shown before, this, this lane position thinking, we bring all of that into that same, visualization And that goes all the way up to, deeper levels of automation. So this view can also guide users towards, autonomous driving in the end. We know that the adoption of autonomous driving is very much a user trust and a safety issue, like users will need to get to trust their car to make, make the right decisions. And that all starts with building trust through visualization. So if the car can explain very clearly to the driver, what's happening outside, what kind of decisions it's going to make, how it's going to move, what kind of maneuvers it's going to make, the better that cross building will will happen. So this is not just about next generation navigation, but it's also a view on how that can expand to an autonomous reality further down the road. And these are a couple of, visualizations of how we think we can bring that, bring that to life. So imagine this is the cluster display in front of the driver. Here's an example of a collision detection integrated into, into navigation. Here, another example of a blind spot detection. So I'm instructed to move to the left, but there's actually another car to the left of me, so it's not safe to take that maneuver. And as soon as that car has passed, I get the green light or the blue light in this case. And I can move over to, to the center lane. Another example is, as I mentioned, level 2 automation. So the cars sticks to the lane it's in. We visualize that by a couple lines next to the line that I'm currently in. And as soon as it needs to change speed, because there's another car in front of him. Again, we use that same, kind of rendering environment to visualize that, that context. It's a little hard to see, but there's a white car in front of them and this is being checked. But again, also for online information. So if we know there is traffic around the corner and you're approaching it to too fast. We can do our Gemtail kind of warnings of over speeding in that exact same, same context. And lastly, an example around how that could even traverse into autonomous driving. So there's an autonomous driving zone coming the driver is informed about that, that zone, coming up. There's the trends, the handover to the, to the autonomous car system. And again, all that information is being brought into one place. So rather than sprinkling dialogues and messages and beeps and notifications all over the place. We believe that that view on the road of the next couple of hundred meters, in front of you is going to be a, an area that we are very familiar with We've been rendering that view since our very first BNDs, and we believe there is a strong possibility to naturally grow that into a next wave of, of navigation. I still remember very vividly the first time I stepped into an autonomous vehicle. The engineer opened the door and said, you go sit behind the steering wheel. So I sat there, and he instructed me to drive to, a highway stretch He said, now you press these 2 buttons, and then you can let go of the steering wheel. And that's when the magic happened. That's when I knew this was gonna be something, right? This was fantastic. Within minutes, So I was talking very excited to the engineer in the back who urged me to look to the front of the car again because it wasn't that save yet that I could be talking to him all the time. So the autonomous driving is, you know, if you've experienced it, you know, it. It's gonna be huge. Right? The the benefits of it are just enormous. So I'll talk a bit about autonomous driving today. Then I'll ask, one of our partners, Eric Cooling from Zenuity to come on stage to explain some of the elements that we don't make. And then I dive a bit deeper in, what the roadmaps is, how we make those maps And I guess you're dying to hear what the market size is of this opportunity. So I'll dive into that as well. So a few months actually after that experience in that vehicle, I was leading the autonomous driving unit of, TomTom. Autonomous driving. It is happening. Yeah? The societal benefits are so big the investments are so big, so huge, it is happening. Yeah. The safety advantages are, enormous, right, that's every day, 3000 people dying across the world and a multitude of that are getting injured because of vehicle accidents. It gives us comfort, right? If we have truly autonomous vehicles, we can actually, look at our smartphone We can, work in a car. We can sleep. So it gives us back time that, that we're losing out on now. In our commute or, or on on holiday, right? Wouldn't it be great if you sort of step into your vehicle, you drive into the highway, you press the, you press activate, function, you drive to the south of France, and you turn around your chair and, play games with your kids. So that's the comfort part. The and the efficiency part, it'll change our cities it will, get to better fuel, lower fuel consumption, all of that stuff. So it's happening. What do you need for it? Well, you need 4 things, to make it happen. First one is mapping. No surprise there. It's a very important element and the higher the automation level, the more important maps become. You also need sensing, so you need sensors like cameras and you need laser scanners or lidars and you need radar, to see what is around you and compare that to the map. You need driving policy. Meaning software that takes the decisions to go left or right or, to overtake And you need actuators that actually, replace your foot and your hands, right, on the gas pedal, on the brake, and the steering wheel. I'll go a little bit deeper into mapping, but I'll first let Eric Cooling from Zenuity talk about all the other stuff that it takes to, make this happen. So, please Thank you, William, and a very good afternoon. I'm Eric, and I work at And as William said, cell information is a true Can I take this one? Yes. Okay. I can confirm that autonomous driving self driving car is a truly transformative technology because it will change the way you operate a car, the way you own or maybe not own a car, it will affect the road transportation system as we know it. Because and it's that's a good thing because as William said, the road transportation system, as we know, it is not efficient. And it is very dangerous. A lot of people get killed in road traffic, and we believe that's unacceptable. And because this is such a transformative technology, our company has been founded, a little bit more than 2 years ago. We were created by the safety leaders of the automotive industry that is Volvo Cars, in Autoliv as a big tier 1. 2 years ago, these two companies realized that self driving and advanced ADAS systems is a crucial part to remain safety leaders in the future. And developing this technology not only requires different working methods, but also completely new business models. The automotive industry is very much organized around bending metal and all the timelines that it has for bending metal. This technology is much more software intensive, much more data intensive And that's why we decided to carve out the development of active safety software and self driving car software from Volvo cars and from Autoliv. And built a new joint venture around it, a pure software developer focusing on this type of technology. I can say that Autoliv has since then spin off their electronics business into a VUNAR. And today, VUNAR is 50% owner of Zenuity and Volvo Cars is 50 percent owner of Zenuity. And what we do is software development for, sensing driving policy vehicle control. And we partner, with TomTom when it comes to mapping. We already had the workshops before Zenuity even formally was founded We were sitting together to understand how can we build together, build a complete stack for vehicle automation. And we're working on that, full speed ahead since, 2 years ago. But the way to do, we do that is, in a I mean, we have made choices in how we want to develop this technology because when you talk about a self driving car, it can mean a lot of different things. Some people may think of, self driving trucks or robo taxis where there's not a steering wheel at all. While we focus on automation for, let's say, privately used vehicles that is vehicles that still have a steering wheel. They just sometimes drive manually, but sometimes drive autonomously. And we believe that that is, a very attractive way to enter the era of self driving cars. Because ADAS is happening in almost all vehicles. I mean, NCAP is requiring that for all vehicles to get a good rating And we see also see from the OEMs that, a new vehicle just has to have, at least the camera and ideally more than that. And by step forward and deal with our uncertainty around, creating revenues, around self driving cars as opposed to doing robo taxi vehicles where you don't create any revenue until you completely solve the automation problem, which is very challenging. We instead do this hand in hand with ADAS such that we can build a business over time. Before I joined Zenuity, I had been working at Volvo Chorus, 18 years in the field of active safety, pioneering in the early days. Adaptive cruise controls, automatic insured emergency braking systems, pedestrian detection systems, and things like that. And during those is we we actually were never allowed to use a map, because an ADAS system is being offered independently of an from the navigation system to the end customer. We could not get the guarantee that there would always be a map in the vehicle. Fortunately, that time has passed. We see that you cannot build a premium ADAS system without having a map in the vehicle. And we also see that if you really want to have a leading ADAS system, the coming years, you almost you need to have an HD map in the vehicle as well. And on the screen, I tried to depict what we believe, we need to develop in the coming years, to move forward. We will, at the end of this year, early next year, launch next generation of active safety systems, at the post of 2 vehicle, new collision avoidance features, level 2 vehicle automation systems. During next year and year afterwards, we will do, hands off level 2 automation, where we also use a HD Map. Then moving forward in 2022, we will start to do with unsuper we will start with unsupervised automation. So that will for us be the 1st products where we can say to a driver, now you can do something else behind the steering wheel. That's a very big task. It's very challenging, but that is what we will do. And then moving forward, we believe that automation for us will go I mean, it will start somewhere in a limited so called operational design domain, for us, it will be traffic traffic jam driving towards having driving. And then over time, we will address other use cases that are important for the end user of a property owned vehicle. So typically parking is one of those scenarios that we will target. So we will do ADAS and AD hand in hand, and we will move forward like that. Building these times, the systems are set is very challenging. And probably challenge number 1 is safety. This technology has the potential to to get us to vision 0, no road fatalities at all. But we also realized that we can introduce new risks into the system by introducing these type of technologies. It is automation can go wrong. Computers can crash. Sensors can get locks. Matt may be wrong. All these kind of aspects we have to deal with moving forward. And that is what we do. And building these systems, in order to do that consist of, well, a few layers, and I can use the layers that that William mentioned, The first one of that is sensing. We have to understand what is happening around the car continuously. An important part of that is the cameras, the radars, and the lidars that we use using. Do you see, some results of the 360 degree camera system that we do, where in each detection, in each frame, we detect, in this case, other dynamic road users. In a similar way, we do detections of lane markets, free space, barriers, science, and a lot of other stuff. And this gives us frame by frame a lot of information on what's happening around the car. We can build in a little bit of short term memory as well by tracking these OBX over time in between frames, but this doesn't give us long term memory. I mean, the car doesn't know that it has been there before. The only way to get long term memory into the car is to actually use maps. So sensing and getting the perception environment is really important, but we also want to know where are we in a map? And, we have to know that for a couple of different reasons, there's the obvious ones like, when you do an automated vehicle, it has to take their the correct route, right? So you have to be in the right lane. So that kind of planning we take from a map, we also do some operational planning based on a map, when we know, things like curvature, we can adjust the speed and we can adjust the steering so that you can do smooth driving. But also other things, which are actually very safety critical, like localizing yourself in a map to only activate the automated driving system when you are at the right location is very important. As I said, one of the first applications that we work on is highway pilots, highway automation. Thereby, the driver can do something else behind the steering wheel. But we have to be really sure that we actually are on a highway when we activate that and not on a road that is parallel to that highway. So determining that you are within your operational design domain is a very critical thing. And that is an information where we use the sensors of the car in combination with the map. We're con constantly comparing what the map data says with what our sensor data says and if we have very high confidence that they say the same thing, we allow the system to be activated. If we're uncertain, we decide to not activate it. There you can see that also in those kind of safety critical events, the marketplace is a very important role. Since as I said, since the well, even before the start of Zenuity, we started to work with TomTom, as an R and D level to do, let's say, mutual learning, doing this kind of vehicle localization, knowing exactly where you are in the map in which lane you are, what's in front of you, what kind of curvatures is there buried to the left? Is there buried to the right? That's a new technology, and we're still in relatively early days. But together, we've been exploring these kinds of models. What is it that the sensor actually can see? How can you represent this in a map? How can you maintain the freshness of the map over time? Those are things that we've been working on together since the last 2 years, and we're making really good progress in that. But also probe sourcing is a very important area. And probe sourcing is the technique where you use vehicle sensors to detect for example, landmarks or landmarks or signs or something else, where the car detect them, you send them to the cloud, you, you, you, you compile that into the map and then you can send almost like a real time map back to the vehicle. And this is a technique that I believe is going to be super important in the coming years. We have built early prototypes together with Tom, Tom, where we use Zenuity vehicles, with Zenuity camera that detects traffic signs, we detect that. We, we kind of compressed the data, send a small package to the cloud. And from the Zenuity cloud, we sent a rotogram, to Tom Tom, who then integrates this into a map and can update the map with a traffic sign that we detected, but it was never seen before. And this kind of mechanisms will be built into the fleet, of course, the coming years, allowing you to have real time maps available for highway automation and for ADAS systems. And for ADAS, this is important because it can really improve the performance of the ADAS systems, but for vehicle automation, this is important because it will improve the availability of vehicle automation. As I said, we can only automate when map and perceived reality corresponds. So these two are key areas that we have been exploring that we will explore and we will learn together moving forward. And those are key techniques both to make driving safer and putting ADAS technology in more and more vehicles, but it's also a that is going to be crucial to enter the area of self driving vehicles. Thank you very much, Eric, that that really helps in, understanding the wider picture. So if we now dive a little bit deeper on, on maps, which maps do we make for, autonomous driving? Well, they've been mentioned today, we make the ADAS map and the HD map, and I've plotted them here against the six levels of automation, right, level 0, through to level 5, where level 0 is that a human controls everything in the car, but it can get warnings from sensors and maps like you are driving over the speed limit, to level 5 where you can tell by the, by the symbol, where you don't need a steering wheel, where you don't need a gas, or brake pedal. It's all gone. That's still a little while away. We're now in mass production at level 2, a Tesla autopilot is an example, as is the, the Volvo system they can all keep lane and adjust speed. So they do, in technical terms, lateral and longitudinal control. So that's the level 2 Level 1 is typically an adaptive cruise control, where you still have to hold the steering wheel. So, our ADAS map is used for the lower levels of automation, level 012, and our HD map is used for level 2345 and you see that there was an overlap, in level 2, because we actually see both. We've sold both. We have level 2 systems on the road with an ADAS map, We have, level 2 systems coming up with an HD map, in production vehicles. To explain the difference very briefly. So in ADAS map, it has been mentioned many times, presentation, and ADIS map is a road level map. So, if you have a 5 lane highway, it's seen as one road. It will say it will have a lane count. It will have one speed limit. It will have one curvature, one gradient or slope. Whereas an HD map is a centimeter level accurate lane level map. So, actually, you know, everything for each lane. If there is an exit lane, then that exit lane has can have a separate speed limit like in in Germany that happens. So it's a road level map for us as in centimeter level lane level map. So what's the role of maps? There are 3, roles that, that maps play in the car. 1 is perception, which is shown here, and I'll, like, explain the picture, one is localization, and one is path planning. Help a car understand the environment around it. Well, here's one example. Let's say this is a picture from a, front facing camera in a car car, and the car now has to decide, am I allowed to drive or not? It sees this bunch of red lights And it has to make up its mind, right? How do you interpret this picture? Well, a car a map will help the car, determine this. It'll tell you in which lane are you today, are you now, If you're in that lane, then it's that traffic light that applies. So it can tell the camera actually, look at that set of pixels because that's where you're gonna find the traffic light that you need to read and that applies to your particular position. So it'll tell you, actually, it is okay to drive, right? It finds the green, traffic lights. Localization is the second, element, the second function of an HD map in a vehicle. So localization is needed because GPS, which is traditionally used to put yourself in a map is not precise enough. It's not good enough. You need more. So we add special localization attributes to the map, things that a camera can see or that a light arc can see or that a radar can see, we add that to the map, and that can be compared to sensor readings. And if you then, do the math, you can find out in which lane you are. Which is kind of important. And once you know in which lane you are, you can also determine in which lanes the other vehicles are. That is not always trivial to determine, but quite important for decisions, right, if you're driving much faster than the vehicle next to you, like what would happen in Germany and you're entering a curve, then it's quite hard see whether the car ahead of you is in your lane or not. But with a map, you can get a much greater certainty that you're actually you can continue speeding and you can safely pass the vehicle that is driving slower. That's an example. The third element where an HD map comes in is path planning. Eric already mentioned some examples A simple example is if you're on a 5 lane highway or a 4 lane highway here, and it's it's, you know, it's a lot of traffic, that you want to know kilometers ahead, actually, that you need to start merging into, the lanes to the right. Yeah. And that's where an HD map, can help you do that type of path planning, right? It plots all the vehicles, or the system can plot all the vehicles around you on that map, and it can see very far ahead much further than the cameras can because it knows in 2 kilometers, you need to, be on the exit lane. So, that was how a map was used in a vehicle. Yeah. About autonomous driving and, and the pillars of autonomous driving and then the role of HD maps. So how do we make those maps? Just, you know, very briefly, we, we mastered this because as as you, have heard Alain say, we can build on, a very long experience and a very wide experience as well, right? We we master all the technologies that are needed. So what does it take? It takes, centimeter level accuracy. It takes ultimately millions of sources. So sources can be our own survey vehicles or Moma vehicles, mobile mapping vehicles, as Alan was calling them, they can be Zenuity cameras, can be other cameras in the end that will add up to millions of sources that are all differently calibrated and, you know, are made by different, vendors and create different types of data. So, millions of sources, and we have to do that in real time. As fast as possible because the faster we can reflect changes in reality back in the car, in the map, the safer the whole experience will be and the better the user experience will be in the end. Now, so if we go into a couple of examples on each of in an example for each of these, So first this so this is a this is not a map. This is somewhere halfway through our production process, right? So we, we get a bunch of raw sensor data in. Then somewhat halfway, we're here, and then we try to abstract this in, we abstract this into a map. Now, why is this special? If you look at this, you can see that you cannot get this from OneDrive. You cannot send out a survey vehicle or any car and drive this in one go and have it all sort of, fit. It takes many drives to do this. You can also see that there are no shadows in this. And if you have many drives, you need to combine them, right? And, that needs to be at centimeter level accuracy. You can't have 2 Lambda polls right next to each other where, in reality, there's only one. You can't have 2 traffic signs and all of that. So that's what we're able to do at scale. And this is really, leading edge state of the art application of technologies. This has been done scientifically on small areas, but never at the scale of the world. And we're doing it at the scale of the world. Yeah. Centimeter level accuracy. Then, there's millions of sources. Here's one example in the top Top left. Yeah, it's left for you guys as well. Top left, you see a video image. From a car driving, in this particular case, it is in Japan, in the area where the Olympics will be held, Odaiba, And, so, you see car driving there with a camera, and it is registering information. Much like, Eric was also describing, it is registering road edges in purple is registering solid lines and dash lines that are on the drivable surface, in pink. And then below that video, you see how that is stored all the time, and that creates a rotogram. Yeah? That information, if you combine it all together, essentially creates a rotogram, and that's what we do with multiple, partners, including Zenuity to make that to close that loop and get information about what's changing, as quickly as possible, millions of sources And then finally, there's, the real time element of it. One part of being real time is that you actually need to be able to stream maps to the vehicle, and that's what we do with auto stream. It's like a Netflix or a Spotify, but then safe for map for autonomous vehicles. So, here's what it does. We're planning a route. This all happens on the navigation map. We're planning a route from Las Vegas to San Francisco. And that route is planned and is handed over to the autonomous driving system. And this is sort of takes you through the configuration. Yeah. A driver in a car would not do this, but is how you would configure what data is then streamed, because bandwidth is a, is a concern. So we want, obviously, we want the road elements, we want, traffic signs for localization. We call our localization products road DNA. So the traffic signs, we're gonna put in row DNA signs so that they can be compared with the camera and, and we can localize. We are gonna put speed restrictions in. Because we wanna know that we're not, autonomously driving over the speed limit. We're gonna put another localization attribute, and that works particularly well with radar, which we call row DNA roadside, which is that sort of Minecraft blocks next to the side of the road. And we're gonna put in Jamtail warnings, live data, plus explicit curvature and gradient. And HD map is so precise that you can calculate any curvature you want but sometimes OEMs want that to be explicit so that they don't have to calculate it in the vehicle. Now, now we're going to start and download only the relevant tiles that we need. So these are all the tiles between Las Vegas and San Francisco. And because the system is very smart and keeps a persistent cash, we can actually look for differences and only download where there have been changes. Again to save, bandwidth and to gain speed. The faster, the less you have to download faster, you can actually start driving, which is happening here. So we've developed this, it's called auto stream. When we started, people said that's not possible, right? An HD map is much bigger than a navigation map and, how on earth can you stream that? And we can't be dependent for safety critical function on a cellular connection, but we managed to address all those, all of those problems and, and created auto stream, which is, going to be in a production vehicle, next year. So that's auto stream. So that's the, centimeter level accuracy millions of sources, in real time. So then we move To the final bit, I promised, which was euro numbers, how big is this market, yeah? What, what I'm showing here is, multiple opportunities. So we see you see private vehicle automation. That's the level 23 and a little bit of level 4 in the future. For private vehicles, Yeah? So vehicles that all of all of us would buy, then does Robo taxi or shared vehicle information, different market, different business models, partially different technologies, but very similar maps. And, there's one example of other. There's actually a larger category called other, but this is one example, asset management for government, right? If you have all this very detailed data, you can actually also add, and find things like lantern poles, in the map. You can find electricity cabinets, all that stuff. That is of interest for municipalities and other governments. Then you see 2020, 2025, 2030, we look at private vehicle automation, in our own market model, we, see that the market in 2020 is roughly 1000000000, right? This is a, what the model gives us. I'll explain a bit about that in a minute. 2025 by 2025 that has grown to 0.8 1,000,000,000. And by 2030, it has grown to 3,000,000,000. So there's an enormous, growth in, in a private vehicle automation market. If we look at robot taxis, we think it looks like this. Yeah, similar size, $100,000,000 in 20.20 in 2025, not yet very big. 300,000,000, a lot smaller than, private vehicle automation. And then it'll go in 2030 when all of those difficult technology nuts have been cracked and there has been time for scaling, it'll be around 5,000,000,000. Government, asset management, smaller markets, few 100,000,000. Now, everything we do, and it's important to understand, and everything we project is only based on private vehicle automation. Yeah? That's what we focus on. That's the business where we are leading that where we want to win, and that's what's driving all of our decisions. Robo taxis will come. But it's upside in all of our projections. So we go a little bit deeper into private vehicle automation, then, this is part of our market model. So let me explain this to you. You see Horizontally the Years, on the left axis, you see tens of 1,000,000, so 20,000,000, 40,000,000 cars, that have a particular, function. And on the right hand side, you see percentages with attach rates. So how many of these cars will have, an ADAS map or an HD map? Those are the two lines And then the colors in the graph, light blue, medium blue, and dark blue are, level 01, combined Level 23 combined Level 45 combined. And what you see is that there's already on the road next year more than 60,000,000 vehicles with level 0 and 1 functions, but they often often they don't use a, a map, right? The attach rate of maps is around, 20% of ADAS map. As we see higher and higher automation coming in at a level 2, 3 functions, we see also the attach rates of maps growing with AT map growing faster than, than the ADAS map. And, ultimately, 2030, we expect to see, or actually the analysts that we've based this model on, expect to see, level 4 or 5 private vehicles again, So these are not the robo taxis, being meaningful as well. Being a meaningful percentage of the total amount of vehicles. And you basically also see that we're nearly all vehicles will have some form of automation, yes, because, we sell in the world about 100,000,000 cars a year. That will grow a bit. But, so that has gone in to, those market estimates that we've, that I just gave, right? The 800,000,000 in 2025 for private vehicles is based on this on these take rates and these volumes. Now what does that mean if we split it out? This is the ADAS map market. So, you see, again, the same time scale. You see the total market value And you see, that by, 2030, this is, around 500,000,000. So we see all the way on the right hand side. Not all of that is addressable. Part of it is in China, which we can't address, and that's the dark red part. We do this and this grows about 20% per year we expect in ADAS map market value. If we do the same for HD map, it looks like this. Yeah? We actually see it starting from a small base. We see a 60% growth over the next decade, 60% CAGR over the next decade, with a very large part, nearly 2,000,000,000 by 2030 addressable for us. Yeah. So, this is what we, work for every day, and and, and this is what we try to capture as much of as possible. So where do we stand today? The numbers have been, been mentioned before today. If you look, What got us here, it's our competitive advantage. We have, experience with dealing with automotive customers, customer experience, customer intimacy, through our automotive Salesforce, everything that Antoine is doing through our cumulative domain knowledge, our global presence, right? We are everywhere. In both in mapmaking as well as in, in sales. And if we're not there, we travel. Our independence, the Switzerland of Maps, as Harold said in his introduction. That's one element of our competitive advantage in this space, Then we have leading technology. A lot has been said about that as well. Our transactional map making applies equally well to our ADAS map and our HD map. That's delivering the shortest cycle times. And, we build up a lot of technology over the years in artificial intelligence computer vision and what have you, right? That's also, all in all, giving us a leading technology position. And finally, we have a very complete the most complete product portfolio in this space. You've seen case talk about integration with navigation. We have, the SD map, you need an SD map to be able to make an ADAS map. Right? An ADAS map is a road level map, and we attach attributes to that. You need an SNE map. If you don't have that, you can't play. We have all those stream. I mentioned that. We have services. They have been mentioned, and we actually can help to integrate those all of those products into the vehicle, right, by working with partners, where we do pre integration, We have our own integration services. So all this together gives us a very strong, competitive position. Nobody has the same set, so we are better than here in many of these things, and we're better than Google in many of these things. And that is translating into market share, right? More than 1,000,000 vehicles, level 12, mostly level 2, actually, on the road today as we speak, powered by our ADAS map. And we're learning from that every day. Those, we get feedback from the, from the OEMs, they tell us what they like about the map and, and, and on what they would like to be improved, and we work with that, and we, and we bring that in. In HD Map, we're the current leader with a market share leader, the market leader also in technology. This is expressed as a market share, of 60% out of all rewarded deals, sort of between call it a year ago, 18 months ago, and 2 years from now, every single OEM will have made their HD map selection decision, at the point in time where we are now, we've we are at 60% market share based on awarded deals. That doesn't come out of nothing. It comes out of out of our competitive advantage that I just described. And out of working with all of these OEMs, for a long time. Eric also mentioned how long we've already been working with Zenuity, even before Zenuity existed. We've been working with, 4 out of the top 5 global OEMs when they were developing their test vehicles and their R and D vehicles, right? We gave them map samples. That has translated for some of them into wins. We're the only company with a self driving stack the cars outside, right? We test our own, map. We eat our own dog food as they like to say on the West Coast. And we were we have many firsts in, in HD mapping. We were the first to file patents in 2009, the first to provide samples in 2013, the first to provide a country in 2015 and the first to cover the highways of the world at least where those vehicles will drive in 2017. Yeah? So with that, I would like to thank you for your attention. And I think there's time for questions now. Quick question, of course, on the, on your market expectation for the next few years, especially in automotive. I wanted to ask you maybe on 21st. On in the next few years, excluding ADAS. How do you see the content per car? Evolving, meaning, like, do you see, any kind of pressure on pricing? I you have a lot of services more and more at a treat like you described EV, but is it something that can, you know, you can increase basically the value you get per contract, or is it just too off set, basically, underlying decline of the price. So it's first question. Well, so price pressure is not new, right? So that, that, continues. I think it's a bit of both. So if you look at, you know, what has happened in, in, navigation maps, so far. Yes, you're right. Basically, you know, integrating more, content or more coverage compensates for the, the the annual price decrease. I think if you look at what we're doing now, including, you know, increasing the size of the, the services package, it's it's more than that. So there's there's added value on top of, what we currently discuss. Okay. Great. On the HD map, I want has the same question because separate, it looks like the OEMs are facing a lot of, you know, challenges, to some extent, with electrification of car with ADAS, and you see the bill of materials increasing everywhere, basically, almost. So I was just wondering, given the HD Map cost, possibly, we are talking about, an increase of content significance. That's how you are publicly, what you are publically saying, do you think for penetration to increase materially, like you are describing, you will need to decrease the the speed of materials as well materially. So my question in your market assumptions, do you expect you know, the value to come down, the ISP to come down for the penetration to go up. In the market model that's behind these numbers, there is a price decline at similar features, assumed. Yes. Absolutely. Because that's indeed, as Antoine is saying, that's the nature or there is price pressure in the, automotive industry. As features increase, of course, we hope to compensate some of that price decline. And I'd also like to say a word about what you said about, is it expensive? Yes, elect vacation and ADAS and all of that, it's expensive. But the part of maps is not necessarily, the biggest expense Right? You're gonna put sensors of, of $100, $200, several of them, right? You're gonna put in a vehicle. The cost of a map, which is, which scales much better than a sensor, right, which is hardware. Is not, in the whole system, is not a, an enormous amount, an enormous percentage in the whole ADAS or, autonomous driving system. And last one for me is if we are looking at your forecasts, for 800,000,000 value by 2025 for HD Map. So if we look at your market share, both I mean, 60% that you're mentioning. Let's take 50%. So like 400,000,000 potential revenues from HD Map, we can back within 5 years, basically, also. Is it the right way to look at it? Your your calculation is Yeah. So revenues were not talking about orders intake. It's just revenues. Revenues not order intake. Are talking about? No. It it was, that model is based on, revenues. And you get subscription reference, right? It's different. It's more like a traffic service where you get annual income from a, from the map. And I'm not going to comment on what IFRS will do to all of that, but, I'm sure it will do something. Thank you. Can you maybe give a bit of an update of all the the partnerships, in the past, you, you have announced partnerships with NVDF, for example, or with with Boish on, on this level, or even with VW, How does it look today? Who's really driving this autonomous driving trend? And how do you partner with them? What's the status there? Stasis of all the partnerships. Yes. So we've made a lot of announcements on, on partnerships. And, the key thing is that you want to pre integrate basically with, especially if it's other automotive suppliers, you pre integrate as annuity is a great example where we work through all of the challenges that you face when you start to collect data from a vehicle. Volvo is not necessarily needed for that, right? And by the time, Volvo as a potential customer, would come into the picture, we can say together, right, this, this part of the puzzle has been solved, and it will make your vehicle safer. How all these partners progressing some more rapid than others, right? I visit most of them, and we, try to continue on that path of mutual learning, right, and, and do that pre integration. For example, the NVIDIA partnership, for a while, it was a lot of noise, a lot of, noise coming from NVIDIA work on autonomous vehicles. It's a little bit more quiet now on that front. Is it or is that just perception from us from the outside? But internally, you're working a lot on a lot of products with them. I'd say, in general, this is not Thompson, Tom, Tom, specific. If you would look at the amount of press releases that were done, you would see sort of a peak in, in 2018, and now everybody is sort of hitting reality. Cars have to hit the road. Business is 1. Let's get our heads down and, and deliver, right, and learn from that. So, I think it's correct that you're hearing less, but a lot of work is still being done behind the screens to realize all the promises that we made in those press releases. Okay. Then final second question is more on, the revenue model. The the way you talk about it and probably it will have a connected car time and continues to update. It really feels more like a software as a service kind of product, which should have like monthly or yearly subscription based on the uses. But how I'm correct that the industry is that the OEMs are not looking at from that side. They're looking more from, from a license, for the licensed products? Or is that changing, or do you see that moving towards that, that's more like SaaS products? Well, it's, it's been an ongoing discussion for already with the, the connected services. Right? So connected services have not always been on a, like, just one license and, and So, and, and the more we move, just as you mentioned, right, the more we move towards navigation as a service altogether, the more we deliver, regularly, or continuous map updates, even more when we come to software updates, it is going to be a, navigation as service model, and therefore, more a, a subscription model than, just a one time license fee. And those discussions are, are taking place. There is, it's a change, right? But there is, I wouldn't say there's a strong resistance from OEMs to move towards that, that direction is a change. Yeah. You, you call yourself the chef with the recipe in one of your slides. To what extent are the OEMs allowing you to be that, that party? And why wouldn't they want to do that? I think across the board, we see, very spread level maturity at OEMs, with regard to, developing, that user experience, right? It's, it's difficult. To do software design in the car, and it's, it's very different from how, for example, design organizations at car companies work. They, I think, across the board, they still spent most of the time on the Brent and identity of the car, of the interior, of the, the, the hardware, user experience of the car, and software is for them almost alien for some, right? So for the less, the less developed OEMs. If you look at your high level quality premium, companies, it's different. They have a very good understanding of what they want, and they are more likely to be customer of our ingredients. So components that we deliver, like maps or services or, or online rooting and search, for example, but there's also a large class of potential OEMs that would love to have a solution delivered to them on a silver plate that they can customize, to their liking and to their needs. And have all the hassle, I would say, around software updating, software management, having a integrated experience left to, left to a potential third party. So, yeah, we definitely believe there's opportunity there in that space. Let me follow on. Is that exactly what's Google providing to these guys? Like, one stop shop and and they provide everything? Yeah. I cut it's it's difficult to understand really what, what Google is doing, but it seems from if we learn from the past, it seems example, customization options are very limited. Like, it's very much this is our solution take it or leave it. That's what we've seen in the mobile space, right? If you buy an HCC phone, or an Huawei phone or, or any other Android phone, it's a Google experience, and it's not an HCC experience. And I think that is something that the OEMs are really trying to avoid want to create an experience that is a brand experience for their customers. So you need a certain level of customization of that, that software you experience that is fitting those brand needs. So there is opportunity next to, kind of a Google only solution. Okay. So can you provide all that? Is that sort of catered for the current R and D budgets that you'll be able to connect all these these apps within the car to each other and and make your own, well, you provide the recipe for the, the OEMs, or is that not the right way to look at it? That's a case by case basis, right? So one of Google's strong points is, for example, having an app store. So in theory, any application builder can create an experience in in the car. But we also know what people do in the car is, is a very limited set of use case. And it's very different from how you're using, for example, your phone in many other contexts. So when people are driving and they pay attention to the to the road. So it's different when once you're in an automated driving use case, people just flip over their laptop or take their tablet and do whatever they want. But as long as you're in a driving, situation where you need to, require attendance. What people tend to do in the car to make best use of their time is to communicate, to listen to entertainment, and to find their way, right, to to navigate and especially communication, whether it's making calls or conference calls or getting ready for your day at work. Those are the typical kind of communication product productivity use cases. And the other class is just listening to the music I want to listen to in a car of that radio channel that I'm used to listen to or continue to listening what I was doing, listening on my phone when I jump into the car. And that set of use cases rather limited, right? It's not you don't need to boil the ocean in order to make those use cases actually work in the car. It's by it's providing to a couple of key services, having a great interactivity with your phone so that your is a fantastic remote control, to whatever is, running or playing on your phone, like nailing a few of those critical use case is essential, but having a enormous, like, a 1000 app app store to to watch the news in the car or to look at your stock ticker, we don't believe that is a requirement in order to deliver a satisfactory, delightful use experience for what people actually expect to do in the car. It's a bit a bit back to that iPhone use case, right? Like the first iPhone did a lot less than what an Nokia phone did at the time, a lot less. But the the things it did well, it did totally frictionless. And, brought user delight and brought user satisfaction. And I think there is also that opportunity in the car. This is not about enabling each and every use case, but this is about doing a couple of use cases really, really well in a delightful, use experience. And that's kind of what we're, what we're aiming at. Mark. Go ahead. Mark Hutchberg, ING. The the $3,000,000,000 you mentioned as a sort of potential revenue pool in 2025, And also with the GAGR of 60%, 20%. How does that fit in with the, the GAGR, the Taco gave in his presentation? Towards 2030, and the water book that is attached to that. How, how does the, how do these numbers ling in with each other, or should I see this separately from that one, or is it part of the order book that we should see, say, 10 years from now. How does that interlink? Well, obviously, what we're doing in ADAS and HD is going to be part of the ambition that, Taco stated for, 2030. Given that the growth rates are much higher and the potential by big, 15 versus 60%. How does that The growth rate of HD comes from a very small base. So it's a bit misleading to use that 60% CAGR and compare that to the 15%, which is from a much larger base, which is our current revenue. What would you expect then to be the proportion of HD to be in that, that number by then? Is that possible to could get. That's a bit difficult. Let's not go into that detail anymore. Okay. Okay. It, then maybe over 2 to, Zenuity, because you probably were there when the decision was taken from full of how to make a u-turn, and turn to Google. Can you explain perhaps what that level of risk and what's behind it? And then maybe follow-up, a few years down the road, can we expect another U-turn? I think still going in the right direction, or would it actually be? More tone tone in the future. Anything you could comment on that? I was there, but I cannot comment, as I look, of all employee anymore. What's the new what's the new the limit as as Dylan was hinting, we're very, I mean, where's the active safety self driving car as software supplier to mobile cars? We're working intensively on that stack together with TomTom, but the actual sourcing decision to source a Tom Tom or to something else or somebody else. That's that's a global course decision, and I cannot comment on that. Bye bye. As you would have expected. Of course. Thank you. Bim Kiela from ABN. You mentioned during the presentation that so far you've won about 6 percent of all the HD Map awards, who's been in the other 40%, is that just here, or are there also other parties involved in that 40%. Maybe also a bit on, always had a bit of a bumpy ride in terms of, order intake because, the level of RFPs is not the same level every year. It's very difficult, for the outside community to see what the level of RFPs is. So can you give us a bit of glimpse into the future in terms of what the level of RFPs has been in 2019 versus 2018. And also maybe moving towards 'twenty and 'twenty one, is that number going up or, or, should we expect more soft pay is there as an industry, as a whole. Also a question for Zenuity. The, choice has been made to work very extensively with, with TomTom. What was the reason, the final reason to work with TomTom and is TomTom your only partner, your exclusive partner, and what kind of were the, the key ticket box, that makes you choose TomTom for such an important, partnership. Let me first answer the first two questions. On the, market share that William provided, that's a volume based market share. So it's not that there were, 5 awards, and we won 3 of them, and that makes, 60%. But based on the car volumes, we, we've won 60%. On the RFQs, we see similar trend as we've seen last year, 2018. So, it isn't that big as it was in, 20,021,017. But with introducing the automotive order or the backlog, we think it's also more fair, KPI to see future revenue. We continuously see reassessment of already re, running deals and extension of running deals, etcetera. That you can't report in the, order intake, but you can report it in the backlog. So the best future indicator of success for, automotive is the backlog and no longer the order intake. And for the last question, You want to take it? Yeah. Oh, yeah. You first, sir? No. You got it. Okay. I can answer. And then while we decide to work with TomTom, already in the early days, Most of it, it's a willing to explore, developing HD Map that fit localization, the fit safety critical aid, our safety critical automotive driving is a journey, and we didn't have all the answers beginning. Tom, Tom, had a well, had willingness to explore, and had HD Maps available can do really fast map making, map making, so that if we do the probe sourcing mechanisms, detect new features, send it to the cloud, update the map, this entire machinery. And there, we felt that Tom, Tom, Russia, right partner for us, and we still think that. Is it the only map maker we're working with? No. But it's the only map maker where we really explore the new grounds and where we do the the core development with. Very good. We can't comment on who's winning the other 40% of the volume in HD mapmaking. Is it just here or

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