CMD 2018

Jun 13, 2018

Slides

Good afternoon, everyone, and we're going to change shift. We're going to talk strategy and finance. But I told one of the participants here earlier today that I've finally figured out why it's 52 degrees in this hotel. Do you know why? Anyone? Keeps you awake, right. And since we're this is the Capital Markets Day, we need be a bit capitalistic. What do you do when you're awake? You spend money. So gambling goes up as the temperature drops. I found that quite interesting. So this is the agenda for this session called the Capital Market session. We're going to discuss our strategy. We talked about it yesterday, and you've seen the keynotes from the divisions. We're going to have Claudio elaborate on technology, and then we're going to have a short break, which is needed after a technology elaboration. And then we're going to talk M and A, finance update, and then there is a summary in Q and A. So let's dive into it. We've worked hard on our mission and vision, and our vision is to we aspire to be the leader in creating autonomous connected ecosystems. And yesterday, we introduced to you what autonomous connected ecosystems are. You can say, is it corporate bullshit? No, it's not. But it's the way we classify the future. People talk IoT. And what you heard in the keynote today is IoT is just an enabler. You can't be an IoT company. It's like I'm it's just a facilitator of doing the things we want to achieve, which is making stuff autonomous. And we believe our mission should be to deliver these digital solutions to improve productivity and quality. And here we go. IoT in itself is not a target, but to deliver quality and productivity, I. E, cost reduction and efficiency, that is never going to go out of sight. So yesterday, in my keynote, I showed you the data dilemma, we could call it that, the fact that we produce more and more data and we generate data. And with IoT, we have machines spitting out data 20 fourseven. And what do we do with this data? Are we getting any collaborator? And the answer is, unfortunately, no. So we use more data in our everyday activities, but we don't use enough data. We're not clever enough, and our systems aren't clever enough to take this new leap into the digital world. So we've talked about the accelerator, the way we can keep up or catch up with the data generation possibilities that we have today. And that accelerator is a combination of a subset of technologies that we have developed over the past 7 years. So, we haven't really talked about what we're doing behind the scenes. But behind the scenes, Hexagon has built a comprehensive integration and communications module, which means that we can tap into any legacy software. We could drill into your SAP system, your salesforce.com system or whatever system it is you want to use, You don't direct a computer towards a problem. Artificial intelligence is useless, and that's why you need the verticals to address. So, when you hear companies saying we're an AI company, that's rubbish too. Then you need cloud orchestration, and Claudio is going to speak more to that as well. And edge computing, we saw that in keynote, where more and more of our instruments and hardware are becoming clever. So once you have this and once you master this in your own industry, you can create autonomous connected ecosystems where machines communicate with machines. And yesterday, we introduced this. It's a wraparound. This is not a product. It's not even a platform. It's a subset of technologies that enable you to reach autonomous connected ecosystems. And the way we operate Hexagon today is we have the innovation hub represented by Claudio, and then we have the divisions that have applied capabilities directed towards a problem in a certain industry. And then we've identified a set of autonomous connected ecosystems, which is our strategic mission to reach within the next 4 years. So we want to see products in these ACEs. We want to see products in mines, construction sites and plants, factories, cities and fleets. And another thing that's important to understand is how do we as a company, create this? Well, we have 6 divisions, and they all have their own specialties. But if we move if we so hone into, let's say, smart factories, manufacturing intelligence itself cannot deliver smart factories. We're actually building on the platform that PPNM has developed. And we need geospatial technologies like LUSIA to do it, and we need geosystems technologies to deliver it as well. And we can take another example like smart construction sites and plants. That is not a Geosystems or PPNM project either. We need to draw the technologies from geospatial and manufacturing intelligence to deliver this autonomous connected ecosystem. So it's all entrenched. It's all ingrained, and it all fits together very nicely. And for those of you who have visited Hexagon Live over the years, you see it gradually coming together. But this is the power of Hexagon. Hxagon. There is no other company out there that can deliver this. They can deliver subsets, but they cannot deliver the complete solution. So if we look at autonomous fleets, what is an autonomous fleet? Well, autonomous fleets are autonomous vehicles that collaborate in a system. For example, in a city where you have traffic and you have buses, you have cars, you have lorries, you have all these vehicles. And it's not only to master driving a car autonomously. You need a sort of map that all these cars agree upon. You need a standard that this is the map we read from. We need to define the traffic itself, and we need car to car communication. And what do you think an autonomous car does if it hits a red light or sees a red light, but it can't see red lights? So we need some sort of overhead that directs the traffic and tells the traffic what to do, when to yield, when to stop, when to break and so on. And that's the excitement that we see in autonomous fleets. And there is a subset and a huge potential of services that you can deliver to autonomous systems. If we move on to the construction side of things, and here we have 2 applications, it's plants and it's construction sites. And we have, for a very long time, discussed smart plants. And Matthias did a really good presentation today describing what digitalizing the plant means. It means law and order basically, bringing structure to these plants so that you can improve efficiency and reduce cost, operating cost. So, we see a scan here of an already existing plant. And the really huge potential for us is what's called brownfield, new old plants that already exist where we don't have enough data around that plant. So auto tagging that Matthias described would be what you see to in the center where it says like TrueView, if we could tag each and every component automatically. And if you click on that tag, you can retrieve the supplier when it was installed and when it's time to replace it. So this is going to bring a lot of efficiency to that industry. And if we take the AEC industry, you hear a lot about BIM. And is BIM the Holy Grail? Is BIM going to solve everything? Now BIM is just bringing CAD functionality to an And then we can issue instructions to the work site. And then we can issue instructions to the worksite, but we never hear back from the worksite. And that's the dilemma with AEC. There is no reporting back system in the entire industry. People go about doing what they're doing. If you're expected to get a tonne of cement today and you called in 10 workers to work with that cement and it doesn't arrive, you're not going to get a signal that it didn't arrive. You're going to see that in a delay report a couple of weeks later. That's the problem with this industry. It's an industry built on entrepreneurs that are independent contractors, create an ecosystem for the construction industry where you not only can present a pretty three d drawing of the building you want to build, you can follow it through the construction process and get reports back in real time. And if we move to smart factories, finally, we discussed this. And as I said in my keynote and as Norbert showed in his keynote, this is a model of an installation we've already done and that we're running in China. This is actually a live autonomous connected ecosystem. You've got a coordinate measurement machine to the right. You've got a CNC machine to the left. The coordinate measurement machine is driving the CNC machine and tells it when you're not producing quality components. You need to recalibrate. You need to change the cutting die or whatever it is. So this is autonomous because there is no human interaction, and it's obviously connected. And if you roll it out, it would be a smart connected factory. Finally, the last target area for our SmartX solutions is smart cities. Smart cities could be anything. Everyone is doing smart cities, and you can see tons of PowerPoint on smart cities. So I think we said it very well in Essai's keynote that what does it matter if you have a smart city if it isn't safe? So we need to start building on our public safety systems and our infrastructural capabilities to document the city in 3 dimensions and then overlay with activity. And we're going to work with public safety organizations to create safe cities. Then we're going to work with utility companies to create smart utilities with as little outages as possible. And then finally, we have traffic. And that's how we describe a smart city from Hexagon. And with that, my introduction is done, and I would like to welcome Claudio Simao, our CTO. Hi, everyone. Thank you, Ola. In the context of being a leader in autonomous connected systems for the industries we serve. I would like to focus this presentation not in all the spectrum, all the comprehensive portfolio of technology that Exagroon has, but in the underpinning elements that to support the concept of ACE. So this is the idea. In when we have the break or when we have the networking, If you have specific questions on other technology, we can then address that. Basically, I would like to show how transformational and I could be even disruptive can be the concept of ACE. And what is the and which are the influence or which are the power of the capabilities that we have in XLT. In this framework, it's a kind of package of foundational of key digital technologies that we interlink together in an interoperable way to support ACE. Just to contextualize, I don't want to be theoretical here, but just to because this is a fact, we can see clearly this happening technology. We know the Amara's law. I guess Matthias mentioned this today. It's about human expectation of predicting technologies, technology impact. And this implies basically that we tend to overestimate the technology in the short time, and we underestimate in the long term. And we see this clearly with IoT, and also we can see this, for example, with augmented reality. We don't see monetization. IoT today, what I see I will not refer to specific players, but what I see is automation. Industry 4.5 is industrial automation, this dynamic dashboard. Connecting A to B is considered IoT. So too much expectation, very low monetization, basically. So this is the point that I would like to bring. So Exergone is focused not in the hypes, but in creating the underlying technologies to prepare ourselves to these new trends and, let's say, benefiting of our domain expertise. As Ola mentioned, our derisioness of our domain expertise will really create many we have already identified so many use cases and which use case we can, let's say, pay more attention because it's more creating more value or it's more monetizable. So there what many people are missing? It's all about the explosive growth of data and technology, as Ulla mentioned. And this is overwhelming companies. Everybody is trying to find where I am in this game of IoT, artificial intelligence and the other digital technologies. So the gap between the technology, what technology can do and what technology is being done is ironically growing faster and faster. So this is the slide also from Ola. So my responsibility is Innovation Hub in synchrony, in sync with the division's R and D teams, supported by the applied technology, the core technology for Nexagon, let's call Technologies, to in the direction of ACE. This slide is just a reference that I use many times because this is clearly happening and also in sync what Ola mentioned. The world is getting more and more complex, right? For smart cities, how can be that dispatching of ambulance, police and fire is not synchronized, is not interlinked with garbage collection or some events that happens in the city. London is not interconnected. So one thing affect directly the other. And base elementary things are not interoperating together. So and the world is getting more complex because now we can see it. We can link A to B in the concept of IoT. The other element, the technologies are getting more and more complex, and this is not so obvious. But there are so many new technologies, stand alone, very efficient stand alone but fragmented. And the overwhelming effect on the company is trying to use isolated. Basically, what we are doing with Exalt in Directional Vase supporting underpinning Aase is a framework of capabilities that are interlinked and more than do them interlinked interoperable. That means if you change here, the other one will realize it and will adapt real time. So this is the concept of interoperable. So Exalt then is a framework of digital capabilities, as Ulla mentioned, that ties and orchestrates all these elements of all these technology and these elements. And this permits us enable us to close the gap between what technology can do and what we are doing with technology. So this is the this is a big advantage that we have. This will enable autonomous connected ecosystems and will address problems that we confront today, but mainly, I guess, as important as we prepare Hexagon for the next step because in the technology is evolving so fast that if you're not preparing yourself, you will be disrupted. A garage company will disrupt you, and then you can buy the garage company with a big multiple, for example. But this happens nowadays. So we have to prepare ourselves for this. And that is one of the causes. So Exalt encompasses capabilities like cloud, mobility, edge connectivity, edge computing, edge analytics, data compression, data preparation, vectorization, visualization, AI modules. As Ulla mentioned, too, AI is not magic. You need a fitness function to tell the direction. But when the system know the know the direction, you can create many layers of head population of the algorithm. And the computer, they what they are good is doing calculations. They do this very fast, and they go to the direction of what we want to do. So AI can be very powerful if you put this on top of domain knowledge. So this will then allow us to collect and leverage data from different types, from different morphologies in volumes enormous volumes because with edge computing, you can compute at the edge and just extract what is important. You don't need to push out the information to the cloud. So again, these are the main capabilities, not limited to this. We are for example, we are investing now in data composition. It's a very it's the next front end, it's the next wave of technology when you can compose data of different morphologies, as I said, to make sense of it. So this is the next frontier of technology. But these are the main that we are using. I would like to refer to some key aspects of transformation when we talk about technology because then this is not expensive. I'm not telling everything, but I guess just put to put again in context. One of the very important aspects that we differentiate, if you ask me, what is different from what Exagone is doing and the others? These are some of them, I can tell. Autonomy at the device level, at the end point. This is basically referred to edge functionalities, not only connectivity, but computing analytics at the edge. So this permits that you do at the edge data mining. You can extract, as I just mentioned, you can extract what is relevant and you can more than this inter operate. That means I don't need to send even what is relevant if this is not timely or if it's not instrumental for the all architecture of the system. Basically today, the news the modern solutions should consider architecture from the edge to the premises, Edge network, cloud premises to simplify. That means I have 1,000 off cameras in Waterloo in London, for example, and I don't want to stream all the information to a central AI video analytics to identify somebody is laying the floor or somebody left a bag in a corner in Waterloo or if somebody is walking during 2 hours in the same post or something some anomaly, let's say. I don't need to string everything. I can process at the edge and send what's relevant. There are thousands of examples like this, but only processing the edge or at the edge is not enough. You have to understand in the whole, the entire architecture what is the meaning of that specific edge. So this is the concept. Edge Intelligence and Edge Processing opens a lot of new opportunities for real time. Another element is speed. Edge processing also influence the speed, right? When coming to the example that Ola mentioned yesterday about Netflix, when Netflix start, everybody said it's impossible to push movies, HD movies, high density movies to your house, right? How we do this, right? They start compressing. In the beginning, they compress and the quality you deteriorate very fast the quality. Then they start sending only what changed from one frame to the other. You don't send the complete frame. You send just what changes, and you compose these at the other edge. And then finally, they develop the vectorization technology. But basically, if you can process if you have edge functionalities, you can optimize what you push through. And if you have predictive algorithms at the edge, you can be fast than real time. That is new. It's a very sexy word now that everybody is saying. Fast than real time, that means you know what will happen and then you act before really happening. And this we have examples already in our domain for that. The second one is speed, right? So speed is influenced by edge functionalities and also artificial intelligence. And more and more, everything that we do is getting real time. So we need it's very important for us that we can really push information, what is relevant, back and forth. 5 gs is coming. 5 gs will be very important for many of our operations. But again, a correct architecture of the solution is more important than just pushing formation back and forth. The other element is future proof it. This is basically what I was telling. If we step the use case to pop up, to start developing capabilities that we will address that use case, you lose the game already. We have to have a framework that is Exalt in our case that prepare ourselves for the next step. If we embed Exalt in our solutions, we will be prepared for the use case that we don't know yet. We don't know how much we don't know in terms of the so fast and crazy evolution of technology and use case. So this is the concept. I'm compacting a little bit because I'm burning my time here. So these are and simplicity, sorry. In simplicity, on top of everything, the customers expect us to be user friendly. We have to have easy to use and we have to obstruct complexity. And obstructing complexity is not only the front end, but also maintenance, life cycle. That means our systems, we cannot have patchworking. We cannot sell a solution where that if when you have to do something, you have to go there and manually adjust connections. And so our system has to be self healing that go again in the direction, what Ola mentioned, of autonomous connected systems. But frankly speaking, autonomous connected system is supposed to do exactly this, right, to add simplicity, to obstruct things that the system should do. So these are 4 flavors of the transformational technology that I try to correlate a little bit with what we are doing with this key foundational digital capabilities. That means if we underpin, if we embed our exalt digital capabilities, our frameworks to our solutions, we will empower tremendously our technologies in many areas. We are discussing with the divisions many use case. We have many use case already ongoing. There are products that we launch with the exalt capabilities, for example. I'm not sure if Norbert mentioned PCDMEs Go today, but this is one case and there are in visualization PPNM in visualization, all these how you treat data to stream, how we present data in multiplatform. So there are many, many use cases that we are already doing this, but this will gain momentum because we are getting more and more mature with the capabilities. Let me give you three examples on how Exalt is progressively enabling Smart X and ACE. This example is on Geosystems. So we have some reality let's call reality capture sensors, could be a scanner, could be a stakeout device or whatever. And we have the piece of softwares that are the platforms for managing these workflows of this device. We are embedding edge clients, edge a kernel, a sub kernel of the logics of the framework. We are embedding in these pieces of software or pieces of hardware. And with these, we can push back and forth to the cloud and then we can feedback. We can use this kind of architecture or for example, use cases, customer intelligence. We can capture usage, how customer is using it, And we can understand where we can change, what we can do better, which functionalities we should do different, which steps we could automate. That means this is much more customer intelligence. This is the famous virtual cycles of the CTO of Baidu. So you sell more, you have more customer, you have more data, you use machine learning, you do better products, you sell more and so on and so forth. It's a virtual cycle that would bring monopoly to the compass. But really, the holy grail is not that. Where we want to go is not there. It's that you understand how the equipment works. You have a machine learning equipment with domain knowledge. That means we have the fitness function that show us which direction we should go. It's called in attrition in data science fitness function. And then we can change the behavior of the equipment on the fly. That means if I'm measuring something and I need more accuracy there, I can reduce the speed of measurement to get more accuracy without the user knowing this. I am making the equipment more accurate on the fly with intelligence, for example. Another example, this is another product very close to market. It's machine health for mining. We have the board computers because we have fleet management. We are one of the leaders in fleet dynamic fleet management. That means the systems self adapt as something wrong happens. And so we are embedding in the board computer edge clients. We aggregate information at the edge, one of the assets because this is a network, and then we push everything to the cloud. We have the predictive maintenance algorithms in the cloud just using what is important, the anomalies. We detect the anomalies at the edge, and we live stream into a command center and feedback to the machine. So basically, the same thing. We have some studies that shows that we can reduce to 10% the cost of maintenance of these big machines. So this is very relevant too. We are not unique with predict maintenance for mining, but this is with our capabilities of processing at the edge and orchestrating everything, edge cloud edge network, cloud premises, we think we have a differentiator for this product, too. Another one that is a little bit related to PCBs, Norbert, to what you mentioned today, we have at the machine level, at the edge level, we have edge computing and our edge clients for connectivity. We push information to exalt core at the cloud, And we use information from CRM because this is the fitness function, domain knowledge that we have from the CMM. And we with these systems today, we can push notifications to iPhone or any mobile device to a manager or supervisor to help him to take correct decisions. So this is basic decision support. Or we can have an algorithm at the edge. We are already sorry, at the cloud level to change behavior of the machines. Examples of these are many. One of them, you are measuring a body of a car and you detect the right side is less is trying to the dimension of the merit is trying to deviate. It's not so good. So you don't want to increase the cycle type of measurement, the cycle time of the measurement because it's a production line. So you start measuring less in the left side and more in the side that the dimension of the merit is growing. And you can push information to the press shop to verify to that specific part why the dye is pressing, is stamping this part to cause the dimension of the merit. Could be also in the welding. So all this logic is the domain knowledge. So conclusion, wrapping up what I said. So Hexagon core capabilities and domain knowledge empowered by Xalt will allow what we call smart digital reality. That means the convergence of digital and physical. Bottom line, as Ulla mentioned, is more productivity, more quality, more security, depends the application that you have. These are the if you want to summarize Exelq on a very high, high level, right? So we can position anything anywhere. We can capture reality in real time. We can provide intelligence domain expertise in the context that would be situational intelligence, and we can design. And then we have a lot of domain knowledge in vertical applications where we are number 1 or number 2. With our framework of Exalt, we have a major, major opportunity to capture more value in many areas. So that's my presentation. We make a break now, right, at 15 minutes, 15 minutes, and then we come back to Ben. Thank you. Welcome back. Good afternoon. My name is Ben Maslin. I've been Chief Strategy Officer of Hexagon for just under a year. And one of the key components of my role is that I oversee the M and A process. So we're going to spend about 15 minutes going through that process, talking a little bit about the kind of acquisitions we're looking for and then how they tie in with the overall strategy that Ola talked about before the break. M and A, as you know, is a key component of the 2021 financial targets. We aim to add 3% to 5% growth per annum from M and A. That is an average. Some years will be better, some years will be worse, but that will facilitate us hitting our 2021 targets. This slide tries to summarize the M and A process at HxGN overall. So corporate M and A, our responsibility is to screen all the acquisitions that come into the group. We work with the divisions to build a pipeline and then to take the acquisitions we choose to pursue through the completion. And on average, over the last few years, we've done between 10 to 15 transactions per year. Our capacity to do M and A is dictated by an internal target of 2.5x net debt to EBITDA. That gives us plenty of firepower to do acquisitions. And at the end of last year, we closed 2017 at 1.8x, so in a very good position coming into 2018. Where do our ideas come from? We get a lot of teasers, external processes coming in from bankers, and our role is to filter through those and work out which ones are interesting and to feedback down to the businesses. But most of the acquisitions Hexagon does are originated in the divisions. They will build long term relationships with potential targets, incubate those ideas, and when the time is right, they will send them back up to us for review. Now that review process focuses on 2 things. Firstly, does it fit with the Hexagon strategy? And secondly, does it meet the financial criteria that we use to work out whether these are good deals to do? In terms of the strategy, we're not just trying to fill a revenue quota with our 3% to 5%. We are trying to buy businesses that will accelerate the strategy that each division has. We spend 2 weeks every 6 months reviewing the strategy of the businesses, go into it in great detail. We work out how we can what technology they need to deliver that strategy. Should they develop it, invest more in R and D? Or can we buy something to accelerate that process? We focus very hard on the synergies that an acquisition will bring, and we give greater attention to those acquisitions that support the Smart X strategy that Ola talked about before the break. In terms of the financial criteria, we're looking for companies with a strong market position. We want profitable businesses, so we want the margin to contribute to the upward trend in margins that we've seen historically and we expect to continue going forward. We're looking for companies with a significant software element, high levels of recurring revenue. And it's important for us to look for targets that allow us to maintain our valuation discipline and create value for shareholders. Want to spend a second just talking about the ongoing shift to software. So if you add up all the acquisitions we've done since 2012, 65% of the revenues we've acquired have been pure software companies. And you can see some of those in the box at the bottom, MSC, Vero, Lucian and AgTech that we closed earlier in the year. The 65% excludes software that we might get bundled with a hardware company or sold together. And an example could be NEXXENCE that Norbert talked about in his presentation earlier. Handheld laser scanners, 30% to 35% of the revenues of that company are software. That's not in the 65%. And this shift is having a big impact on the financial metrics of Hexagon as a whole. Software and services now represents around 55% of group revenues, and that is contributing to rising profitability. It's reducing the inherent cyclicality of the group because these business models are more stable. So since the NAFTA economic downturn in 2009, we've obviously added Intergraph, MSC, Vero and so forth. They set the company up very well as and when we see the next slowdown. And finally, the shift towards software is accelerating the reduction in working capital that we see and the improved cash flow that we've seen over the last couple of years. So a very positive overall impact on the group. Maintaining financial discipline in current M and A markets has become more difficult. As many of you will know, we have a very hot M and A backdrop at the moment, fueled by low interest rates, a volatile growth environment that is forcing companies to acquire to keep their top lines growing. Private Equity Funds that have a lot of resources at their disposal. And obviously, financial markets themselves, spot multiples are very high. That just raises overall expectations. So how is Hexagon active in this market? We've kept disciplined. We've walked away from acquisitions or lost deals where we don't think the financial metrics make sense. But we've still managed to close 10 to 15 acquisitions per year at what I think are very attractive valuations. So how do we do that? Firstly, we screen a large number of targets. So for the 10 to 15 acquisitions that we close every year, we'll probably screen a couple of 100 of opportunities. At any one time, we have a pipeline of about 100 projects at various stages for us to draw from. And clearly, by looking at more opportunities, you can be more selective and make sure that the valuations work for you. Secondly, we focus on the highly synergistic projects. By identifying synergies, we can make sure that we can accelerate the growth and margin progression of companies that come into the group, and that helps bring the paid multiples down. And then thirdly, where we can and we try and structure acquisitions with earn outs, we think this makes very good economic sense. It allows us to pay less upfront and then align the incentives of ourselves and a company coming into the group to make sure it performs very strongly. And that altogether manages to bring the multiples down. Plus, we have a couple of inherent advantages. As I said, the businesses will incubate these opportunities, build long term relationships. We are often the preferred acquirer for some of these smaller companies that want to be taken over. We're not we have a fairly light touch in terms of how we integrate companies. We like them to flourish, support entrepreneurialism, which means that, again, for many companies, they want to come into the group. And we look at a lot of different areas, niche technologies, where some of the bigger players, they don't play. So this is tying back to Ola's strategy, enabling the SmartX and autonomous connected ecosystems that are pulling together the different technologies we have across the group into solutions for smart factories, smart cities, smart autonomous fleets, smart farms and mines and smarter construction sites and plants. And the M and A process feeds into this as well. So what this shows you is just some of the acquisitions we've done recently and how they feed into increasing the kind of technological reach that these solutions that we're working towards have. So for smart factories, MSC, Nexsense, Vero, smart autonomous fleets. We have Virez, a simulation software company for autonomous vehicles that we bought last year. Autonomous Stuff that we signed that transaction and announced it last week, that will play significantly into our longer term view of smart autonomous fleets. Ecosys, our project control software business, agtech, takeoff software feeds into smart construction and sites and plants. So lots of new technologies coming into the group. I have a few examples of those now, and obviously, you can spend more time with them in the zone. The first technology is LUCIAD, which we acquired in the Q4 of 2017. This provides a visualization platform to fuse, visualize and analyze geospatial data in real time, and real time is the key. It's on the fly. As Jurgen talked about in his presentation, you can pull in 3 d maps of cities. You can overlay that with sensor feeds to create what we call a 5 d digital reality, which allows you to show moving objects on a map and see how they pan out over time. This obviously has a potentially very big number of applications in our Smart X opportunities. As we can see here, in San Francisco, city applications, traffic, people flow and so forth. And then longer term autonomous fleets, anything you visualize, something moving on a map, has use in aviation, mining and agriculture. MSC, we acquired this just over a year ago. It's a leading supplier of simulation software, a very strong position in automotive and aerospace simulation, as you can see on screen. This has been within the group now for just over a year. Margins were already very strong when we acquired it, and the integration has gone well. Growth is now accelerating nicely. What MSC does, as Oli described earlier and in his keynote last night, is allow us to take the metrology data coming off a production process, which is a source of truth of what you've made, and feed that back into your CADCAM software, the manufacturing workflow and ultimately with MSC back into your design suite so you can make you can use that data in the next iteration of products to make it better and improve quality. And then finally, a little video on autonomous stuff. Again, we signed this last week. We expect it to close over the next few months. Their core product is providing platform vehicles that integrate hardware, software, all the key controls you need to drive and support autonomous operation. They sell to OEMs, Tier 1s, tech companies, universities, start ups, anyone who's hoping to build a product or a technology that goes into the autonomous vehicle project. Have their own software for speed, lane control and so forth, LiDAR object processing, as you can see somewhere in this clip, and solutions for capturing and processing the vast amounts of data, terabytes daily, that these cars kick off. I'm selling one of these cars, quite scary, very exciting. I think it will take me personally quite a while to actually have an autonomous vehicle. But for the group, we think it's a fantastic acquisition, very clear synergies with technologies that we already have. So positioning intelligence, the GPS and correction services that Michael's business has, simulation software in manufacturing intelligence and obviously, map production and processing where Hexagon is a market leader. And then longer term, clearly, the technologies that are developed to produce autonomous cars, that can be translated into solutions that we will be working on for smart farms and mines. Just in summary, this is the acquisition history for Hexagon Hexagon over recent years. So as I said, the last couple of years, the run rate has been about 10 to 15 acquisitions per year. So far in 2018, we've closed 4 acquisitions and signed autonomous stuff on top of that. In terms of the historical contribution to group revenue growth, 2011, the 33% is when Hexagon bought Intergraph. There were a couple of years after that whilst that deal was digested and leverage brought down where the contribution was a little bit less. But since then, it's stepped up nicely, and we are running at the 3% to 5% run rate that is our commitment to hit the financial targets. For this year, if you include acquisitions we did in 'seventeen and the spillover from that plus what we've already closed, we've got 3.5% revenue growth in the bag for 'eighteen. So in conclusion, M and A will continue to be a core component of Hexagon's strategy. We'll focus on acquisitions that have a high software element, high synergies with the rest of the group and contribute towards the development of our SmartX initiatives. And we feel confident that we can, even in fairly elevated M and A markets, keep adding 3.5% revenue growth per year and with that, increasing shareholder value. So with that, I will hand over to Robert. Okay. Thank you, Ben. Good afternoon, everyone. My name is Robert Velkich and I'm the CFO. And I'm going to take you through some finance slides the next couple of minutes. Starting then with a historical overview of Hexagon and the path to progress. Hexagon's path to becoming a leader in digital solutions really started in year 2000. At that time, we were a company of had sales of €500,000,000 and an EBIT margin of 5%. Since our transformational journey began, we have delivered strong sales and margin growth. And in 2017, we had sales of €3,500,000,000 and an EBIT margin of 24%. So taking you back to December 2016, when we launched our financial targets, our new financial plan, our 2021 plan. In 2016, we closed our books on 3 point €15,000,000,000 and we had an EBIT margin of 23%. The plan that was launched had the base case scenario or has a base case scenario €4,600,000,000 27 percent EBIT margin. And then we also have an opportunity scenario where we're to reach €5,100,000,000 28 percent EBIT margin. And then once again looking at 2017, where were we? We were at €3,500,000,000 with a 24% EBIT margin. So clearly on tracks toward these targets. Ben zoomed in on this one. This is the basic assumptions of our financial plan and the components of it. Ben focused on an M and A box. I will focus a little bit on the organic growth box. Once again, what we've said as Ben reiterated or said was 8% to 10% is the total growth per year on average. 5% of that growth should come from organic growth. And it's important to stress this is an average over this period of time. So any given year we can be above or below the 5%. So it's important to stress 5% is an average over this 5 year period. 3% to 5% will come from M and A as Ben pointed out. And then when this plan was put in place, FX was assumed to have a zero impact on us going forward. So looking at 2017, how did we end up? Well, total growth 10%, organic growth 5%. The contribution coming from acquisitions was 6%, and we had a negative impact from FX of minus 1%. So once again well in line with our targets. Shifting gears a little bit then, I would like to talk about a few key points that explains how our strategy has contributed to strengthening our financial metrics. Starting with the shift in our business model, as it's apparent from this slide, 55% of Hexagon sales today is software and services related and 40% of the sales is related to recurring revenue. Going back in time 2010, this was the recurring revenue part of sales was 20%. And since a couple of years later, we are now at 40%. And there are really three things that have been driving this transition. Firstly, it's a shift strategy from selling products to selling more solution focused products. So where we bring more value to the customer and having getting a response from the customer and then having ability to and then willingness to pay. Secondly, our software centric business has typically outgrown our hardware centric business lines. And then thirdly, as Ben pointed out, the M and A strategy of Hexagon has been acquiring software companies who has a recurring revenue model. And from Ben's slides, once again, 65% of the companies that we have acquired in the last couple of years has had these features software and recurring revenue. Okay. So where will these key metrics go going forward? What kind of target is can we have going forward? Once again, a very hard question to respond on and to give a scientific answer on because there's many variables at play for us improving these key metrics. So it is once again based on this development will continue to improve. You will see a continuation in this development based on the 3 arguments I gave to you in the previous slide. Okay. My next point is then our strong focus on R and D. As you know, that's the core MD and A of Hexagon. And on the R and D side, we spend typically 10% to 12% of annual sales on R and D. And this is really an essential part of our strategy to be able to continue to deliver profitable growth. From time to time, we also get questions on capitalization. Why do we capitalize? How much do we capitalize? And the effect we have on our P and L statement, is it increasing or decreasing going forward? And the answer is that we capitalize 50% of R and D spend every year and we amortize it over a 2 to 6 year period. And this has been the case for the last 10 years. So a very consistent approach when it comes to capitalization. And the reason for why we capitalized is really because it's pertain to new products, if the product is expected to generate considerable earnings in the future and the cost is significant. So looking at the benefit then from capitalization, as is evident from this chart, it's the gap between capitalized R and D and amortized R and D is roughly 2 percentage points. This gap has shrunk and is continuing to shrink and will also continue to shrink going forward. So final comment on this slide is really, I mean, the R and D focus and core of Hexagon, you've seen multiple examples of that throughout the day with all the divisional keynotes and all the interesting launches embedded in those. And you will see further more of that portfolio when you do the tour tomorrow in the zone. Okay. Another slide and another strong development. This is our cash flow starting in 2011 until 2017. Cash flow from operations has increased with 112% over this period of time. Looking at the cash conversion, our average cash conversion during this period of time is 85% and that should then be compared to our target of 80% to 90%. So the improvement is very much driven by the mix shift I mentioned on previous slides. And this also the recurring revenue driven model that we work with. Also final remark or comment on cash flow when it comes to seasonality. Typically, our cash flow is a little bit weaker in the 1st 6 months of the year and typically stronger in the latter 6 months of the year. Next slide then, looking at the working capital to sales. Once again, a very positive development for us throughout the years. Back in 2010 prior to the acquisition of Intigraf, we were at 30% plus and now in Q1 2018, we are at 13%. So a very positive development for us. And actually, internally, we have had an internal target of 15% and that has now been overachieved. It's a little bit of a soft target. We will never come down to 0. We will never as we are not a 100% software company with that kind of model, But us being on these levels is very impressive. We have bits and pieces of the HEXOON business and the HEXOON divisions that will always tie up working capital as we grow. And but still 13% is an impressive number. Final comment on our final slide, which is related to cash flow and then it's taking you back then to Q1 2018 and what we presented there. We will have 2 larger one offs in the cash flow statement during 2018, where we are investing in 2 facilities that will impact the cash flow negatively this year. It's Calgary, which is being inaugurated in July 2018, where we are moving into an R and D facility and that facility will house employees from Positioning Intelligence, PPNM, SI, Geospatial. And the second larger investment we do here is in Hongdao in China where we are investing in a state of the art technology park in Hongdao where we will showcase all different technologies and all different divisions within Hexagon. So the impact that these two investments will have on the cash flow statement is CapEx of €90,000,000 to €110,000,000 for 2018, which means that the amount in investment in tangible assets will amount to approximately €145,000,000 to €165,000,000 for 2018. Okay. So looking at our return on capital employed, here we have an internal target of 15%. We're currently at 12.6%. Percent. And considering the high profitability of Hexagon, you might think that the 15% target is a little bit on the low side. But you need to consider and you need to be aware of that with the very ambitious M and A strategy that Hector von has had historically and then going to have also going forward, it means that we have done several larger M and A deals, which means that the goodwill amount in our balance sheet is large. And also we are a little bit of a young company, I would say. It takes time for a company to grow into its balance sheet. And we with 18 years of track record, it will take time until we grow into our balance sheet. Eventually, we will grow into do the alternative calculation, if we would take away the good, we would take away the good, we would take away the good, we would take away the good, we would take do the alternative calculation, if we would take away the goodwill from our balance sheet, the return on capital employed would actually be 37%. So but for us and for me, it's important that we are moving in the direction of reaching the 15% target and that in itself is a testament of improving margins within Hexagon, a very disciplined approach when it comes to M and A valuations, and also once again the underlying shift that we have in the business model. Talking about margins then, starting with gross margin, 61% is our gross margin on a rolling 12 month basis. And once again, what is the underlying effect or the reasons for this one improving? Well, we have a lot of small incremental steps in the right direction within the Hexagon divisions. The software and services part increases, the recurring revenue part increases and the solution orientated sales increases. All that is enabling and fueling this development in the gross margin. And also us improving the gross margin is clearly an indicator that our new products that we constantly launch are able to command a higher price than previous generations. So looking then at the EBIT margin, once again a very positive development for us rolling 12 months, 24%, which should then be compared to the 27% and the 28% target that we have. Okay. Looking at our debt level then and our deleveraging capacity, what we have in our financial bank documentation today is one financial covenant. Net debt EBITDA of 3.5 is the max. And we were hovering around that level back in 2011 following the Intergov acquisition. We then took a deliberate decision to deleverage our balance sheet. We set up an internal target to reach 2.5. And as is evidenced on this slide, we reached that target within 2 years. Since then, this ratio has become or has continued to come down with the exception of 2 spikes. The first spike was in the fall of 2014 when we in the same quarter acquired 2 software companies, Mintech and Vero. And also the other spike is related to the acquisition of MSC, Hexagon's 3rd largest acquisition ever that created a spike in this curve as well. But what I think is a key takeaway from this slide is really we will have temporary spikes in this curve, but we also have with our strong cash flows, we have a tremendous capability of deleveraging very fast. So although the curve is spiking, we're coming down very fast immediately after that. So once again, if we just do a theoretical mathematical exercise, 31st March, we were net debt to EBITDA wise at €1.77,000,000 All things equal, that give us a headroom of almost €2,000,000,000 when it comes to net debt and €558,000,000 when it comes to the EBITDA. Looking at our financing then, here we also have a very transformational story I would say. Historically, we were very dependent on the bank loan market and that picture is very much different today. As is evident from this slide, today when our functional currency is euro, we have 98% of our debt being denominated in euro, 93% of our debt fits within the capital markets, I. E. Commercial paper, MTN notes and bonds. And our average interest rate on our funding today is 1%. 42% of the funding of our debt is long term and 49% of the interest rates that we pay are fixed. And the average duration of our debt is 17 months. Also a final remark on this slide, All the short term debt of Hexagon is at all times fully backed up with the revolving credit facility we have in place, a €2,000,000,000 facility sitting with 14 banks, which has a maturity in September 2021. So to conclude then and to summarize what I've been talking about today, Well, I've been looking at the shift in the business model towards more software and solutions, which will further strengthening our recurring revenue and margins. I talked about capital, the continuous improvement of working capital and the very strong cash flow of Hexagon. Also on the return on capital employed and the target we have there, it's an improvement, a continuous improvement despite a very ambitious M and A strategy that we have within Hexagon. And a final remark then that we are clearly on track towards the 2021 targets. So with that, I hand over to you, Ulla, and welcome you on stage. Right. It's time to wrap up and a few summary slides. Hexagon's expansion is going to happen in 4 areas: expanding the core. And I think you've seen today, especially with keynote, that we're modernizing and we're simplifying our products. And it's much easier to use the new products than the old ones, which is super important for Hexagon because we can act as a much greater market. Capitalize on digital transformation. We've heard that word over and over again, but I think it's not a mantra that you can use generically. You need to know what you want to transform. SmartX is our wraparound for the future applications that we see. And they are in factories, construction sites, autonomous vehicles and fleets, smart cities and mines and agriculture. And then we have new opportunities. And we talked about autonomous X, where we definitely have a strategy for acquiring that. And then we have the AEC market, which is a new market for us, especially in terms of software platforms. Content monetization is something that we've discussed. And it's a way of transforming old hardware revenue into recurring service revenue. And I think the best example we have of that is Geosystems that used to sell airborne sensors. Now we're selling data to users of data, and it's a recurring revenue business. Synergis and Innovation. We're continuing to leverage Synergis across the divisions. We have innovative sensing technologies and Exalt as a framework for all the divisions to draw from. And it's important to remember that it's not separate businesses. We're orchestrating this, so to say, to reach the SmartX. To create a smart construction site, we need the base platform from Intergraph, Hexagon would never have been able to do this. The geosystems technologies and sensing technologies and knowledge about that market is absolutely crucial. Geospatial provides 5 d capability, and manufacturing intelligence is helping with accuracy as well. So you can take each one of this, and we can tell you a story how we draw resources from all areas of Hexagon to make this happen. And I think when you look at other companies and you compare our companies to those companies, you will never find this depth and breadth of applications and technologies. And this is what's needed to deliver the future. So how do we set about reaching our financial targets? Well, it's a combination, as we've heard today, from divisional development, where we have divisional 5 year plans. On top of that, we have group projects where we pull resources from the divisions and from the hub to enable the SmartX. And on top of that, we have M and A, which for us is very much a make or buy decision. So we have a quote here from a famous professor, and that is autonomy can only be achieved by converging presentation today. And I think you're going to see more of this when you go to our technology center. It's that tomorrow. And with that, we open up for Q and A if there are any questions in the auditorium on what you've seen or anything you wonder