National Instruments Corp (NASDAQ:NATI)
NATI Investor Conference
August 6, 2013 11:00 a.m. ET
Alex Davern – COO, CFO, and EVP
James Truchard – President, CEO, and Cofounder
Eric Starkloff – SVP, Marketing
Ray Almgren – VP, Marketing
Pete Zogas – SVP, Sales
John Graff – VP, Americas
Francis Griffiths – VP, Europe
I guess Caitlin if you can close out the doors. Okay, if we could all get seated we will get started. Hopefully everybody had a chance to attend the keynote this morning, and got some of the energy and enthusiasm in the crowd, certainly got me going early. This morning was great to see.
For those of you joining us on the webcast, the keynotes this morning were also webcast. If you haven't seen it, you'll be able to see a repeat of it later at NI.com. My name is Alex Davern, I'm the Chief Operating Officer at National Instruments. I'm going to do a quick intro and then we'll hand it over to Dr. Truchard to get right in there. If we can move to the first slide that would be great. So we should have a Safe Harbor, Caitlin, can you put that up or I'll just talk to it?
So in our investor conference today, we will be making some forward looking statements. I advise everyone to refer to our SEC filings for a comprehensive list of risks. Forward-looking statements obviously are always associated with the risks that we may not be accurate, may not be right. So I would like you to understand those risks in investing.
In our topics today, Dr. Truchard will be kicking it off talking about how we are going to drive technology and use that to leverage into revenue growth. Ray Almgren and Eric Starkloff who is also in the morning in the keynote stage, where they will be focusing on our software differentiation and how that drives platform adoption. Pete Zogas with some of the regional vice presidents of sales will talk through our sales model and how we leverage our position that will let you to drive our revenue growth, and then closing this afternoon, I will talk about how we are going to drive operating leverage moving forward.
And without further ado, I’ll hand it over to Dr. Truchard.
Thanks Alex. I’ll stand up here so everybody can see in support. What I would – we decided to do today is kind of give you the behind the scenes story more from the shareholders perspective of the talk that I gave this morning. So it’s basically the same slides but the story behind the story that I would like to share. Because this has been very confusing, people will ask me, “Okay, how much business are you doing in industrial market, how much tests and so forth…” when we are seeing it as one thing. So this is – to make that point I started out with this simple example of how with the iPhone now, all these apps some of them are instruments, some of them are embedded devices and so forth but they are a one platform and there isn’t an app store for instruments and there isn’t an app store for these embedded devices, they all reside in the same app store. So that’s our perspective of creating a platform that totally redefines the perspective that you need to take on it. So that’s what I was trying to do here, talking about one of the oldest instruments and one of the newest.
And then pointing out these examples, all instruments on the left and embedded systems on the right, they are all part of one ecosystem. So understanding that concept is central to understanding the vision that we’re trying to create at National Instruments and how we’re operating. So we saw how they’re also now all virtual instruments and platform based embedded systems. So with that perspective we went on to this slide and I’ve pointed out the [backpipe turning] that gives people perspective on measurement devices and the ecosystem system and operating system that embraces them all. And that’s our goal with our platform in graphical system design. So , we started out in the ‘80s using the phrase virtual instrumentation. Over the last 10 years we’ve moved that phrase to include not only virtual implementation but include this platform based approach, graphical system design.
So we’re really trying to redefine how you think about – though that the technology that we use and we sell on our platforms, that is indeed a platform based approach and it does both measurement and control. And I will talk about how we then take that on for our vision going forward. Key thing is any of the applications can be done with combinations of the platform. Now one big difference about our marketplace, our application areas rather is that we have many, many different kinds of measurements we have to do. And so that's why we have so many different IO products. I always say if we could have a 100 GHz 32-bit [ADD] converter, and that was low power, we’d need only one card, or maybe a few, but basically because we can’t get all the performance and all the dimensions in one IO module, we have to have many, many different choices and that each time we pick a new choice, we can expand our efforts into a new area, new kind of measurement or new customer or the like.
We also have two major platform sizes, one is PXI which is for the heavy-duty instrumentation, heavy duty large scale systems and then a CompactRIO, which is for the small-scale systems and CompactDAQ reuses the same module that CompactRIO does. So these core or three platforms as it were really give us the IO capability we need to serve these very, very diverse set of applications across these domains. And then at the application space, the customer has lots of different needs of analysis capability, ways to look at their problem, and we try to address those and solve those, LabVIEW was very fortunate in coming up with a model of computation that this works very well for these distributed multicore and as we call them heterogeneous processing systems. So we are able to serve with one platform and some core technologies, a very broad array of applications.
Now I was giving a talk at RF Regional Advisory Council and I started with this slide, and the point of the slide was it really set a stage of our vision and it was the timeframe – it was the exact timeframe when we started the development of LabVIEW. And Jeff and I would meet once a week or so and I hit him with ideas, he gave me his feedback each time, and we did that for 2 years to come up with LabVIEW and that’s how we got the LabVIEW, and it’s based on kind of these points that we were trying to create, we used the phrase in 1985 to do for test and measurement what the spreadsheet did for financial analysis. And we really were very fortunate, Jeff came up with technology that as I would put it nailed it, it really answered this goal that we had set. And we were able to set the stage for not only what we could do in test and measurement but also in this embedded space as well, so that’s how we got from that point.
So in that -- in my RF presentation I used the Qualcomm example which we highlighted last year where with the PXI system they were able to be 10 times faster than the traditional instrumentation systems, mainly because they could synchronize measurements at a much higher speed. Then by going to the FPGA and as you saw today, controlling the unit under test directly from the FPGA you could get over another order of magnitude 20 times faster beyond that. So 200 times faster than a traditional GPIB based system where we started in 1983. So that was our vision being accomplished through each step along the way and the process.
I used this again – I used this last year, which is it really brings home this platform-based approach that we are bringing to the marketplace, that is indeed a major transition taking place. We still have alarm clocks and instruments, traditional instruments from the past, but we’ve moved on now where from the generation of roughly 45 years with Easton, a general radio company was successful with vacuum tubes and then transistors and integrated circuits with Hewlett Packard another 45 years, and now a software based approach built on platform. So once again making a change in the perspective – that would be the old instruments still around, they won’t all go away but the center stage just like the clocks that are still around that we place all of them, although my alarm clock on the iPhone really works well compared to these ones in the hotels which I can come in late at night and I can never figure out how to set correctly, whether they get really go off or not. So the technology has moved on toward this platform-based approach really a center stage.
So we’ve over the years used to assemble ying yang the software and hardware view that’s very, very well [woven] in this platform based view. We still have bits versus frequency, we still want all these IO, because we want these control systems as I will explain to have this measurement capability and IO capability in them as well, so we call it virtual instrumentation, it’s still virtual instrumentation but it’s in the bigger context of also doing this graphical system design.
Last year we introduced the vector signal transceiver and it was the realization of decades of work for us, first starting with processor software, move into FPGA software, first on plug-in boards for the PC, then in CompactRIO, moving into our – some of our -- we had a product called RF RIO which was kind of a prototype for what the VST would be, on into FlexRIO, then on to VST. Note these are all with the same platform-based software built around multicore and FPGA as you saw today. So it’s a really continuous progression moving between heavy-duty taking on some of the hardest industrial applications around and then moving into RF communication, software-defined radio, RF measurements, high performance measurements on the production floor to make our most successful product ever. So really building in a straight line on the vision around the platform-based approach.
As you saw this a lot today, this combination of processor and FPGA, now there is another dimension that you will hear us talk more about in the future. And that’s distributed systems and the cloud you will hear about that more – [focus that] around tomorrow you will hear more about the cloud, tomorrow. So the cloud is becoming a part of this and it’s a part of this industry 4.0 as the Germans call it. So really it’s this idea that you can have information from anywhere, influence decisions – decisions can be made anywhere up and down the chain all the way in the front end FPGA. So it’s really about the technologies that have been evolving over the last decades, coming together to create yet another industrial revolution. And that’s done again with our graphical system design.
So here we show a slide taken directly out of German working groups, it was the industry 4.0, of course Germany makes their living with industrial production, they’re world renowned, certainly have shown a lot of leadership and that with all the money in Europe, I guess there is something and their national academy of science and engineering produced a study and a report where they show all these technologies coming together to create yet another industrial revolution.
Now a little background story, I was invited to give a keynote talk at a workshop – cyber physical systems workshop October of 2006 -- October and the lady who ran that workshop at a recent National Science Foundation workshop attributed me as defining what the cyber physical systems were and my talk that I gave, and basically by talk was about our vision for graphical system design and the CompactRIO and how it could change the way industrial applications were done. So we have been very much involved in this process of defining and driving forward the next generation of the way systems would be built in industrial factory.
So cyber physical systems is a term now accepted both in the U.S. and in Europe with Germany leading the way in Europe. And here we see a definition of computation, communications and control, with this ubiquitousness that we like to see where this allows manufacturers to create quantities of one, for example, efficiently. This allows quick feedback, global differences yet have in common technology. So all the elements that are improving efficiency of the production process, better use of materials and so forth. So it’s a lot of attributes each one driving and we see literally thousands of examples where people are trying to do this to make more efficient use of energy and create -- generate energy and the like. So basically around this concept of computation, communication and control.
So you may hear lots of different terms, it’s ironic, one that I kind of now like now and which we used a lot earlier, it’s intelligent system. When we went public [Brian Beam at Robertson Stevenson] used that terms to describe us, I wish that latch on to news even since, that probably saved a little work on the marketing side but it’s basically a very good term and [it’s 101 used] – the latest one you will hear a lot of buzz around programmable world and one we are going to be using a lot because our customers are building this big analog data, where you take in all this data and making it into information, so that’s one that will be coming into the picture.
Now the White House has just started an initiative with the Office of Science and Technology where Vijay Kumar is busy working and we’re putting them to work on the tip of the problems that we still have. Synchronous communication is one, that having math that’s readily accessible to another, so we are seeing that these initiatives really add value and help us in our process of bringing this technology into the marketplace in communications and ways of doing it reliably and predictable, a critical for critical safety systems for example, and just making the thing work reliably in the wide range applications. So they will be hopefully helpful in this process of driving this technology forward.
So looking in it, we are using this graphical system design to build cyber physical systems. So fundamentally we’ve got technologies that’s highly unique for solving these kind of problems. So a statement I often use when I give a talk at the big physics conferences is, for the first time in the history you can have advanced measurements in the same platform you have in advanced control because we have all these measurement technology but on the other hand we have all these control technology, all the mathematics, all analysis needed to do advanced control. So in one platform you can bring both capabilities together, you see demonstrations of that with extremely large telescope, the work we do at Telecomax, the Large Hadron Collider, these are all examples where we are bringing the two elements together into one platform.
So I put out a [be-hag] the first time it’s been seen, to do for cyber physical systems what the programmable logic controller did for discrete systems. These programmable logic controllers are made by companies like Allen Bradley, Siemens, (inaudible). So they are the ubiquitous components primarily around discrete systems, in other words, off on taken place that – the only place what used to be called ladder logic that was done by relays. You use relays to create logic and the programmable logic controller, as the name implies, replaced that, and these are the main space of industrial production now. We see the change where more accurate measurements are going to be needed and used to go to the next level and that's where this cyber physical systems, more use of software, more use of distributed capabilities, distributed flow of information alike as the major trend as we go forward.
Here are some of the examples of things we've been working on all the way from medical devices to software defined radio. We've been doing radar systems. Smart grid is obviously one you read a lot about in the newspaper and hear about on the news. We are heavily involved with the things like phase measurement units, control IGBTs. We have GPIC, which lets you control IGBTs, for putting power on the grid, whether it’s a storage battery or megawatt storage battery or multi-megawatt wind turbine watt, we’re able to work with that.
We are also doing some work with fuel cells for the home, a company in Korea, for example, and then of course a lot of different physics applications, also working in the transportation area prototyping next generation system, testing a variety of different technologies, electric cars, batteries – testing batteries has been a big area for us and the like, and then of course a lot of prototyping work, lot of work in academia where these technologies and tools are being used to help teaching next generation concepts.
In 2008 keynote, I talked about the petabyte age for the first time and now we are really seeing that come to pass. To use the information analog data is the most prolific data in the universe, it’s all around us, and we have the measurement capability to measure that analog data and petabyte age was about a lot of sensors around, lots of data and where you have more data, but more is different now because we are able to make value out of the data in our approach in the petabyte age. So basically it’s about information and cyber physical system taking that data and convert it into information for automated and human decision-making in the process all up and down the chain, all the way from the FPGA up to the cloud, we can be working and here we see another definition.
So when we started data acquisition work and even when we were working with GPIB, we used three icons, acquire, analyze and present, that’s still there. It’s just in a bigger scale where we have distributed systems with lots of sensors, lots of IOs, we call them data acquisition and analysis nodes, on into the cloud. And we can run software at all locations and get an optimum solution, get that upfront, screening out data that we don’t need, and only sending to the central location the relevant data, for example, can be part of this process. So we are uniquely positioned to move into this new era where you have ubiquitous computing and ubiquitous ability to do analysis and computation.
So we use the term big analog data to position what we're trying to do, and the architecture starting with the sensors, which typically our partners work with or make and then the system nodes which are data acquisition analysis nodes, on into the IP infrastructure. We’re starting to take on new partners that can help us in the IT part of this process.
Looking at particular application always helps to see one first hand, get underneath the rail car, look at the CompactRIOs and see the electric motors and I actually got a little clue of how Tesla got all of their technology for motors, they had to just look at railcars and I got to see some motors on the railcar. But what we got out of it is that mundane problems can really be helped with this big data strategy and you run these railcars for years, you take all this data, terabyte of date whatever and then you go back and look at the patterns for things, (inaudible) cars use more electricity? Did you have it timed so this car is going up the hill and the other one is going down, so you don’t have to use the brakes, you just dump the power in the grid and it gets used by somebody else, otherwise the voltage gets too high. All these new things that once you put the data together and step back and look at it, big data has messages to tell you on how to operate, railcars were failing because they have tracks that were bad, these things show up because the car vibrates as it goes over these cars. Next thing you know that car is failing. So these are things that are valuable in getting better systems, better efficiency and so forth and you will see many, many of these as the years go by.
So again some of the big data applications in our space that we can work with and started to work with, that will only continue to expand as we go forward. So graphical system design is a platform based approach and then we are able to really take on a new set of problems and combine both test and measurement applications with industrial embedded applications.
So with that I would like to thank you.
Okay, thanks Dr. T. Okay, good morning everybody. I am just going to stand down here, I’ve already had enough time on stage. And I am going to go through and talk about our platform, you will hear us some of the messages – some of the messages that came through in the keynote but I will be diving little bit more into (inaudible) opportunity, growth opportunity side of that. And then my colleague Ray Almgren will also come up and really get into our strategy around competitive differentiation and platform adoption and the science behind platform adoption.
So I encourage you to ask questions during my presentation. Don’t hesitate to raise your hand, we do, we are webcasting this, so I want to make sure if you have a question that we capture that on the microphones. So Marisa and Gary are in the back, put your hand up and they will bring a mic to you and ask your way.
Okay. I am going to start with some pretty fundamentals, our mission as a company and you probably saw some of that this morning and you'll kind of live and breathe it here this week. It’s to equip engineers and scientists with tools to accelerate productivity, innovation and discovery. And it actually provides kind of a pretty good framework for explaining our business here this morning, because I will talk about – when we talk about scientists and engineers I want to give more color to you about which scientists and engineers, which applications and markets and opportunities that we see and where we see the growth opportunities.
I also want to give a little more color on these tools and obviously NIWeek is a big launching point for us for new products. And so I want to talk about some of the new products and what that new capability really means from our perspective in terms of our business opportunity.
And then as I said in the center, if you saw the keynote this morning you probably took away this idea of a single platform going after all these opportunities and that single platform is really built around integrating our software and our hardware and our business is built around the foundation of driving loyalty and differentiation through our software. So that’s the part that Ray is going to dive pretty deeply into and talk about how we do that, and how we drive value for this from the differentiation that we create in our software platform.
Another thing that probably came through loud and clear Dr. Truchard showed it was this common architecture and that's really been a refinement of our strategy over the years that’s really coming to a point now where we literally have a common technical architecture that underpins all of these different product capabilities and you saw this morning a really large breadth of applications that are literally using the same architecture under the hood and much of the same technology is reused going all the way from high performance test systems to deployed embedded systems. And that’s deliberate, has been very deliberate and this is why -- this is what we see as the benefit to NI of having this really focused effort on building a common architecture, it gives us a lot of leverage of our development effort, we’re able to develop a common set of products that serve all these different applications spaces with the same R&D. We’re able to meet a lot of niche applications and so many of the applications that we showcase and that we serve are niche applications that might be difficult to solve or there might be a niche company that solves that and what we are betting on is that we can create a platform that solves a broader set of applications and therefore is much more competitive and lower cost in each one of the niches that it serves.
Obviously there is a benefit of economies of scale, as we get more commonization across our products. We have single products like the vector signal transceiver that sell into a whole bunch of applications in RF where traditionally you’d have many different boxes. So there is an economy of scale at the product level and then literally inside the vector signal transceiver are the same component technologies that are used on other product based on that architecture that I showed. So there is another economy of scale around having common components and the purchasing power that we have around those common components.
The customers -- being able reuse their IP, we talked about the scalability over time and between these applications, that’s the benefit ultimately to us as well, really realized through that last bullet. Having this vibrant community and NIWeek is a great place to experience this, so those of you who that haven't been here before, this is kind of a living breathing version of our community. These are loyal, very loyal customers that have built primarily around our software platform and have a pretty intense loyalty. Many of them have built their career or their livelihood as partners around our platform. And so you saw us showcase a couple of those this morning.
But that's a pretty powerful force multiplier for us and as I said Ray is going to get into that in more detail but we think that’s very unique especially in our core kind of years in test and measurements, don’t have that element to their business, they don't have this software community surrounding their platform, most of them don't really view it as a platform approach.
So we think the result of that has been a gain in share. This is one measure that we do in terms of our share, we look at an aggregate of public test and measurement companies. And you can see that over the last six or seven years as shown in this chart that that there hasn’t been a lot of growth as you know among these companies. So they are really incrementally up from 2007 and a very large portion of that incremental growth came to NI, as we've grown rather significantly over that same 7 year period, and that’s the result of the investments we've made and the differentiation we’ve had and our ability to disrupt traditional relatively slow moving market.
So let’s talk about test and then I will get more into embedded, this is a view of the opportunity that I've shown you before. That kind of shows some of the application areas within test and measurement and a couple of the growth opportunities here in the area that we're pursuing that we believe there's opportunity for growth are actually related to some of the reuse of technology that we get between going after test and embedded, this kind of different market areas. So one example I was talking to a few of you about last night is real time test and so real time test is basically a type of test that you do in a validation lab to test the software of an embedded device. So the most common place this is used is in automotive, you have all kinds of software in your car, you probably know that, running on embedded electronic control units and in order to validate that that software works correctly and it doesn’t have a [barge], it doesn’t have a safety issue, there is a technique that’s done to emulate the rest of the car in order to test that embedded software and... that’s what real time test does and for us it combines the measurement technology that we’ve developed over the years for test and measurement and the real time control technology that we've developed primarily first at addressing some of these embedded opportunities.
And the union of those give us a very competitive platform for these applications which are growing. So as software content in embedded devices grows those techniques are expanding beyond the automotive market into everywhere else where you have embedded software running. You need to do – the technique here is called hardware in the loop test, you need even electronic control unit on your washing machine, and that gets tested in a very similar way as some of the electronic control units in your car. So that’s a growth opportunity that we’re pursuing I think we have a very good platform for.
The other one I talked quite a bit about is wireless and RF, and been a focus for number of years. It’s an area that’s growing significantly for us. We’ve had quite a few investments and as I mentioned this morning the product we launched last year at NIWeek based on the same architecture and using the power of the FPGA to improve the performance of test systems has really been a breakthrough product for us and I will talk a little bit more about that.
So here’s kind of an overview of our approach within test and measurement. So I actually tried to avoid drawing hardlines in terms of the hardware products that are used in these different opportunities because the truth is that things like PXI are used in test and embedded and platforms like CompactRIO are used in also embedded but also in test. And so it’s not as clean and that’s again that’s by design, that’s the way we’ve purposely architected our platform to give broad capability to different applications. But I think it’s a reasonable proxy that if you look at high performance test applications those are primarily solved with our modular PXI platform.
And as I showed this morning and we tend to show each year at NIWeek the benefit our customers get is ultimately in lower cost of test, and we think that's a pretty intense need in the marketplace, no one wants to spend more on test. They are pushing to lower their cost of test and we have a platform that can provide that and it does that through faster test times. So when we showed this morning 120 times faster test, that results in lower cost of test, if you can test something faster, you need less testers, lower capital expenses actually providing equipment that is lower cost than our peers. And the other element of total cost of ownership is the development time, being able to get a tester deployed quickly if you lower the development costs of the test system.
So another discussion we had last night is – if you are doing this, are you as NI shrinking the market, shrinking the opportunity and I think that is -- we believe that there is some inevitability of that and as a disrupter it is our strategy. Customers need lower cost test systems, we are very a small percentage of that opportunity and we believe we can provide that and disrupt the market and grow in the process.
So one point I want to make on RF as a growth opportunity is that the reason RF has been a focus for us and wireless is that we believe this is a pretty broad need in the marketplace and it’s a need that’s getting broader over time, I think a lot of times you think about wireless and immediately you think about consumer electronics products like your cell phone and so forth as were RF testers. And those RF applications, in RF, there are applications we serve but our reason from putting a lot of focus on this is wireless is migrating into everything, like we all see that as consumers. And so wireless is becoming a core need for testing devices across basically all of the industries we serve.
And so when we talk about the growth opportunity in RF, we are talking about not just mobile device test, although that’s part of it, we are talking about things like the radar and defense opportunities. Signal intelligence, electronic warfare, there is a whole set of applications in that space. We are talking about testing the infrastructure that’s used [to get a micro-printer]. Talking about the infrastructure test that’s used to carry wireless signals as well. Yes.
Just looking at your $6 billion TAM, that you’re talking about on RF, if we look at the VST2 where we stand today and your list of growth opportunities in RF, can you help us understand of that $6 billion TAM, what you can currently serve with your VST2? And of those four opportunities if you could help us kind of size the relative market opportunity?
Sure. So I think that – first of all there is a couple of ways that we look at this overall opportunity. These are kind of our own look at estimates on it because most markets studies don’t break these things down. But one is frequency range, so the things at all different frequency range in the spectrum, and then the other is in – part of that marketplace you have wireless standards, right LTE and Wi-Fi and so forth and so on. So from a frequency coverage point of view we now have coverage of products up at 26 GHz, a very high frequency. The vector signal transceiver goes up to 6 GHz itself, that particular product to different product, it goes higher.
The high frequency capability we have by the way is largely in part of an acquisition that we did a couple years ago in Phase Metrics. And so 6 GHz and below is majority of the market opportunity, all of the consumer electronics and everything that we all use are in that frequency band. So all of those applications that you think of wireless standards tend to be in that frequency band. As you get higher in frequency you're getting more into defense and aerospace applications and radar. There’s a substantial amount of the opportunity there as well and once you get over 26 GHz it’s really niche, it’s a very small portion of the market above that. So we have frequency coverage that covers most of this opportunity and get a majority more than half we believe is under 6 GHz.
Then from a standards point of view, one of the areas we’ve invested quite a bit over the past seven or eight years is in our R&D development and software development around having all the coverage of all these standards, because it’s constantly changing and you have to be able to – more and more devices have multiple radios and so you have to be able to test multiple things, you have to be able to test LTE and Wi-Fi and Bluetooth etc.
And given our investments over the last few years we are in a good position there as well. We have coverage of all the major standards and the bulk of the opportunity from the wireless standard point of view. And one of the things we showed this morning, I don’t know if it came out or not, but one of our strategic objectives is to actually be using our platform to prototype next-generation standards so that we are actually ahead of the curve when new wireless technology comes out. So the wireless gentleman – one of the PhDs [Sadat Mckiel] is working in a team we have that is working with researchers on 5G which is pretty far out there but already researchers are using LabVIEW to sort of define some of the math and analysis that's needed to support deployments seven or eight years from now. So anyway that’s part of getting us earlier on so we can capture the market opportunity when things are rolling out.
Now to the things, I don’t think I can get as granular at each one of those, but obviously in terms of order of magnitude mobile devices and wireless is a big part of the opportunity, but one of the things I also want to emphasize on that – that’s the largest one on that list, but I do want to emphasize again that’s a pretty broad opportunity. People think of the – we think of the LTE for example or 3G, you think your cell phone, well there is also a whole market opportunity of all the other devices that are having in a machine to machine and other applications that are getting wireless and those tend to be really well suited to our platform because wireless is one of the measurements you need to do among many. And the more integration of different types of measurement and test you have, the more compelling sort of modular software based platform is. So that ends up being a key part of that market opportunity, the largest is wireless and the next is this broadly military and aerospace is a very pretty big market opportunity, in fact, there is probably in order of size on the slide there. Thank you for the question.
Just one number though, if you had to throw out one number, your 4 million out of 6 billion covered –
How much we have covered from a pure technical capability point of view, yes it’s certainly more than half, certainly well over half is covered from a pure technical capability point of view and now obviously we are – on the other hand, we are pretty new to the market, our competitors in the space have been in this space for 50 years, literally. And so it’s an area that we know we have to build more brand perception and another element to our strategy and we acquired AWR last year, was related to sort of building our critical mass in our brand perception we’re seeing -- that we are seeing the perception in the industry change, to view us more as a company that plays in this arena but that happens over some time. So that’s the work we have ahead of us but from a technical capability I think we have strong coverage.
Okay. So here is a proxy again, we talked about PXI and our opportunity there. Here is a view of the overall revenue in PXI from all vendors. So this is data from a prime data, this isn’t just the NI PXI curve, this is all vendors and you can see that compared to the industry that I showed before that had virtually no growth from ’07 to 2012, here this has almost doubled. This is significantly faster growing area than overall test and measurement.
Now the other point I want to make on this is that according to this study, NI has over 80% of this revenue and that’s been steady to growing over the last few years. I think that’s the key point in that we have this industry-supported multi-vendor platform in PXI but are own differentiation in having all of capability and all the components and in particular having the software that is used on almost every PXI system has made it such that 80 plus percent of these PXI applications are sold by NI. And so that's really the ideal situation for us.
Okay, the case study that I wanted to share and this one is we mentioned that briefly in the keynote this morning but I really want to illustrate this as really indicative of a lot of the opportunities that we have in the space. Hittite is a medium sized company, they are about $260 million in revenue and they do high precision components for military and aerospace applications and cellular infrastructure and even test and measurements, so they sell components that are used by T&M vendors for high precision measurement. So the point is they are not a huge multibillion-dollar consumer electronics company, they are $250 million, there is a lot of Hittites in the world, hundreds of companies that are in this kind of category. And they do validation and production test, that’s another difference that a company of this scale align between sort of validation test or engineering test and production test isn’t as [Stark], right? It’s not like they have some bunch of factories of contract manufacturers, they do all this sort of in house and sort of medium to low volume.
But test time still matters to them, test time is still a very expensive part of these high precision components that they build, a big part of the cost of those components is in the time it takes to test them. And so that's why they turned to the vector signal transceiver, that’s the product that they are using. And they are using some of the techniques that we showed at the keynote this morning to put logic down in FPGA that is unique to their application, it’s unique to Hittite. And I think that’s the key point. Last year I talked about when we launched the vector signal transceiver I talked about Qualcomm, they are the ones that have achieved the 200X performance improvement in their validation lab, same thing. Qualcomm got that performance improvement by putting intellectual property down on the FPGA that was unique to Qualcomm, we couldn’t just invent the stuff and design it into the product. We had to create an open platform that allows them to put their own unique IP in order to achieve this performance gains. A lot of times that’s because intellectual property is related to specific interfacing to their device and their chip, and it’s a proprietary protocol to do so.
And so same thing with Hittite, they are achieving a 30X performance improvement. Again I mentioned this morning how we get little numb to it, I mean it’s really astounding. We’re not talking about 10% or 20% or 50%, 3000%, 30X so it’s pretty remarkable improvement that they saw and that obviously has a dramatic impact in their cost.
So to switch gears and talk a little bit about the opportunity in embedded, I think this is one I want to spend sometime on it, it’s a little harder sometimes to understand our opportunity in embedded. In test we have set of traditional test and measurement companies and lot of them you cover them and you can compare us pretty directly to them. In embedded we are talking about opportunities to change the way people build systems, to do it differently than they have done in the past. And you saw this morning we talked about custom design, the alternative to what we are proposing is custom design and when we say custom design it literally means buying components, designing a printed circuit board, building on them there and then designing from scratch all of the software to build some kind of an embedded system, that’s what most of the world does.
And we fundamentally think there is an opportunity to provide an alternative where you can use higher level design language in LabVIEW to create these systems and prototype them and then deploy them in actual applications. So the other simple statement is the difference between test and embedded is that in test we are testing your products, in embedded we are inside of your product, the customers’ product.
It’s the same platform and literally can be the same products but the benefit is different, the value statement to the customer is fundamentally different in the space. And so here it’s about shorter time to market, that's the advantage. By using this platform you get your idea to market faster than if you have to start from scratch each time. And I think therefore the opportunity is that we tend to serve in embedded our opportunities and applications where time to market is highly valued, where there is competitive, there’s a lot of innovation and people are kind of in a rage to get a solution to market. That’s where our platform provides the most value.
And so you see things like – I will show you what an asset monitoring in a minute but you see machine, control precision machines, disruptive kind of machines, the smart grid, and energy applications, alternative energy or new techniques for oil and gas extraction and fracking we talked about, those are the opportunities, and life sciences, all kinds of new medical devices are often areas where people are trying to raise, to create solutions and our platform provides a way for them to build those designs quicker.
So fundamentally here, not only are we being disruptive, but we are helping our customers be disruptive in their market by getting to market quicker. So here is an example I – couple of examples here, this is one that I mentioned briefly this morning. This is very typical of the type of application. So OptiMedica, relatively small company, building a device to do laser eye surgery, had an idea the new technique for cataract surgery, built a platform based on – in this case a plug-in board that has the same architecture of the FPGA and the processor and IO, runs LabVIEW, and built the whole machine around that, all the vision and motion and controllable lasers and everything is done inside of this board.
And the other thing to keep in mind is, when we are talking about embedded, these are machines that sell thousands to tens of thousands, that’s kind of the sweet spot in volume for us. And there is a lot of things in that category. These likely aren’t things that sell millions, at some point if you are selling millions of something the economics lead you to reduce cost to a custom design. But in a thousand to tens of thousands like most medical devices, a lot of energy applications, that’s the sweet spot for our platform. And that’s exactly what this is and I showed you how they just got acquired and I think that’s another statement about this ability to be disruptive, the company that acquired them obviously has a larger R&D budget and can do a lots of custom design of new machines, but in this case OptiMedica beat them in market and had a disruptive position in the marketplace.
The other example we showed was, energy application, this is a smart grid, I am going to talk about the smart grid. So they are literally building intelligence into the grid, they are in Toronto to better handle all the different distributed energy generation alternative energy that’s being put on the grid. And so again that is a CompactRIO system that’s getting deployed out into the grid at different distribution points, and the opportunity there, as I sort of hinted at the end of the keynote is they are interested in permeating the technology even further to each end note of the grid itself. So tens of thousands, hundreds of thousands, of components.
So I mentioned a lot of the areas where we are most successful where we have the most differentiation opportunity is the kind of the intersection of these things that are looked at as sort of discrete opportunities. And one of them I want to highlight is in the space of monitoring, machine condition monitoring and this is an application that's actually going to be highlighted real prominently at the keynote tomorrow but I know a lot of you might not be here for that. So we are actually going to have on stage some senior folks from Duke Energy, the largest regulated utility company in the U.S. and they are doing a large deployment of machine condition monitoring systems based on CompactRIO and the goal here – this is a really interesting application because when I say it fits in between, it again is a measurement application, like a test or measurement application but it’s a deployed industrially rugged system, they are putting one of those CompactRIOs on each of their machines. And so it has these attributes of industrial ruggedness and real time control because they actually ultimately wanted to do some control of the machines themselves but it’s fundamentally a measurement or data acquisition application.
We will show a picture something like this tomorrow – this is a little complicated, I will walk you through it. So here is what they are doing. They have all this generation equipment around eastern US, they actually have ten thousand different machines that they want to monitor for the purposes of doing preventative maintenance. They want to prevent and predict failures. And so their goal is to outfit all of those machines with sensors and measurement devices and put a measurement device on every machine or new machines. So it’s thousands of measurements systems. And the goal they have is to basically first use complex analytics big data to start to aggregate this information and predict the performance of machines and predict failures, predict when a turbine blade might break or predict when a bearing might go out. And they are actually working with some of our partners that have expertise in that specific area and they will focus on LabVIEW to do this kind of preventative maintenance and then they’re ultimately having an intelligent node out on their network and CompactRIO they can put some of that intelligence back into the CompactRIO and do control of the machine as well.
So the value statement here is – or one thing is what do we compete with, it’s an interesting story because they are not really doing this type of monitoring today, this kind of high speed preventative maintenance, they do some portable systems that technicians have, they have some of those, but moving to put device on every machine is new, they haven’t been doing that before, the value they have is to basically – if they prevent one of these failures they save a lot of money, cost a lot of money when a transformer blows up or turbine goes down, or whatever. So this equipment is being justified based on preventing those failures. Right, that’s the goal. And they are having real good initial success, they will be on the keynote stage. Also joining among the keynote stage will be EPRI, Electric Power Research Institute, a collective research institute and power generation that will be talking about this solution and sort of – somewhat endorsing NI approach, they are talking about NI’s approach and the Duke application, so very compelling application, it’s an opportunity in that core space, but we think this represents a fairly generic opportunity outside of just power generation as well, machine condition monitoring, complex analytics, managing lots of data and being able to have software that can run on the back end data but can also be distributed out in the network itself. We think that’s a pretty generic use case that we can – that will see a lot of opportunity. Yes.
Can you put some dollars around this kind of system for us in terms of the dollar content of sensors and do those have to be NI sensors, can you talk about a whole range of CompactRIO –
Sure, I will give you some sense, obviously I don’t want to reveal anything particular to this customer, we get a sense that these devices and plant servers here, this is NI equipment. So the sensors aren’t ours but all the things that are acquiring data from the sensors their goal is to outfit those systems with CompactRIO, so you can equate those number of devices to the opportunity in this scale of an application to that many CompactRIO systems. And you’re talking about CompactRIO systems are 10,000ish dollars depending on how they are configured. And that’s one utility in one particular application space. So it’s a substantial opportunity for us. On the other hand, we’ve heard anecdotes from Duke and others about the cost of the failure, some of the equipment that they are monitoring and it’s tens of millions of dollars for each piece of equipment in terms of the cost of a failure. So the economic justification is pretty clear to them. Thank you for the question.
Okay. So now I want to transition and we want to talk about really the core of this platform and I mentioned this is where we drive differentiation and our business model is really to drive adoption through our software platform and use it to differentiate through the integration with hardware. So to talk about that I want to bring up Ray Almgren, most of you probably met Ray, he is a 26 year veteran of NI and his career has been spent really all around this point of adoption. He basically started our academic program which is a big part of this and he will talk through that and he has been a leader on our software teams for many years. So he’s going to talk to you about the strategy of adoption and about how that differentiates our platform.
Thank you, Eric. Okay. So what I am going to try to convey to you in the next 30 minutes is what we call the science, if you will, of adoption and as Eric mentioned, we do consider ourselves unique in our primary markets of test and embedded in the sense that we are fundamentally a software company that have all of this measurement and control hardware. But the culture of NI, and the business model of NI looks exactly like a software company. But when you think about us, and you think about our markets, you don’t think about us as the software company of measurement and control because we’re kind of the only company that has a business model that looks like a software company. Everything else tends to look like a hardware company.
So a lot of the strategies that we employ at NI as the supplier of these systems looks more like what you would see from an Autodesk, for example, or Microsoft. Somebody that’s really into driving adoption through their software platform. And the differentiation that gives us is significant in the power of our user base. We have a very passionate set of customers of all of our products, but it’s because of the attachment that they have to our software. One subtle psychological point about that is because we make developer tools, meaning we don’t just make the app that you use with our device. We make the tools that the customer uses to make their device. So the attachment that they have to their creation with our systems is much higher than if we just had a device, it would be our product. But in this case the psychology of our customer base is that it’s their product. And we spend a lot of time and effort making sure we can cultivate that and develop that to create this power of the community that we talked about this morning.
So what I'm going to talk to you about is a little bit of the science, if you will, of the software company that operates inside of National Instruments whose singular focus is to drive adoption and loyalty of our software platform because as you could see with what Eric showed and Dr. T showed, we can monetize that through all of these systems and all these applications that our customers are developing. So it starts of course with the LabVIEW message, the LabVIEW technology, everything emanates from how do you make LabVIEW front and center in the hearts and minds of our customer base. So it's not an accident by the way that this NIWeek conference looks like a software company conference, right. It looks like Autodesk University. And what we do at the conference every year is we make sure we feed the community with the features that make them happy.
Now we also have a lot of features that drive our business forward that we’re very careful and if you look at the features that we highlight here in the screen, we’re doing things to make sure we’re driving the business forward through monetizing our systems with CompactRIO, FlexRIO, all the products that we announced but we are also making sure there’s features for the developer community. Things that help them show that they are on top of trends, like for example the mobile. I will talk about that more in a minute but how we can turn our developers into mobile platform developers.
Our larger systems customers, which is critical to the growth of our systems business, we invest a lot in tools and things that you would find from very high performance software development companies. So we add that into our LabVIEW platform as well. On the bottom, you see things that we're doing for the first-time user, the sample projects seems kind of mundane, it’s not really sexy feature. But it's really important to us when we get that first customer it may be a student, it may be somebody who’s brand new to the NI platform, they might have spent the money they did on LabVIEW, it may be a student edition in a $150 on a data acquisition device that connects the USB. We are very focused on making sure that customer has a beautiful wonderful experience with us. So that as they mature in their career they’re able then to appreciate the value of our graphical system design platform.
And then as you saw this morning we spend a lot of time on this third-party community. The ecosystem of companies that build on top of our platform, that's another extreme benefit that we have relative to companies that don’t have a software platform. Because the reality of our market is that there is more IT, more value being added on top of our platform than we can make because of the large number of developers that are adding value. You don’t get that if you don't have a software development platform. The same example that Dr. T talked about with iOS. It’s an enormous ecosystem, that’s very, very valuable for us to be able to do that.
Okay. So the cool feature, the dashboard, so what are we doing here? Well, we’re making – we’re trying to make sure our developers A can add significant value to their systems but also that they can be trendy and hip and be doing the cool things that you have to be doing if you're a software developer. So anyone who builds on our platform is now immediately able to develop applications on the iOS and soon on the Android. And as we showed you we've got tools and capabilities so that you can seamlessly have these really slick user-interface bind to different systems that are measuring and controlling anywhere in the world and even share those user-interfaces. So those are important features that again drive the sense of accomplishment and loyalty in our user base.
So I am going to go through kind of three different areas that we focus on in terms of the strategy at this --to drive this software competitive advantage that we have throughout our platform. So in simple terms, we showed the technical demos of two of these and tomorrow we will show the Duke Energy but it’s these numbers that ultimately deliver the goods for us. The software platform simply drives productivity far and above what you could do with the alternatives. When we look at the market research that we do about our own brand and the own value that we have relative to our peers, the thing that always comes out at the top, one of the most valued attributes that we basically own in the mind of the market is hardware, software integration.
So when you have to integrate all these different pieces of hardware whether they come from us, whether they come from other vendors, we are the company that they most think of to do that. That results in significant savings of time. That's where most of the time is spent developing these systems is getting these myriad of devices connected up through different interfaces and busses and all that stuff. We are the best at doing that. That’s our charter, we try to make sure our software integrates our hardware and our competitors’ hardware for that matter, so that we can be the standard by which people use to integrate software and hardware.
So the development time numbers are significant and our biggest challenge as a marketing organization is getting this message out. Once the customers understand this kind of significant value that they get in their production lines and their prototyping, they are customers for life generally. That's very valuable to us. The other thing that we can do is through the technological differentiation, particularly as we described it with our LabVIEW RIO architecture. There’s things that simply can't be done with any other technology. That LabVIEW RIO architecture, the way it integrates software and hardware seamlessly gives customers, like Hittite, the ability to test in a way that there is simply nothing else you can buy. And that's a significant technical differentiation that we’ve spent years developing.
In fact, I’ve got a timeline here to give you a sense of how long it's taken us to develop that capability. It’s significant. We first debut this LabVIEW FPGA or the LabVIEW RIO architecture at an NIWeek back in 1997. And we’ve been working on ever since and delivering different system platforms along the way, starting with plug-in boards, then when we had the big CompactRIO announcement moving on to last year with the vector signal transceiver and this year with our new CompactRIO taking advantage of the [Zynq] platform.
On Thursday, I am going to introduce a version of that same LabVIEW RIO architecture designed specifically for students so that we will be creating graphical system designers, if you will, in the units of hundreds of thousands every year because they will be able to develop very sophisticated embedded systems at a very low price using the same highly differentiated LabVIEW RIO architecture. So the development that we've done over the years is going to give us sustained differentiation for a very long time in these embedded test and measurement systems that we offer to our customers.
Okay, so let’s talk a little bit about adoption and loyalty. Here is another area where we are going to act different and look different than most of the companies that you would compare us to. This is where we do things to drive long-term adoption that just simply wouldn't be done if we were just a hardware company. One of them is we write software for LEGO, it’s kind of an odd thing, right? LEGO would not be one of your typical customers but it’s enormous brand value for us. Most of our customers, probably many of you grew up with these things, you have a very strong affinity for the brand of LEGO. It’s one of the most powerful brands in the world and we’re able to take advantage of that because our LabVIEW software is what powers that and most of our customers know that and they appreciate that.
It also turns out from a statistical point of view, it gives us access to about 2 million future scientists and engineers, that’s a big number. So every year 2 million kids are programming with a version of LabVIEW and having a really good time doing it. It’s a very, very successful, again long-term adoption plan, something you wouldn't normally think of a company like ours doing in our market. But it’s very successful. Often I think of the [Congress] which would just be horrific for us if we weren’t the software platform for LEGO MINDSTORMS because we’re the perfect software for it. It screams to be programmed in LabVIEW.
Here is an example of something we do - to drive adoption, so there is a very famous robotics competition that’s primarily done in the United States, so there are over 300,000 kids all around the world that are participating. It’s called -- first it was started by the famous inventor Dean Kamen, many of you may have known of him, he’s invented all kinds of medical devices, life-saving devices and he’s devoted his life now to creating and changing the culture to inspire kids to pursue careers in science and engineering.
It turns out that they have standardized on just about every platform we have. The very young kids use the LEGO software and the older kids in high school use our CompactRIO, and we are about to announce on Thursday a new controller based on the Zynq architecture specifically for that program. But why would they value? Why would we be investing in high school? You can’t monetize high school. Well one thing is that – and I will talk about our university program in just a minute. The kind of experience the students get in this competition is unbelievably intense. It's one of the most complicated applications you could ever imagine and it makes you feel good when you see these kids, because you are like, okay, we are going to be fine. If these are the kids that are going to be doing the work of solving the world’s grand challenges we’re going to be just fine. It’s unbelievably complicated.
But the immersive experience they get with our technology is significant and another data point, every team has at least one, often two or three mentors who are engineers working at companies that we do a lot of business with. So again, the brand value of first is enormous. The other very important thing about first is all of the sponsors are first are the who’s who of high-tech companies, and we get access to the C suite of all of them largely through our relationship at first, it’s unbelievable. The access we get through this program. So it’s again part of a long-term adoption strategy and it doesn’t cost us that much money but gives us access that otherwise we would have to do some crazy like run a Super Bowl commercial to get that kind of brand awareness and it wouldn’t make sense for us. First is a good example of how we can do.
Okay. So moving on to the university space, this is another long-term adoption play. So it turns out that pretty much every university and college in the world is using LabVIEW to teach science and engineering concepts. There is kind of a social movement going on in education right now that we can take advantage of. Most of the educators have realized that the route memorization and theory is driving out the future innovators for our industry in droves and they’ve got to integrate some kind of a hands-on learning, if they want to keep students interested in this profession. Basically the engineers have figured out they’re going to have to do marketing. If you want to have engineers stay in the profession. We are the solution. We are the guys that make the stuff that students can easily integrate into a classroom and so we are getting massive adoption of our tools by students who hopefully will go into the workforce and soon be customers.
So we spend a fair amount of time making sure we can take our products and here's the key, we don’t make new products for this market. We make derivative products. We take the same architectures that we sell into industry, sometimes it’s something identical product but sometimes we put a little [façade] or something on it. So we get massive adoption in the university space.
Now we track the efficacy of this, it’s hard as it is in many marketing programs to really track your ROI and how it leads to an exact customer order. But what we can do is track, when did you first learn about National Instruments? At what point in your career did you first get exposed to National Instruments? Since we've been investing heavily in our education program we can see now that we expose a lot of our customers their first touch with us at some point in their education. And when we trend it over time you can see that a larger and larger percentage of our adoption efforts are actually first touch in the university space, and this is really powerful part of our strategy that gets our customers hooked on our platform early on in their career.
Related to that, Eric mentioned the 5G – yes, question?
Thank you. On the previous slides, the numbers you had, so what does it mean 35%, 40% -- percent of what?
Okay, yes good question. So it means that of the customers that were surveyed in this global study that we did, it’s a survey of our customer base. Of the respondents when they were asked, when did you first – how did you first learn about National Instruments? In 2013 it means 40% of the people surveyed said either as an undergraduate or graduate student. So four in 10 of our customers first learned about us as a student.
Okay. So a very important attribute of this adoption is making sure you are connected with the people that matter in research. And as you can tell us we talk about a lot of our applications particularly in embedded space, they often are areas where there's new IP, there's – they are pursuing -- problems that haven't been solved before, that’s a sweet spot for our business, as Eric mentioned 10 to 100K. So a lot of times these customers that come out with this thing started in an incubator or in a research lab, almost every time. And so we have an intense focus on knowing which researchers all over the world are working on the things that most likely will turn into commercial product, and we want to be there with them.
You also have the attribute in the academic world that there is a hierarchy or a tree structure of the number-one professor in certain kinds of algorithm development, creates the grad students and they go to different school and once you can get a hold of that line of researchers you know who to talk to. And so in this slide we are showing some of the universities. These are the ones that are really driving the latest research as Eric said in 5G. And they have all adopted our platform and we have a small group of PhDs at NI whose number one job is to work with these. And so it’s not just in wireless but in other areas of our business that we see as critical to the future.
Okay. So turning that into dollars and cents, what does it mean for us? Well, here is the kind of a high level metric, it’s I guess in some way obvious, but when we look at our business from our customers, those that have adopted our software platform are worth basically 12 times more than those that haven’t. So obviously there is a common trail of business over the lifetime of a customer for adopting. And so that’s why as I said the group that I work with has this intense focus on software adoption -- intense because of the long-term value it brings to our business.
So now a little bit about community, community matters a lot in a software – in a software publisher, getting your fans, your champions and your influential end users is absolutely essential to having a strong base. And in fact, in most software industries, it’s brutal in the sense that there tend to be one or two leaders in a software industry and then it’s hard to come up with the brand name of anyone else. It just works that way because it’s an information economy. And so community matters a lot. All of the good software companies focus intensely on making sure they have the right elements of the community and in the slide you can see here talks about the different elements that you have to have and it goes well beyond your products, the services, the training that you offer, the consultants that you have that are apart of other companies that can be – the experts. You also have as we talk about the third-party products that build on top of our platform that can be used to solve problems that either we don't have the expertise for or it's really not an area that we want to start on, but we would rather invest our software development in another area.
So here are some numbers, it’s probably hard to gauge the absolute relative value of these things to other ecosystems, but it’s a big number, particularly in our industry. In fact, if you think about kind of a hardware only company, their total number of online users is zero. They don’t have a base of these folks that are innovating on the platform, they’re just using the product. We have lots of user groups, this Example program is how we get started and there’s 10,000 instrument drivers. These are software tools for all of our competitors’ hardware – 10,000.
So if you want to integrate a system that has all kinds of measurement and control from anybody, you come to us. Now obviously the tools and the investment that we put into integrating our hardware is differentiated. We like to think it's better. Internally we have these two terms that we talk about. We talk about big eye integration and little eye interoperability. So from a marketing point of view you’ve got to promote little eye interoperability, right, that you are compatible with everything you can run with all the different standards and we do that. We make sure that you can use our stuff with our competitors, that’s very important.
But in the end when they start buying big systems, when the size of the problems gets bigger and bigger, the thing the customer really cares about is big eye integration, how well does LabVIEW and CompactRIO work together, and if that’s done extremely well we get to monetize that business extremely well.
Okay. This tools network is an important part, it’s kind of our answer to the App Store if you will, 175 again might not seem like a lot but it's a significant number. And we work hard to encourage our third parties to develop those, we give them early access to our tools. We spend a lot of time, we help them market them, we kind of give classes on how to do good marketing and how to get your word out and all that, so that they can show their tools to our customers.
Here is just an example of the power of our network in terms of systems integration and consulting. So the first slide shows the dots of where we have NI employees, sales and marketing, engineering but primarily the sales and marketing people that can interact. As you know, we’re mostly direct and so this is how we interact with the customers that are using our products and help them adopt our technology.
This is where all of our third party alliance members are. So you can see that because of this network effect we have an enormous effective sales force for our platform, that’s much, much bigger than we are. So not only do we get the value of the IP that they put on top, we get the value of their ability to interact with customers that we can't reach. It’s a very powerful part of our differentiation and you can see that we have them lined up in the areas of where we’re focused on our business. So we make sure we have the right set of partners that have the expertise in the areas that drive the growth for our business.
Okay. So in summary, we have a very focused strategy centering around LabVIEW to drive adoption. Again what we do is we make sure that, that software is something that they find value in, that ultimately can change their career, change their life in some cases and what it makes possible for them to do and then see that we’re able to monetize it through the hardware. So I will leave you with a chart of our run rate of systems, the measurement and test systems that Eric talked about over the last few years. So in a sense right, while we talk about ourselves as the software company, this is how we monetize it.
These are the folks that after having adopted our software platform start buying the system platforms, the CompactRIO, CompactDAQ and PXI in volume, so that’s kind of the measure to us on the software side is are we doing a good job. Are we empowering the rest of our systems business to get adoption of theirs? So that’s the, if you will, some of the sign I jokingly call this our money ball, this is our money ball strategy. That the software at a lower cost as we can getting adoption and then over here we are winning ball games with the big systems. So anyway, that’s a little insight into our adoption strategy.
So I think lunch is next but if you have any questions, I will be happy to answer them.
As you shift more of your emphasis to larger projects, could you just talk about how you have to shift the marketing message and the marketing resources to make that happen?
Absolutely, that’s a big focus of ours is how do we shift the message, in some sense it goes away from just the features of the products and the benefits of the products to the brand value of the company. And we have to weave that very carefully between the LabVIEW brand which is our most powerful product brand by far and what the National Instruments brand stands for. So what it really means for us and what we’re doing is we're spending more efforts in explaining what’s possible with the National Instruments platform as opposed to all the feeds and speeds of these products and all of the technical features of LabVIEW.
But that's exactly the kind of thing that we have to do. We still have to have that balance, because as I said the software adoption side of this we are hell-bent to get as many souls as we can on to the LabVIEW platform, so that’s still a very broad-based, but we do have to add to that now kind of a more sophisticated kind of NI brand building activity. And as I mentioned, the first in the LEGO stuff helped. It starts to move us into a realm where companies think of us as the major supplier for their systems. Very good question. It’s exciting marketing challenge for us. Yes sir.
And with the different examples you had at the performance 10X, 30X better, you would think that just the customers would be stampeding you like, why wouldn’t that customer then use you, why would they choose to use a competitor with that level of differentiation?
Right, as the guy in marketing that's one of the most painful questions I could be asked is why can’t you get that word out and get people to understand that you get those kind of benefits? Having spent so much time in the software adoption area, I view the biggest challenge in this which again is a function of the software economies is – it’s kind of a religious conversion to get someone to move from their existing software platform to a new software platform, despite evidence that would suggest unambiguously that you could be more productive with the other platform. And so to me again that's why the efforts that we have to drive its adoption to help people understand that they can do it is what’s key.
And it’s hard long into someone's career after they have been using a different tool to get them to switch. The earlier we can get them to understand the power of our platform, the more likely we can get that. It is a tough problem. I think if – it’s simple – I guess every marketing department, just everybody understood.
I gave a specific example I think related to this point. One of the challenges we have is yes, just as Ray said, sort of adopting this platform and learning to how to use it and being productivity and everything else. When we launch a capability this morning that might have seem subtle but it’s a really important and it’s related to exactly this point. We showed how in the past our FPGA based platform has a relatively steep learning curve and so there is this sort of choice the ease of use of a traditional driver that looks like everyone else’ stuff and the flexibility of an open FPGA and that capability that we launched this morning really is, we think, a breakthrough and kind of combining the best of both so the customers can start out of the box with our instruments and it looks like the other instrument. It has a very familiar interface but once they get to a point where they need to add some capability they can do that without having to sort of rearchitect their whole system which is obviously very difficult and increases sales cycle and everything else. So it starts to chip away at one of these challenges that I think we have.
All right. Good afternoon everybody. My name is Pete Zogas and like to welcome you to the afternoon session all of you listening to the webcast, I like to welcome you back.
I have the job to describe how we are building value through our selling channel and how we are adding value to our selling process. And I have been at it for many years -- 29 years and every year at this time at NIWeek, I believe we’re just still getting started. And with me today – I am going to introduce you to two other leaders of our sales team John Graff and Francis Griffiths who are also 20+ year veterans at building our sales channel and have been in this business for a long time. So throughout the presentation if you have any questions for us, we will take them as they come to you.
So with that, let's talk about our long-term growth. This is something that certainly the sales and service side of the organization is pretty proud of, that on one hand, it’s a testimony that customers like the product, they buy the value that we are offering them. And every good sales person wants a value proposition that actually is truth. And when customers adopt the platform they get the value and there's nothing like repeat business, there is nothing like long-term growth and sustainability.
We've been selling to our customers since the early days when I first started the company selling them GPIB hardware and the same customers now are buying PXI. They are buying CompactRIO. They continue to use the software, their graphical system design has evolved from casual systems to very complex mission-critical, and that's what we are doing from selling and service side to keep up with the demand and keep pushing our new technology on to the marketplace. One thing we want our customers to think bigger, we want them to think more about what part of their organizations can they adopt this technology to have transformation, whether it's reducing costs on the operations side or increasing their time-to-market on new designs, being able to validate them sooner, being able to incorporate link the design into validation. These are the -- this is the expensive market and expensive application space that we're dealing with.
Now under the covers little bit on the revenue. We’ve started exposing it to a little bit of color to what's going on in the business, and we have three elements that we point to, one is the high velocity transactional piece of business, typically represented by casual data acquisition, casual applications, if someone is spending $5000 worth of their budget, they build the small systems and they get a return pretty quickly on that. When you start moving into system-level business more mission-critical, the average – the order sizes are going up, the opportunities are bigger. Typically the length of the sale cycle might increase because more of a team is making the decision, and we might have to build a bigger sales team to go out there and service that opportunity. And that's the part of our – that’s the part of the company, that’s the part of the opportunity space that we’re seeing quite a bit of growth in, both on our opportunity pipeline and it’s turning into revenue, and you'll see it in our average order size increasing and you will see it in some of the big wins that we celebrate at NIWeek.
And so this is how it is, this is we split it just to give us the metrics in these three different businesses, less than 20K representing that high-volume, what you don’t see here is the number of orders that we process. So there is roughly 230,000 orders that we process in the blue line, orders less than 20K. And you can imagine how much contact, how much communication exists, how much velocity exists there and then the rest of it is in the order of magnitude less in orders but of course value of the order size increases. And then we started reporting the orders, the volume of business that we’re getting in orders greater than 100K. And these are even higher mission-critical richer opportunities that we are going after.
Now every sale that we do, we sell tools, we sell methods, we sell how-to to our customers. And in most cases the sale cycle can be abstracted to something that looks like this. Where we go out there and first of all we start asking what is their application? We try from R&D and from the marketing perspective paint through these new products, we try and cover all the application space that engineers and scientists can build to solve their grand challenges. So we don't want to leave any application off of our target list. So the first thing we have to do is ask the customer what they're trying to do, consulting with them, what type of sensors, what type of signals, what type of connectivity, the legacy systems that they might have to do in order to get their application solved.
At that point we start doing some product demos. It could be as simple as what we call a three-icon demo, taking a signal, acquiring it, doing some analysis, throwing it up to a software front panel and LabVIEW, and we start removing the risks that they are going to be able to do what we said they are going to be able to do. And in the high velocity casual systems we’re able to do that in a sales call. We can go out there, sales people are technical. They can do a demo. They close the deal, and we have an order.
As the systems business, now with PXI, with CompactRIO as customers turn over to us a little bit of more of their mission-critical applications, they want to see the risks reduced a little bit more than three icon demo. And so we talk about things needing a proof of concept. They might want to buy a pilot, or get a pilot system that’s actually running in their system generating data that they know is truthful and they can do pass fail, critical pass fail or they can actually do some part of their control system with that. And so this is also lengthening the sale cycle, it requires a little bit of a different resource from the standpoint of selling and service, but of course we match that up with the value that the company is -- our customer is trying to derive from it and the size of the opportunity and the margins for National Instruments.
So as we scale the business, our sales and marketing organization is responsible for covering that entire ground of high velocity casual touch all the way to selling at the sophisticated level and making sure we are realizing the opportunity that’s in front of us. If you look at the investment we’ve showed you, we pushed forward on this investment in the field operations and these are the people that are customer facing. They are the ones that are available in the marketplace to do the proof of concept, do the qualification, do the consulting and doing some post-sales support as well to make sure that customers are successful in the end. This is not represented from the total headcount that is in the sales organization, which is also inside sales people who are on the phone that are connected to our website and being readily available to our customers through call centers and casual touch. This is the investment that we have said over the years we need to push more people in there to again service the opportunity that we’re seeing in the system-level business in the higher value opportunities.
I’d like to just walk a little bit through that. So if you look at the two [accesses], and most of the time there is a relationship with that. The opportunity size versus the complexity and sometimes the complexity is in the technical ability to build the application. So you see that under that 10,000 or someone is coming to our website, we have a big investment on the website to help you configure, help you start with your application interest and work through the many different line items that we have in our toolset to build your own system. And then we can -- we have a vehicle for them to actually pick up the phone either, even though the website, make contact with our inside sales representatives so that they can help them maybe determine what the difference is between CompactDAQ and CompactRIO and which one might be better for them to go into that direction with.
And then when you get out into the field we have the field sales engineer. And these are typically degreed engineers with our tools and they can go on a little bit more valuable opportunities and they can do that that demo. And they are linked with the inside sales team because many times the inside sales team is talking to a customer from the web and says, hey, this is – I think it might be worth your time and my time to send our field person out there. And so a typical demo gets placed.
Now when the order size starts increasing, complexity goes up so that demo might increase and also it might get more complex because more people are involved in the decision. They aren’t going to turn over multimillion dollar orders to an engineer or a project lead. They're going to probably get visibility and support from their finance team and from senior management, and they want to connect with our finance team and manufacturing process and our management team and leadership to make sure that we’re going to be in there every step of the way with them. And so we've been building on the sales organization to supplement these roles of the field and the eyes are with business development that might be pointed towards specific application or industries. System engineers, which are basically aging application engineers that get really good at using our products, craftsmen that we can put in to the proof of concept into the pilot phase with our customers. And then senior DSM sales management and finally this is really the area that is the rich environment that our alliance members come into play, because these are solution experts that we also include as part of our sales team to help qualify and close the deal.
So this is really more -- little bit more color on to that investment of headcount that you see. And then in the end, we are satisfying this by building a profitable business at the same time. So our constraints on this almost infinite demand from the marketplace, I mean you see from the keynote material. We can turn a lot of heads through our customer testimonials, through the solutions that our partners and our customers can, we can turn a lot of heads of the marketplace. So it’s almost an infinite demand of selling in how to and support. And so the constraints are our budget, our constraints are we have this much money to spend that will help us build a profitable business so that we can keep investing in new products and in the future of the business.
How do you do pricing and revenue recognition with your alliance partners?
Okay, so the pricing, we try and keep it as simple as possible. So we have with our partners that are buying our product, integrating and shipping, we sell to them for a discount, right and we have discount program depending on lots of things, value add, volume, strategic products that we are trying to promote, things like that. And then on the software domain we have another program for our alliance programs where members on the software side remember that we are dependent and committed to helping them build a very good LabVIEW programming and system integration capability. And so on the software and services side we have a program for them also that gives a very good pricing on our software and then services that they need from our applications group, training things like that.
Do we release it – it’s between 11% and 12% of our business goes through what we call the value added reselling, which is the integration channel. We have another nomenclature for OEMs that typically get embedded in, they get rebranded and sold maybe through another system that's not included in that, that’s 11%, 12% is really what I would call the partners where we engage cooperatively in the market. So the revenue recognition really is just their value add on top of ours.
And we have some cases where we actually will work a deal, where the end user will buy product from us and we will ship it because the partner doesn't [one to one], they want to get in the middle of that, might affect their margins for instance if depending on that. And so this area we have a lot of customers that will buy directly from us and then they will buy the services coming from the partner. Good question.
So with that, I wanted to turn it over to John and Francis to give you their – some of their insights as far as the territories that they're covering and also the experiences that their sales teams are engaged in.
Thanks Pete. Good afternoon and it’s my pleasure to spend a little time with you. So what Francis and I are going to do is we are going to walk through some actual customer applications, we have seen a number of them in the keynote and during Eric and Ray’s presentation but we are going to focus little bit more about just how we deploy the sales resources in order to close the deal. So we are going to take the curve and the information Pete just discussed and give you kind of some specific examples across the range of applications and products.
Just a little background, some of you know me because few years ago I was involved in investor relations but I have been at NI 26 years, variety of roles, application engineer, product management, marketing, operations but for the last three years my responsibility is really our sales oriented functions, including support and operations to serve our customers in the north, central and south America. So with Francis and two other peers our responsibility is covering the broad range of customers we have across the planet.
So let me jump right in, and the first example, I am going to talk about is coming from the electronics industry and the customer is a large global multinational company. In this particular case, their application, they were looking for solution for validating the design of some new radios they were working on, so this would be the engineering, this is kind of the step before things go into production. Now this customer consistent with what you just heard from Ray Almgren has been a long-time user of LabVIEW and our software, actually for 10+ years and so their traditional solution was LabVIEW controlling traditional instruments, box instruments.
Now as we increase the capability of our measurement platform of our instruments, our sales – our local sales engineer regularly goes in, meets with the customer, tells him about new features such as LabVIEW 2013 and during one of these interactions, the conversation turned to – talking about the capabilities of our measurement platform, that conversation turned into an opportunity to do a proof of concept. So in this case and this is kind of what Pete was referring to, the complexity of kind of that initial burden. They knew us real well from the software but we have to kind of prove from a tactical standpoint we could address the measurement needs of their application.
So we embarked on putting this POC or proof of concept together, we used one of our system engineers. These are sales resources that – it’s a limited small number of them but we will deploy to work with the sales team and customer and they put this proof of concept together and again just get over there that kind of tactical barrier and this particular case once we got past that, now the conversation turned into talking about how are you going to fully integrate the system and deploy it across multiple labs? And that’s where we brought an alliance partner in.
So it’s a good example of kind of the steps and again leveraging the software base that we have, working with our sales resources and then the alliance channel, you see on the slide, I mean this was a six-figure type order for this one particular opportunity. But a really key to this was this kind of opens the door to a lot more business in that account. So this is the first time we – as we like to say we got on the other side of the cable, so it’s the software and our hardware platform and this was one particular line of the radios but there is actually hundreds more. So now you can – our sales forces are going to go in there and spend more time and then reinforce to the customer the benefits they are seeing. It dramatically reduced their [jet] time, dramatically lowered their costs.
Next example is coming from aerospace, again a large company, a long-time customer of NI both hardware and software in a broad range engineering groups and functions. And in this particular application, they were facing a critical situation and they have their engineering counsel, their chief engineers came together to address this critical situation, they needed to put together a high channel count data acquisition or measurement system. And they had estimated that, due to the complexity of the system, they would probably take six weeks to get the system spec ordered, and then they would integrate and develop that.
One of the chief engineers who is a long time NI advocate spoke up and said well, I believe National Instruments can help us put the system together in two weeks. So that chief engineer called our local sales engineer. This was a Wednesday evening. The sales engineer pulled an all-nighter who said it was his first ones since graduated from college, to spec the system, put a quote together, the next morning he delivered the quote to the customer. In parallel, he started contacting our production and operations team because to add to the complexity the system was being spec here but we are going to be shipped into Japan. So our operations and production teams started leveraging the capabilities of theirs, started kitting and having those products set aside.
The order came in on Friday. We had already been kitting and actually our production team had already made sure it was set up for transit and we delivered it to the customer on Monday. Now also in parallel, we got one of our system engineers who took the written description of the system and started architecting the LabVIEW code. The customer was going to be doing the development themselves but we just wanted to help them get started. So he created some LabVIEW code to kind of address the configuration they would have delivered that to the engineer over the weekend, and this just helped their ramp and they had the system up and running within 10 days of that original phone call.
This played out the -- our sales engineer team in Asia got a formal award recognition from this customer and the sales engineer back here in the US actually was called in, he was asked to come to the engineering lab and deliver some screwdrivers that we packaged with some of our products. But that was just the route to bring a man when he walked in the lab, the engineering team gave him a standing ovation for what we were able to pull off. It shows you another side of the value we bring but again to put a system together in 10 days now with the selling resources the capabilities of the platform that Eric and Ray talked about this morning.
Third example is in industrial machinery, this customer is a manufacturer of motors, a broad range of motors that go from consumer products that you might see in Home Depot up through larger industrial motors. And in this particular case, a new VP had come in, and as he is responsible of the production and as he kind of audited their production and their test strategy, what he realized is they didn't have a test strategy. What he saw was they had 88 different test cells, which in fact what I meant is they had a different tester for every product. They were getting no leverage, no efficiency, some of these test cells have been built 10 years ago. Others were just cobbled together in recent times.
And in this case one of their managers – again a long time NI customer, an advocate spoke up about the NI’s broad measurement capabilities but also our broad exposure to a range of testing applications. The VP actually asked for us to come in and do an audit of their test strategy. So for two days we had a team that did interviews with their engineering departments, design engineering, production engineering, manufacturing, technicians, management and the end result we gave them a documentation back to this VP where we made recommendations of what we saw as gaps in their test strategy.
Now this wasn’t a recommendation of, oh, you should just use NI products, it was actually based on the knowledge and experience we get working with 35000 different customers where we’ve documented best practices. What we see other leading companies do in terms of standardization of test assets and test resources. Best utilization of your test engineering labor force and we documented these, the VP was really excited about it, in fact, at the meeting he signed off on a $90,000 purchase order that one of those engineering teams had been working, and so that’s like short-term order but you can imagine now through this engagement and through the trust we've built, it’s opened the door to a lot more opportunities as we work with them on as they embark on implementing this new test strategy.
And the fourth example is high-volume production test consumer electronics. And this one I want to kind of address again just the capabilities of our platform. Now often when you hear us talk about production test, you immediately might think our PXI platform and our instruments. This solution actually uses CompactRIO and our single-board RIO and LabVIEW. So most of you might think high volume production line you picture this really clean environment with a bunch of robots moving everything around. But any of you that have visited any kind of high volume production will see that’s not often the case. In this application the customer was going to build what they call a universal tester, kind of a black box device that they would deploy in the production line.
And then the operators on each production line take the device under test, plug it in, it does the test, pass/fail, take it out, put it on a conveyer and they are just doing this again across a high volume – I mean tens of thousands, hundreds of thousands of units. So their alternative for this kind of building a universal tester, the one approach would be to try to use traditional instruments but that was going to be extremely expensive. You’d have to have this rack of instruments at every production line. The other alternative was to do a custom design, build this little black box tester themselves. And so this really demonstrates our platform in that, we took the measurement expertise and knowledge we have, and we delivered a CompactRIO but the flexibility of doing custom embedded design with LabVIEW FPGA and we were able to let them officially and quickly develop this universal tester that they’ve now deployed. And there is over 2000 of these testers across all their production lines, again testing hundreds of thousands of consumer electronics devices. But I share that one to just kind of (inaudible) at times we will sell cRIO into ATE and test and we will sell PXI into industrial and embedded type applications.
So with that, I will turn it over to Francis and he can share a few more examples.
Thank you, John. So good afternoon. Francis Griffiths, I am also a veteran, I look much younger than those guys. So I thought you’ve probably been PowerPointed out a little bit, hopefully this would be a little entertaining but also of interest.
I started off working at National Instruments in the UK and been running the business in Europe now for the last 12 years or so. Just a backdrop to the applications that I am going to talk about, we had a tough test market in Europe in particular, as well documented with PMI and so on. What I decided to talk about here are the four applications that are a little bit more on the industrial electronics space where we’ve seen a lot of good growth opportunities in Europe and the market as a whole. And hopefully I can share with you a little bit of insight into why we’re having the success there in this market in Europe in particular.
And with that said, I think also the markets I am talking about are really global as well. So lot of these opportunities that we have here are either replicated around the globe, or I am talking about global companies. So I think keep that in mind as well. And just one another thing, I think a lot of the – I think similar value propositions that John talked about and differentiate as to why we are winning the business, I would just – you take away a couple of things, the evolution of our sales force, we have developed lot more impactful relationships I would say high level, senior level relationships, now in the years that I have been at National Instrument, I think that’s kind of reached the peak which is an important for us, particularly in these large deals.
And then also the use of our partners, I think you’ve probably heard that theme and through the applications I am doing to talk about have that component. I think the other one to bear in mind is it’s also the fact that we have this high value differentiated platform, it is lower cost, it is higher performance, the measurement performance is really I think a level beyond lot of the traditional incumbents in the industry that I am going to talk about. But also the fact that it’s open, the platform is open and getting lots of data is one thing, but you’d then have to managing data, making intelligent decisions from that data, whether you are talking about a smart grid machine is really important. And there is a lot of value in that back end process.
Our systems are open and that’s really important point, particularly to service providers who do stuff with that data and manage their service. And so I will talk a little bit about that in a moment. So by the way I didn’t mention I am actually based in the UK and I am from South Wales, I am a Wales man. So I am a fellow kelp, got a little bit of the [cultic] but the same as Alex. So hopefully that will help me in this presentation a little bit.
So the first application is in energy and if you were in the keynote you probably saw a little bit of this today. But this – the reason I wanted to talk to you about this application is because this particular account which is a large utility company managing the electricity distribution and this particular account, we’ve done very little business with in the all the years that we’ve been over there. And we actually had one user or couple of years he was using our LabVIEW and our CompactDAQ platform, in this company in a lab. We opened up an opportunity through a reference from this particular user and Pete showed that large base of – or large component at the base level business and I think this is a good example for you to think about how we can leverage those types of users those accounts to grow into something which is really a large piece of business. So that’s one of the reasons I wanted to share with you. As John describes and now we had a field sales engineer go in there take that lead, we had an alliance partner helped us in terms of packaging here and in system engineering, we had to basically prove out a power measurement unit, power quality unit for this utility company.
The reason they need to do this is because as they have more and more different types of energy coming on to the grid, so wind and solar and so on, they have to manage the quality of that electricity. And we with our CompactRIO platform have a differentiated position, you need to make more challenging measurements, that get really good quality for the information from the grid. It’s a distributed system so you have to collect data from multiple nodes around the grid distributed, but it’s quite challenging for these companies, the entrenched players tend to offer closed systems and closed in terms of what you make the measurements close, in terms of the way you manage the data.
So they have a system that they can actually customize their specific needs, the measurement capability that we have the flexibility and then also be able to manage the data in the way they need it is really a big value proposition for them. So we were able to displace through the combination of our partners and our fields proved out to a burden of proof the system and but they are actually right now in the middle of deploying hundreds of systems actually on the grid right now. So it’s a real success story of brand new account, small data acquisition customer that we have taken that to a multimillion dollar opportunity. So I think that's a nice success story and as I said I think can leverage in that large install base, it’s really an opportunity for us.
So another application on the monitoring side, so Europe we typically have quite a good footprint and lot of expertise in trains, fast trains in particular. So we serve a global market that is helping to develop design trains that go all over the world. So this particular customer is a 3000 person consulting company that actually manages and – designs and manages parts of trains, also aerospace systems as well. So now the reason I wanted to talk about this is because we’ve developed a large footprint of LabVIEW developers, very professional LabVIEW developers inside this organization and the reason I bring that up is as our platforms have improved in terms of performance and so on, we need competent LabVIEW program as that can build and manage bigger projects, you might have heard that today with some of the features in LabVIEW 2013.
So this opportunity, we were able to combine the performance of our PXI and CompactRIO into a real-time system that basically allows the customer to test – not just test, to simulate and to test various components of that train, and that's a really powerful value proposition, the traditional system – to give you an example, the PXI and CompactRIO per carriage of the train. So you have a whole series of monitors and you can actually simulate and test all different parts of that train, not just things like door opening and so on but also power quality management and so on that’s going on in the train.
So really quite a challenging project, but when you get a large group of talented LabVIEW programmers is you can really drive down the development time and really lower the cost of that whole process and that’s one of the major value adds for this particular customer. And what’s exciting here is that I think with that size of a team, I am expecting that there is plenty of more opportunity in those types of applications for us. So I think this is a new data point in terms of where we have come with some of these accounts. And again these guys operate globally as well.
So those two applications were particularly on the morning side but you probably heard a lot today about control. So I thought I would switch a little bit, so that’s data coming in and the management of it and so on. So these next couple applications are a little bit more on the control side and this one is machine control and John talked a little bit about I think this type of application and so this company, they manufacture – they are a global manufacturer of turbines, compressors and pumps. And one of the challenges that they had is when you deploy these types of machinery into the market obviously you need to make sure you have the right level of quality but every one of these pumps and compressors has a unique some print if you like or characteristics. Everyone is unique.
Now what these guys wanted to do, the incumbent solution again was a closed system. So it will enable to adapt the measurement platform to the specific needs of all the products that they were manufacturing. And that was a problem because the after service market is – some of these things go down in a wind turbine for example, you have a huge costs on your hands. So investing in the front end of this process in terms of making sure the product meets the spec but then also being able to monitor once it gets deployed is an extremely high-value process that they wanted to nail down. And so we work with our partners’ system engineers actually in an array of different applications in this account.
The reason I wanted to talk to you about is because in the early days of the development of the account, and we have been working with these guys since the – actually for 20 years. We brought them through from our PC DAQ products to our CompactDAQ to our CompactRIO. And if you look at our organization we've gone from in the labs to product development and in the design right through now to the OEM piece of the business. So when they shipped a turbine they recommended supplier for monitoring that turbine is National Instruments and that’s a part number that they give to their end customer.
So we’ve done really good business to date but there is really a big opportunity for us now moving forward because now we are really into the production and deployment end of these guys’ business. So it’s really – it’s a really great account but I see lot of opportunity moving forward to really grow that business and the good news is that as the grid and complexity of that becomes more demanding, it flows down to design of the supply chain, they have to make more demanding in measurements and on the other thing that you probably heard n number of times is that once we go through the burden of proof the expectation of course is that the next cycle becomes easier for us once we’ve proved out our capability in some of these new markets, I think that’s a good thing.
The final opportunity is with wind farms, so I happen to – you have several energy ones here but this is wind farms and this is interesting because this is a company that actually manages the services to provide energy on to the grid and they manage distributed wind farms around the world. So they have a need for good access to monitoring the wind farms looking at the efficiency of the energy coming from those and in order to do that they kind of run about their business model slightly differently. What they decided to do was when you get the electricity from the cell you have to turn that into AC voltage to distribute it, it’s called an inverter, I am sure most of you know what an inverter is, you have to control it, and the way you control it, and the way you can manage the performance of the inverter, the efficiency of the inverter is through a very smart embedded system and that's what this company have done, they have built a CompactRIO system which has really smart control algorithms for the inverter but the other thing that they did which was really cool was they added some really nice data logging software in the box as well.
And the reason that’s important is because the alternative for them was to close box from an incumbent. And the incumbent wanted to charge a premium for the box and the premium for the data and that’s expensive. So these guys, they came to us, we worked with a partner and they actually built the system with the partner, the partner did a lot of ruggedizing of the system for the deployment and they were able to lower the cost by 20% of the capital purchasing and they have actually lowered the cost of the overall service they are providing for the customer by 25%. And that’s why I was trying to emphasize at the beginning here I think the flexibility translates into that really differentiated position for us from a turnkey closed solution but also having access to data is a really valuable piece that we also provide because the system is open. So again this was a really successful leap, we’ve deployed over thousands of these systems since this particular opportunity closed.
So they were the four applications, so now just to leave you with I think in our field our system engineers and our partners I think are doing a tremendous job here in terms of opening up these opportunities and now to close them, and as I said I think our open platform is a real strong value proposition. So thank you.
(Question Inaudible) how do you measure sales effectiveness, you have a very high SG&A, so what are the distinctions you are looking for? Are you looking at number of trials or number of – what are those leading indicators you are measuring and then what do your best sales people do like what are they look like, that’s different from average?
In terms of metrics, the majority of our sales people are assigned geographic territory and will do analysis which is done globally. We will look at a territory and we look at not just the run rate of past business but we will look at leads, we have an opportunity system where the sales force kind of quantify, any of these examples put to them, we will look at the health of that opportunity pipeline. We look at various conversion factors, we have benchmarks in terms of the average and actually we have a lot of data and that lets us then build a coaching model. When we see a territory that’s under potential, because there is lot of leads and opportunities but the close rate is lower, we got to – the manager goes, is it selling, maybe we don’t have enough resource, there is a time where we will look to make sure we allocate the resources properly, other times it’s the coaching or training issue.
Yeah, so your question was, what average of like this is top performer, right? It’s a good question. I think first of all, my immediate reaction would be, I think I am going to brag a little bit here and say average in our sales force is pretty high. Okay let me start there and then I would say, if you look at top performers I think it’s probably similar traits to another sales force, I think in particular we would value [hunting], opening up new opportunities that where you put a knock on the door, be a little bit more proactive in search of the new opportunities. So a little bit like John said, so we try and encourage and help to foster that, develop it a little bit more and I think in my own opinion is I think to some of the top performers I think is going to need skill that they have, is my observation.
The only thing I will add is that we’ve made an investment in CRM tools and we are fairly connected around the globe. Many of our deals span across geographies and span across – so I don’t think but we have quite a bit of visibility in our opportunity database that we can manage resources and put them where they need to be and then on the competency side of things, remember we’ve got sales people where we motivate based on activity, they need to get out there and in front of as many customers as possible, and we need people that are really good at qualifying and identifying opportunities maybe even before we get the customer calling in and asking, we will go right out, take a success story, and a value impact that we had and take it right to a customer and provoke them and say you don’t know that you are having this problem or you don’t know what kind of gains you can have, let us talk to you.
As your sales mix has evolved and has become larger order sizes and do you have a sense as to how much of your customer spend falls into OpEx bucket versus a CapEx bucket for them, is this as simplistic as looking at transactional orders versus orders over 20,000? That’s one question. And then for the bucket, or the percentage that falls into CapEx, how much now is operational CapEx for that customer versus – more capacity oriented, or expansion oriented?
I think in general the order size this is lower -- in general the lower order size is the more probably it is in the expense side of things, the higher the order the more it falls into CapEx, we don't track that ourselves from the standpoint of how we categorize the orders. So I can't really give you a precise answer from that standpoint.
Can you generalize just based on the type of applications, the monitoring asset – kind of asset management versus installing larger test systems which might be more clear cut –
We do. We can’t delineate, for instance, they are buying our products to support the test of a product that they have under development typical capital expense. If we are designed into the system like this inverter control system we are now part of their COGS, for their particular product that they put out there in the marketplace.
Do you have a sense of what that might break down?
Again, 11, 12% goes through the value added partners, so from that corporation or company that’s part of their COGS, right? On the other hand, that’s capital expense for whoever their customer is. I don’t think we can – I don’t have enough information I can to give too much clarity on that. when we go out there we know that we are either talking to their R&D budgets in the organization or we are talking to operation and I think we approach those customers and try and deal with their constraints on both sides, trying to reduce their capital expenditure on the operations when it comes to testing. We know that that’s a cost that they’d not rather not generate but they know if they don't spend money testing something is going to fail in the field and it’s going to be even more expensive, and so they move that cost all the way up to design validation, now you are talking R&D budgets and that typically is less, less motivated by cost over there, they are more motivated on how much of that product can I test, how much of the design can I bring out, I want even more data and you saw some of the examples, some of our value is with our open systems that you - companies are collecting 10 times more data on their design and at the same time doing it for 10 times faster down in production. So any way sometimes in R&D they want more data, that’s typically how we set up our selling and our value proposition is really on which side of the house we are talking to. Obviously in an OEM situation we are dealing with trying to remove their COGS and lower their COGS.
John, a clarification from you, I don’t know if I heard this correctly on your consumer electronics example, did you give us a unit number? I thought that you said 2000 units have been deployed?
In that high volume product test the consumer electronics, yeah over 2000 CompactRIO and single-board RIO, again it’s interesting because in a way it’s kind of like an embedded design, they were building kind of custom box tester in – the volume is because of the number of manufacturer line for that particular device.
And then I guess in the front run, I know (inaudible) probably going to talk about this, but before you guys have to run off to with all your customer engagements, I would love your thoughts on where sales force head count is now, productivity and your ability to leverage that, some things that was clear coming out of your last earnings conference call is that the head count is going to be under scrutiny and some natural attrition, I think [where we can exit the year] about the same level that you exited the June quarter. From your perspective when you look at these opportunities do you have the manpower in place to address them to drive revenue growth even in kind of a flat head count environment in order to leverage that headcount, how should we think about that as an improving productivity trends as you – jut any way you can help us quantify that and what your thoughts are?
As I said we look at our opportunity pipeline as one metric as it applies to how much resource we can apply to it, things like probability come into play. I mentioned it’s an infinite demand, a lot of customers are interested and we got to work with the pace at which they want to make the investment. We are talking about platform changes in these cycles of trying to reduce risk and proving without a shadow of a doubt that they can have a payback is part of where we are applying these head count to. We also have scalability in the alliance program, so by dealing with the constraints of the budget and saying okay, how far ahead do we need to invest, we’re talking about that all the time how far ahead do we invest, you can see we pushed on that in years past. So we have plenty of people in the field. I think for the capacity of opportunities and at the same time yesterday we brought in the alliance partners, we typically do that before the NIWeek, and we get them excited because as much of a market that we are making for our own product, we are making an equal market for services and value add, some of the scale that we can get, some of the leverage in the proof of concepts, and working through consultation we can lean on those partners, so we can scale that our opportunity management that way. One more, time for one more. Or we can just say thanks a lot, it’s been our pleasure.
We are going to wrap up. I am going to talk here for about 20 minutes or so about some of the economic metrics we are looking at and productivity and our plan for driving operating leverage in 2014 and then we will have Dr. Truchard and myself again open up for questions at the end of the session so that we can close it out in an interactive fashion before we move to tours of the trade show floor.
So for those of you that don’t know me, my name is Alex Davern, I am the chief operating officer of National Instruments. I have been with the company since 1994, joined a year before the IPO and you think 19 going on 20 years is a long time with the company but when I stand up here in front of the sales VP you just saw, I think our average seniority within the company in the sales VP level is about 23 years. So you see a lot of long term people at NI and that’s a very good reflection on how we choose to run the business.
If you watched the customers today in the crowd, if you look at their shirts, and I was at the ATCAB, the automated test customer advisory board yesterday and you got customers like Lockheed Martin, like Boeing, lots of different customers in the automotive space. People who want to buy our tools and our technology invest in it and deploy it over many, many years, over 10, 15, 20 years. They want to know if those products are available. If you see some of the developments on the trade show floor and on the keynotes today many of those developments took multiple years to bring to market, to be able to develop new measurement science, bring it to market get it adopted. You heard from Ray today about the academic program where we are nurturing future customers from a very young age to drive the shift in the demographics in our favour over time, that’s not a one quarter strategy, that’s a multi-multiyear strategy to get a very strong position in the marketplace that we can monetize over time.
And the thing they all have in common is timeframe, the timeframe in which we choose to operate in which this market you need to operate if you are going to drive for long-term leadership in this space is one with a significant amount of time. So I will start with this slide here which shows our revenue as the company going all the way back to 1985, even before I got here, so you can see in this trend a number of things, tremendous amount of stability over time. So our average order size right now is about $5000, back in 2004, 2005 timeframe it was more like $2000, but still an awful lot of customers placing purchase orders with us every year which has given us a fairly high degree of stability. You can see consistent growth over time with some interruptions and interruptions have been primarily market-based relative to the broader economy, we saw an impact in 2001 when the technology bubble burst. We continued to invest in that timeframe, we were raising our investment in R&D as a percentage of revenue, took a few years to recover and then from ’03 to ’08 we were able to double the size of the company driving organic growth in that timeframe. A lot of that growth came from continuing to invest in ’02, ’03.
And you see the next downturn that really hit the economy was the great recession in 2009 and I sometimes equate the economic impact on our business, it’s a bit like the grade of the road ahead. Sometimes the road is steep, sometimes the road is downward and we can leverage that and in 2009 road got really steep and I think everybody is aware of the dynamic that affected marketplace. We continue to invest through that timeframe, we continue to hire R&D, we continue to hiring field sales, we made a commitment actually in 2009 at the investor conference this time four years ago, we set out our plan spending pattern for 2010 in terms of driving leverage in ’10 and we went ahead to then when we got to the peak of the road, and the road started to turn downwards and we were able to run a little faster, we saw a tremendous recovery in 2010 in both revenue and profit.
And at the end of ’10, when the PMI was in the high 50s we made a decision for that reason and also for competitive reasons to invest pretty aggressively in ’10, ‘011 and ‘012 again pushing that boulder, at the time we made that decision we didn't anticipate a two year period of time when the PMI was going to be flat, making that road pretty steep, and so that’s impacted our operating margins in this time period. But it’s a little bit stored energy. As we pushed that boulder up the hill, at some point when we get it over the hill we are going to a benefit from those investments, as the road either flattens out or starts to lead to our benefit.
So strategic goals for 2013 are fairly straightforward, we want to sustain our strategic investments in R&D and field sales. As you heard earlier on from [Patrick] our intent is to hold our headcount flat and really from the March quarter through the end of the year, it will go up a little bit in June and July – sorry, in July and August as we go through Q3, as we get a lot of recruiting that we do from engineering students in the summer and will come down through attrition in Q4 and we anticipate finishing the year a relatively flat of where we were in March. We are broadening and deepening our customer relationships. So I would think of this in terms of design wins and some of the commentary that you heard from Francis and Pete and John today relates to design wins that we are getting design-in to now where people have limited budget but you are looking at much broader scale of developments in the future. And it’s a little bit like what we saw in 2009 where we were winning a lot of designs but there may not have been a lot of budget, when the budget came back in ’10, we were able to get a very strong recovery.
We continue to enhance our service offerings and partner network, so as we move up in the average order size and the complexity we are also leveraging a channel to help us service that business so we don't have to change our own channel dynamics too much. And then I will talk about profitability as we get towards the end, we’re going to make a viewpoint on 2014 very much like we did at the NIWeek in 2009 in terms of our communicating our intent and plan for spending in 2014 relative to revenue.
Now Pete showed a slide earlier on, so I won’t belabour it, you see a mix of our revenue growth over time based on the side of the order and it really reflects where we've also been investing our R&D dollars and where we’ve been investing our sales and system engineering resources. And I do want to make a couple points here that Pete made earlier on, the grey and the green bars above 20K, 20 to 100K and above 100K combined in 2012 was about 10,000 orders, so it’s a big number, not an enormous number but it’s a pretty big number 10,000 different purchase orders.
The blue bar represents about 240,000 customer orders in 2012, so just to give you some scale of difference. Many of the stories and the examples you heard from the sales force today, where you saw somebody who was in the blue maybe it’s a LabVIEW customer using data acquisition moving up the value chain as we capture more share wallet of that customer and a very valuable part of that for us right now with our LabVIEW position with our data acquisition position, with our GPIB position, we have access to a very large portion of the markets’ customers. We may not be able to capture a very large portion of their total test spend in the past but as we bring them into the platform, as we bring compelling products out at higher performance we are able to continue to drive market share gains through share of wallet.
I will just spend a few minutes talking about our largest customer and I am sure there is lots of questions about this, so I am free to take them if you like. We tried to show on our conference call last time some clarity around the orders received and the revenue received from that customer over time. In 2012 we had – if we look back at our previous chart here you can see that spike in Q2 of 2012 which is pretty unusual, normally our largest order volume in a quarter comes in Q4 with that year-end budget flush that we normally see especially in Europe.
Last year we saw a spike in Q2 heavily led by orders from our largest customer and then from an order point of view you see the number gets quite a bit lower in Q3 and Q4. From a revenue point of view, that orders from that customer turned into revenue in Q2 and then especially in Q3, so we had a pretty tough comparison from that customer in Q2, we will have an even tougher one here in Q3 and that compare gets quite a bit easier as we move forward.
Now as I have talked to many of you before, this customer we serviced in 2012, we were servicing two applications for this customer, we were designing, believe that we are the only vendor servicing those applications, they went through a major ramp last year in production in the summer as they deployed that technology across their product line, this year they are buying incremental quantities of volumes increase. So the volume of revenue we see from those two particular applications in 2013 is quite a bit lower than we did in 2012. We still believe we are the sole source supplier to those applications.
Now I am going to talk a little bit about the PMI and how the various different order categories relate to the purchasing managers index. Those of you who are not familiar with it, it’s the global PMI that we use and when it’s above 50 it means the global manufacturing or global industrial production is going to increase and when it’s below 50 it means is going to decrease. And you can see the recession in 2001 I talked about earlier on, you can see the great recession and I apologize that the years are not showing up but that big dip (inaudible) towards Q1, that’s Q1 of 2009, Q4 of 2008 and you can see a recovery and we’ve had this period in the last eight quarters when the PMI averaged at 50 which means on the essential terms there has been no growth in industrial production globally for the last two years. That’s obviously affected by a big recession in Europe, weakness industrial production in Japan offset by some growth in the emerging countries.
Now I have a personal theory but this is a theory or hypothesis that the longer it’s at flat, the longer it’s at 50 the tougher it gets for those people who supply capital equipment because customers get progressively more cautious. Now some of the data points we have seen, in the recent month or so have looked a little bit better but we are going to want to see significant period of time, multiple months of stronger readings before we will get confident that the PMI itself has delivered some form of sustained rebound. We did see a fall back obviously in Q2.
If you look at it relative to our various different order sizes we start with orders under $20,000 who were most deeply penetrated, this was about half of overall revenue. You can see a pretty strong correlation. We had in orders between $20,000 and $100,000 you can see there is also a strong correlation but at a different level, we have been able to grow that business quite a faster and we have invested in that over the last period of time.
And then when we look at the large orders over $100,000 we call this the bed of nails. So it can be a little bit volatile and it’s always been a little volatile. And you can see Q2 of last year we were up 135% in that category. That's what fermented a very tough compare, not only from our largest customers but we actually had three pretty large customers placed orders in Q2 of last year, which compounded on top of each other a little bit. And you can see four quarters later in Q2 this year were down 3% and as you know if you’ve ever dealt with sales when you look in a quota, the first thing the guy is going to look at is what he did last year in the same time period when you are setting quota for this year, it has a big impact on your year over year growth perspective.
Now on a two-year timeframe, our orders over 100K are up 60%, so I don’t want that to get lost in the mix. So over a two year time period we’ve seen a significant growth in that category, obviously the numbers are a little bit skewed by the results we saw in Q2 of last year. As we look forward we're going to be very focused on driving operating margin in 2014, as we talked earlier on I believe we have done a significant amount of investments and pushed that boulder up the hill and I do believe we will see a period of time when the slope of the hill changes downward, perhaps soon but we want to wait and see how the PMI fares out before we get confident of that’s what we are going to see.
Now the other challenge that where we can reflect on the challenge is take a look at what’s happened in the market. And as I have done here for many years we will compare our revenues to the core public T&M companies that we have data for. The one exception here is Rohde & Schwartz, RMS, it’s roughly $2.5 billion European company, it’s private but they do publish the numbers once a year, about a year. So we do see their numbers on an annual basis.
When we take a look at this market, the bar represents the aggregate revenue of all of these companies, that does not include our revenue and over the last five years after the downturn and recovery this market’s essentially been flat, it’s up about $100 million over the last five years. In that same time period we’ve drawn our revenues about 55% or a little over $400 million. So from one point of view we’ve captured roughly 80% of the market share, that’s been available in this market over the course of the last five years. From another point of view, this market has been flat for five years. So it’s been a difficult market space in which to grow, we've managed to drive a separation between ourselves and the market that’s somewhere in the 10% growth points per year over the last five years.
Now if we look at what’s happening in the first half of 2013 I won’t get into all the numbers, but when I look at the same sort of players with the data we have available my guess on what’s happening with this number is there is roughly minus 14% for the first half of 2013. So that PMI has stayed weak for a long period of time, we are seeing a tough market in our space and it puts our differential at plus 6 for the first half roughly at about 20 points. So I think we are pushing the boulder up a fairly steep hill in this timeframe and we are going to look for broad macroeconomic change before the slope of that hill is going to change in our favour.
Now in terms of driving leverage everybody I think is very familiar with the decision we made in the fall of ’10 from a recruiting point of view to be aggressive and adding talent to R&D, where we felt to be three to five year return in 2011 and adding talent into sales and marketing where we felt the return would be closer to two years, which is right about now. And we made those decisions at a time when the PMI was higher, some of it for competitive reasons, also a desire to really realize our vision and drive forward to capture the opportunity that we believe is in front of us.
We definitely forward invested in both these categories, and I believe that we will be able to drive growth by keeping our headcount relatively flat for the next 18 months or so and using that as a platform to drive leverage. So I think we made the investments that were necessary to be able to accelerate our roadmap and in this time period we want to leverage those investments as we move forward.
Now to put those investments on a relative scale in terms of our ambition and our expectation as we move forward, we can take a look at how the industry has unfolded over the last decade or so in terms of relative investment. And we look at those same set of players where we have data, and you’ve got Agilent in green, you’ve got Teradyne in the orange, that’s kind of in the middle and the CNI and we have data for other companies as we’ve got a little further on in time.
And over the last decade or so we've gone from a situation where we were relatively small player from an investment in R&D to one where we are now competitive in comparison to the largest companies in the industry and you can see Agilent’s business is a little over $3 billion, Danaher through acquisition of Tektronix and Keithley and others has roughly $3 billion business here, Rohde & Schwarz is about 2.5 billion, Teradyne is somewhere in 1.5 to somewhere to $2 billion. So they’ve got significantly greater revenue than we have at this point in time.
We believe that this market is very ripe for disruption. We believe we have access to a large number of the customers in this market space. We believe we have very differentiated vision of software position and we believe that over time we will be able to move people up the value chain of NI tools and be able to capture a greater good of this market.
That’s the forward looking statement, I am sure general counsel would like me to caution you, that may not prove to the case there is risk in investing but that’s what we believe and that’s what we have been able to deliver over time.
Now if we take a look at some of the benefits from our investment, and we look at revenue from products released in the last 24 months and this is from hardware products, we don’t [carry count] new versions of software. And it gets affected by the economy as well, and as the PMI weakened in ‘012 or as it weakened in ’09, we saw some impact on that number. As we look at the first half of 2013, despite a weak economy this is a key that’s been allowing us to broaden our separation between our results and the market over the course of the last 12 to 18 months, we just launched a number of new products at NIWeek last year, that have been very, very successful.
As mentioned by Eric this morning that the VST, the vector signal transceiver is one of the single most successful products in the history of the company. Unfortunately it doesn’t all shine right through on the topline because we have been dealing with that steep road that we are trying to push our boulder up. And that’s been part of the challenge that’s held back our performance. But if we annualize what we saw in the first half we do expect to see an all-time record in terms of revenue from new products released in the last 24 months in 2013.
From a gross margin point of view, we may take in great pride over many, many years and I think the model target of 75% or 76% of gross margin was set by Dr. T I think back in 1989 – ‘87 excuse me back in 1987, and this is one of the most boring gross margin curves you would see yet obviously we have been very excited by even a 1% move because we all understand the leverage that there is in that number. Now we've gone in this chart in 1993 instrument, we were probably I am guessing here less than $100 million in revenue and instrument control was probably about 40%, 45% of our revenue. Now we are well over billion dollars in revenue and instrument control is about 4% of revenue, we have been able to sustain that high value market position for a very, very very long time.
Now we did see a dip in gross margin in Q2 related to a particular application for our largest customer. We’ve obviously guided to margins recovering significantly in Q3 and we believe that our overall margin picture will be very stable as we go into the longer term. So we have not changed and don't intend to change at this point our target model for gross margin over the long term. There are occasions when you are a disrupter and you’re in disrupting a large market earlier on when the competitive dynamics is going to get relatively fierce and stay that way for a period of time. We’ve seen this many, many, many times, as we disrupted different markets and so this will be a topical thing that will come and hopefully go out pretty quickly.
Now from an operating margin point of view, and I know there is a lot of interest in the room in this topic, we made decisions post to the tech bubble burst in ’01 to drive a big increase in investment in R&D that allowed us to double our revenue between ’03 and ’08. Coming into 2009 we saw the rapid impact of a downturn in the economy at that time, you guys understand high gross margin with a lot of fixed cost, profit is very sensitive to revenue. That’s the way the model works. The form was pretty easy to understand.
Coming into ‘011 and ‘012 as we made some significant investments that I now believe we can reap the harvest from, we saw a reduction in our operating margins as the PMI fell off. And here in 2013, with a top compare and a difficult market we’ve seen our margins being impacted in the first half. Looking out to Q3, we expect our operating expenses to be flat in Q3 basically we gave guidance to you – to be down in Q4 and if we see our normal seasonal pattern of revenue we believe we will see a significant recovery in operating margin in the fourth quarter.
Now the question everybody is also interested in is what is our bias and our intent around investment in 2014. A very similar to when I stood here in August of 2009 and we gave guidance on our spending plans for 2010 and 2011, we laid out a relative plan and so our investment profile for 2014 will be dependent on how we see revenue unfolding in 2014. And we’ve offered a variety of scenarios here to try to calibrate people in terms of expectations. So you can fairly understand the intent of management.
Now depending on the PMI etc., we will see a variety of different outcomes. Depending on the success of our new products we will see a variety of different revenue base outcomes. Our intent is pretty clear from this slide which is to drive a lot of operating leverage in 2014 to see a good strong recovery in our operating margin in 2014. We’ve executed against this sort of plan before, very successfully in 2010. It’s well understood across the whole company, there is a real I think deep understanding internally that we've made these forward investments that have positioned us very, very well and now we intend to reap the reward as we move forward and try to drive leverage but the scale of that leverage will be relative to the broad macro environment and how our business is performing in that environment.
So with that, I will close, just to reiterate our intent -- continue to sustain our investments in this time period, next year is going to be a year for management we’re very focused on leverage, I think we've got a tremendously disruptive innovative platform. I know how excited our customers are about the potential and I personally am a strong believer that we will be able to drive long-term revenue growth for NI and we will be able to leverage investments we’ve made up to now to improve our operating margin performance.
And with that, I am happy to take your questions.
I guess I have a question in looking at the order chart, it is pretty obvious that you’ve had a tremendous amount of success in the large order sizes. Can you talk about why you haven’t had more kind of year-over-year kind of CAGR growth on the smaller blocking and tackling as your market opportunities have grown and your product has proliferated?
So it’s a very good question. The question is why the CAGR as you look at the smaller buckets of orders if you like has been lower. A couple of reasons for that. One, this is an area where we’ve had a strong market position for a very long time. So we definitely have a far greater market share in the activities that are involved at that transactional level than we have as we move upstream. That’s one of the reasons. That reason is a very large broad volume of business and so it tends to be much more sensitive to what’s going on the broader economy. The market share gains for us is not only obviously to drive more users at the broad based level over time but the rate of growth there is probably going to be below the company average going forward. And then to monetize that user base as we move upstream.
Would it be normal to have big orders and kind of new opportunities lead to the smaller like trickle down in terms of order size?
The majority of the time it may go the other direction.
The only time you’d probably see that is where we get – we have site licenses for our software, then you will see the order – smaller orders. But generally it’s the other way, we’ve got lots of data showing that if we get an order in a data acquisition board, then in the future we have a better chance of getting larger orders.
Just understanding that the revenue is a huge portion of driving future operating leverage. One thing that I thought was obviously excluded from this NIWeek, probably related to last year to your $2 billion revenue target. It wasn’t mentioned at all during your presentation. So I am curious what is the timeframe, last year I think you said 2016, you thought that that was a reasonable timeframe to achieve $2 billion in revenue?
When we were at our NIWeek in 2011, we set out a goal and the goal was on the assumption that we would see the global PMI be at the average of level that it had been over time which was 52.5 roughly and under that circumstance we expected to reach about $2 billion in revenue by 2016. When we talked about last year obviously at that point in time we have seen a full year with the PM flat, we made the comment at NIWeek last year that’s going to delay the realization of $2 billion in revenue some period of time. Now for the following year for the last 12 months, we have seen it to be flat again, and so as a macro proves more difficult for the market it is pushing out our timeframe of the expectations of hitting $2 billion. I personally believe we are well-positioned to achieve the goal but I realize quite clearly that the timeframe is going to be dependent somewhat on the macro. So I am not really willing to commit to a date at this point in time.
And then I guess as we think about National Instruments’ long term growth rate, and that’s why I was wondering about the $2 billion revenue side, but historically your company has grown at double digit type of year over year CAGR, in 2012 we saw you slipped under double digits, still a good year especially given the macro, I guess I should have paraphrased the question, understanding that you are gaining share and understanding that we are in a tough macro environment, but that being you had one of your best product announcements or releases ever, still grew 10%, this year arguably we are looking – we are tracking probably low single digits. How should we think about your long-term growth rate, are you still a double-digit growing company, do you think you are poised to accelerate given some of the opportunities that you talked about in embedded or should we think about as you get to the scale that you are at that you should be slowing more towards the T&M type of growth rate?
I will give a short term answer and then Dr. T can share the visionary view of the world. It’s like Einstein said everything in our view is somewhat relative and as we look at our performance over the previous five years and I look at our performance in the industry is roughly about 10%. My personal view is as we’ve accelerated that gap here in 2013 but the market’s gotten quite a bit worse. My personal view also is that this tough market for T&M is something that probably is going to be relatively difficult for some period of time. So I personally wouldn’t be surprised to see the test and measurement market overall be in the low single digits, for some period of years. I do believe we can well outperform that business, so I think we absolutely have the potential to be a double-digit revenue growth company as we move forward. But it’s conditioned on the macro to some level.
So I think the issue of what the general economy is doing is a major one now and so part of the answer has to be when will we see a better economy (inaudible) reality and circumstance. As Alex mentioned we’ve seen some of the biggest split between how we have performed and the industry has performed. We serve the industrial industry, so it’s – as test and measurement has been a really challenging time I don’t fully understand, I don’t know if Alex why it has been a challenging in the general test and measurement business as we have seen. Now as you saw in my presentation we have been working to expand our role with a platform and platforms can be quite powerful and quite successful. So as we go forward and gain scale in these new areas, hopefully we will see the benefits in terms of that growth rate.
Alex, if you could comment on the recent economic numbers, I mean the US ISM new orders number was like 58, I know you guys look at the global PMI but when do we decide it if we are in a better economy or not?
Well when I saw the US PMI number for July which I am sure many people have seen here –the single greatest sequential jump in one month since I believe 1993. When I look at that number I love that number. If that number prove to be sustained over time we are going to see I believe a strong – strongly sloping road in our favour in the second half of this year. I would caution though in my experience in these things has been one month’s massively outsized movements tend to be volatile. So I am reluctant and I look at the automotive shutdown, the PMI is seasonally adjusted number, there is a real change in the automotive industry this year in terms of not shutting down in the summer. So I am going to be anxiously awaiting the August number in the US to see if it’s sustained at that level. So I am a little bit sceptical that the strength of the PMI in the US in July will be sustained through September. He uses every opportunity to make sure he’s leveraging resources.
If you look at the mix that goes into computing, the global PMI, is that compatible with your mix of business or can we look at it as if the US starts to really work versus Asia or Europe, could that be a better indicator by looking at the separate components?
Yeah certainly geographically mix it makes a difference. The way the global PMI is done is based obviously on industrial production, weighted as you look around the world. In an economy where the bulk of their industrial production is agriculture we’re not going to be that correlated to US. Over time has proved pretty correlated with our business in the US. So I would think our results in America have been highly correlated with that number over time. So we will see how it plays out. Nobody would be happier than me to see the PMI number for July carry through the rest of the year, but I would also caution you not to be shocked if it happens to fall back in August.
I just wanted to ask you about the operating leverage, for those of us here putting together long term models, are there reasons that we shouldn’t extrapolate this out 3 to 5 years could see similar operating leverage over a longer period of time – just the one year you were talking about on your slide here?
So ultimately that would be a trade-off between growth and profitability, obviously if we carry this leverage number on forever we'd end up with a really high profit number and probably sacrificed a lot of growth. So you take this guidance as a 2014 intent, now when we look at 2015 we are going to be very conscious of our goal to hit 18% operating margin and so we will review where we are in ‘014 and making our plan for ‘015 but I would not extrapolate this guidance out beyond 2014.
Alex, again on the OpEx, so you referred to 2010, and your goal to get back to 18% really leverage that, I think a lot of us are surprised at how quickly you turned from that 18% goal and just ramped spending significantly. So I think I talk to investors a lot (inaudible) if you said that, but is that going to happened over 18 months or is it going to reaccelerate to a large degree again in six months if the PMI does hold up fairly decently and you do get some extra growth that you were planning on in 2014, so just how do you ’08 fears that this is not going to happen?
Obviously we are not giving guidance at this point to 2015. So I maybe answer the question in more general terms. When we were making the decision to ramp investment in the fall of ‘010 and into earlier ‘011 we were doing in an environment that was very different than the environment we have ultimately turned out to think. And I don’t think many people – certainly when I was looking at GDP forecast and PMI forecast and everything else I don’t think anybody was forecasting what’d happen for the next two years. So it’s a little bit of a lesson learned – I was too optimistic in that timeframe relative to how the economy was going to fare out. And as it turns out, I should have been a little bit more cautious. And so as I accumulate more white hairs over the years, I would probably be a little bit more cautious next time around.
Secondly, we also are in a situation right now where I think our capability with 2100 people in R&D is relatively un-paralleled in the industry. So we’ve reached the point at where our ability to drive innovation I think is probably greater than any other company in T&M in the world. So from that point of view our need to be able to drive future investment is significantly I think less than it was 3, 4 years ago. So I think we are emerging as the leader, it may take a while for it to play through the revenue but I think we are really well-positioned from a capability point of view. Perhaps Dr. T can talk a little bit about --
Certainly my view is that we need to focus on the effectiveness of the investments that we’ve made, so I am definitely focused on that, I hope we do go to a pattern that we’re historically waiting to see the revenue before we get too aggressive but that’s my goal is to do that. I do believe we’ve got a good solid resources on board and can be very effective in getting a R&D, sales and marketing done.
Were there lessons learned from this last ramp in head count and investments are going to be more effective than what you have done -- (Multiple speakers) better metrics than you had in the past, and more better visibility in what ROI could be --
We are learning every day and certainly we will learn the lessons as you go through an expansion like, you are going to try some things that do work very very well and some that don’t work very well. So we want to take those lessons on board and always be more effective next time around.
You guys talked about the cloud a little bit earlier and I am just trying to little bit better from a product perspective, are there specific do you see as the driver or is it just something you have to enable within your products to leverage data in the cloud or little bit more on that would be great?
Two things, one, we are looking at the products that we can create [as specific to that]. Secondly, we have some products that really will be enabled, we have had [DDMs], since we acquired a company in the late ‘90s that serves the automotive space and has gone into other manufacturing areas. It’s about big data. So big analog data, so we are well positioned to get benefit from the products we have and also the ones we can create that enable big analog data.
And for many of our customers in cloud will be an internal cloud that they will manage it themselves as well too, given the nature of the data, utilities are not likely to put their analog data on an external cloud.
A perspective you can take is we’ve always leveraged generally available technology and this becomes a new [fad] of generally available technology and their special products that can go with that.
If that’s your last question, I am going to close by thanking all of you who came to brave the 104 degrees in Austin, Texas. So thank you for doing that, for those who have the opportunity there will be a great keynote tomorrow, the Duke Energy application in particular will be highlighted. So if you are looking for how we have growth opportunity I think the keynote tomorrow would be a very useful exercise. And again thank you for your time and we hope to see you tomorrow.
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