All right, everyone. This on? Okay, good. Well, thank you again for joining us here in San Diego, Teradata's new headquarters. I'm Gregg Swearingen, investor relations. We have a good number of analysts here in the room. We also have a number on the webcast. The webcast is being replayed, so you can go back and review that. It'll be archived on the website at teradata.com. I'd like to direct your attention to this important information regarding forward-looking statements, as well as non-GAAP financial measures we'll be discussing today. Our discussion today includes forward-looking statements that are based on current expectations and assumptions. While these statements reflect our current targets and beliefs, they are subject to a number of risks and uncertainties that could cause actual results to vary materially. The risk factors are described in Teradata's filings with the SEC and on our website.
During today's presentations, we'll also be discussing certain non-GAAP financial information, which excludes special items such as stock-based compensation expense. We will also be referencing other non-GAAP measures such as free cash flow. More information about these non-GAAP measures can be found on our website. First off, this morning, Victor Lund, Teradata's President and Chief Executive Officer, will provide his perspective on the progress of our successful transformation. Oliver Ratzesberger, Chief Operating Officer, will then provide an update on our strategy, followed by Reema Poddar, EVP of Product and Technology, who will provide an overview on our new Teradata Vantage. That's our new analytics software platform for pervasive data intelligence. Stephen Brobst, our Chief Technology Officer, will then come and talk about some real-world customer activity. Following Stephen, we'll take a break.
Mark Culhane, CFO, will bring it all back together from a financial perspective and provide our targets for 2021. We will then provide an opportunity for a good healthy amount of time for Q&A. We expect to conclude the meeting by or before noon, so we know you have a number of you have flights you're trying to catch. With that, I will turn it over to Vic.
Thanks, Gregg. I tried the T-shirt thing, but so as you get older, you shrink, and it's true. All my grandkids are getting taller than I am. This thing that appears on my side is not a fact that I've gained weight. It's just that there's a compression that occurs in the body, and I don't feel comfortable in the T-shirt, so I'm not going to wear it. I think I don't feel comfortable in a T-shirt. You got to see me in the morning when I get out of the shower. It's real ugly. I won't look at the mirror anymore, but that's another story. I'd like to welcome you all. Thank you for being here. Those of you that were here last night, I hope you got a sense that this is a new Teradata, one with enthusiasm. We got a plan. We're going forward.
We're excited about where we are. We're confident in what we're doing, but not arrogant as we move forward. New digs we've got, I think, reflect our change in attitude around here, and I hope today you get a sense of that. It's just been a little over two years, since we did this last time. I was new at the time. At that time, I set out two goals for myself. First one was to build a management team that could drive Teradata forward. The second one was, with that management team, to drive a strategy that could build momentum to have a sustaining and growing valuation for Teradata, the best thing for our shareholders and for our folks. That was my objective. We at that time introduced the start of where we are today, and at that time, we had a strategy.
That strategy was around mega data companies, the large companies who use and generate a lot of data. We introduced at that time Teradata Everywhere. Teradata Everywhere was our first thing where you could move software across anywhere. It could be on-prem, in the cloud, wherever you wanted it, provided benefits to our customers of being able to place a bet with not having to figure out where they were going to use that bet. Further, that was the first offering we had ever had as a subscription, and that's the only way you can buy Teradata Everywhere. It has to be bought on a subscription basis. I think from the numbers you have seen, we've had traction on that. The other interesting thing about Teradata Everywhere was it was the first time we talked about the ability to buy software separate from hardware.
We started talking about where we were in that. The third element of that strategy was we were going to build this consulting organization that was going to go out and develop apps and then come from the outside in to drive consumption of Teradata in our customers. We announced that, and at that point, I started also building a team, and I think we've had great success on that. Those of you who were there last night and got to meet all the folks that were there, I think you will agree we've got new folks. We have nine people on the LT. Five of them are new to Teradata, and the four that were at Teradata when I arrived here are all in new positions.
We've used those folks together to figure out where we need to go from now, where are we, how do we drive outcomes. We took what we knew. We went out and engaged with our customers. You've all heard me say on calls and everything that I think the key to any successful company is they have to know what their customers want, and that's what they have to deliver. I think the tech world is fraught with people who go out and find a great technological solution, and then they go search for a use of it, right? We've done the other thing, and that over the last two years, that journey has led us to where we are today.
When we got with our customers, we found that we had these mega data folks, and the bulk of them are very large companies, but some of them are growing and coming aggressively. They all have some key characteristics. We picked that set for a reason. When we go out there, the first thing is, like I say, they're huge. They've been around a long time, right? They're massive companies, or they're very complex companies. Take your pick. The other thing, it's a characteristic of all of them, is they generate huge amounts of data, and it's growing exponentially. The third thing is that they have these very complex ecosystems. It's grown over a long period of time, and they got one of everything, right? Maybe four of everything. It's across there, and they're having a hard time figuring out exactly what is all the stuff.
I was talking with a new chief data officer of one of our customers. We just expanded our presence with them, and this was an individual who had run half of the world for this business. He wanted to come back in and deploy data against the business. He thought they could do a lot better job, and his first task was to find out how many data instances they had, and they had well in excess of 5,000. That can include a laptop with Excel on it and all that, but even in that case, it would fed into the corporation. They've massive amounts of data, and it's growing. Very big problem for all of them. The next thing, being big companies and most of them being public, they're very interested. They have to drive earnings. They have to drive revenue. They're very risk-conscious.
Cybersecurity or the risk of missing what they've told the street, they want to control the risk that they have. They also are interested, particularly in this environment, in controlling costs. How do we expand and become analytics without a massive increase in our cost structure? The other thing, and I think in life, you can be super smart or you can be lucky, and sometimes having both is a good thing, I think we introduced our strategy at exactly the right time. These customers have been down. First Hadoop showed up, and it was going to be the answer, it was going to be the silver bullet, and then the cloud was going to be it. Before that, it's been a lot of things. At the end of the day, our customer base understands there are no silver bullets.
This is a process that has to be taken on. It has to be worked through. It has to be approached in a thoughtful manner. You have to demonstrate results along the way. That's where we get to our new strategy, Vantage, that you're going to hear about today. Vantage focuses on that. We spent a lot of time trying to figure out how do we deal in that environment and how do we help our customers succeed. We know that our customers' success drives our success. If we don't help make them successful, we won't be successful. It's key that's built around that. The other key difference that you'll hear today is consulting is now focused around driving our product from the inside out. Vantage is in there.
From what you saw two years ago, that's going to have the main implication for everybody in this room is that you're going to see our consulting revenues are down because we're not chasing all the consulting stuff around the world. There's a lot of stuff to that. Consulting is a key part of us, we want to deploy our smart people in a way that makes our platform better. That's what we're using. Wherever it is, we need our consulting people focused on our strategy. While it does mean the consulting revenue's down, actually, our product mix and everything is much better than it was two years ago, and actually, we think creates a higher valuation for our shareholders. At the end of the day, it's the share price, not the revenues that matter, and we think that's exactly what this strategy does.
I'll be back at the end to kind of summarize. Again, I want to thank you. I hope you sense the energy and enthusiasm we have around here. We are excited about where we are. We think we have spent enough time with our customers that we actually have found a holistic approach to the problem of analytics, and it's more than technology. In fact, another point solution is the last thing you need when you already have 5,000 data instances in your organization. With that, I think we're going to roll a video, and then Oliver will follow it. Thank you all for being here.
We have a brand promise that we should be designed around you to make life less complicated, but also protect you. The mission is to focus on our core values being quality, safety, and environment. We try to gather data on both our customers and also from the vehicle and how the vehicle is being utilized. The cars need to have the help to be able to be autonomously driven. For autonomous drive, you need a lot more detailed maps and real-time updates on maps when it comes to obstacles in the road. If the vehicle detects slippery roads, it sends a signal up to other cars with this functionality that are coming into this area to warn them. More and more features in the vehicle will depend on the connectivities.
Ultimately, we hope that we should be this sentient enterprise to be the one that could provide new feature and continue to develop models and provide new business opportunities for both ourselves, but not least, the customers of ours.
Great. Good morning, everyone. Thank you for coming to beautiful San Diego. I hope you see a very different Teradata today than you saw for those of you that were here two years ago. Part of it is the work environment. A big part of it is our people. Before I start, just one little fact here. We just got voted by, in large part by our employees, as one of the top workplaces in San Diego. That was not the case just a few years ago. This campus was very different. The energy in the room was very different. It's a big part of our transformation is to change who we are and do it with our people, you've seen the branding that we have launched this year that has been driven by our new CMO, Martyn, who is also with us here today.
There's a lot of change happening. What I want to take you through is the essence of what our strategy is and what we are seeing out there and what's happening in the world of these very large
Mega data companies, the top 500, how we have referred to it over time. As I do so, I want to take you through one of these conversations, Vic just gave you a little bit of sense of that. These are conversations that are happening at an increasing frequency. Us having conversations with C-level executives of the largest companies and getting their perspective of how they need to change their companies. The last 15 years or so, with the advent of open source, with a lot of new technologies, with a lot of choice, has gotten a lot of companies into that state of, like, let's adopt the best-in-class, so to speak, technology for every problem that we have. At least that was their belief, right?
For every new problem, another team in the company found another technology that supposedly was better than any other technology that you had before. What it has led to is that executives are now facing these problems of, you heard 5,000 data silos within a single company. That is not a one-off. That is in every bank, in every retailer, in every telco, in every car manufacturer that we walk into. That's the scale of magnitude of a problem that we have. It has made it into the boardrooms of these companies. In fact, I just, two weeks ago, saw the top five goals of the CEO of one of the top two banks in the United States, and the number two goal on there was simplification. Simplifying the business model, simplifying the technology infrastructure, because it has become unsustainable from a couple of dimensions.
First of all, if you operate that many instances of technology, you are tying up thousands of headcounts. You're quickly spending billions of dollars a year to operate that. Another bank in the U.S. has 800 risk systems running, 800 instances of risk modeling, it's becoming increasingly expensive to spend $2 billion a year on this kind of problem. It's making it all the way up to the boardroom for multiple reasons. First of all, in a world that is driven more and more by efficiency and operational excellence, obviously, there's cost pressures that companies are under. The whole problem of cybersecurity, which is getting bigger and better by the day, is taking risk at the various boards to an entire new level.
When you have that many instances of technology out there, your risk profile, in addition to the cost of operating that, just goes through the roof. To keep 5,000 instances secure is just becoming an ever-increasing problem for these companies. These executives are now coming to us and saying, "You know what? We are realizing that we were too point solution technology instance-focused over the last couple of years. We have several of every technology that we have and every version under the sun of every programming language, every processing framework, every database, whether it's in the cloud or on-prem, we need to simplify that." That is a big part of our strategy and why we are focusing on these very largest of companies, because the opportunity here is huge. It's not a simple problem. You don't turn off hundreds of instances overnight.
This is clearly something that needs to be implemented. They're all looking for who is the solution provider that can do this at scale? Because they have tens of thousands of employees. They have hundreds of thousands of applications that need to run, and almost every other technology on the planet today limits them in terms of scale. Yes, you can stand up an instance and run 15 users. Or maybe some of the newer cloud things, they say, "Okay, we can run 80 users at a time." That's just not anywhere close enough to consolidate these infrastructures into a much more simplified way. Billions of dollars are spent in a single customer, and we see this across the entire customer base that we have.
The problem with that current landscape is, in addition to risk and complexity, they're spending billions of dollars on that, yet a recent survey that we ran in this customer segment, 74% of executives tell us that the technology is too complex. They're not getting the things done they need to get done, because the projects take too long, right? It's overwhelming for their IT departments to operate that and to make changes to it. A lot of these things that have been done for agility, let's build another point solution because we can do it very fast in 30 days, in 90 days, have now become tech debt to them that they're struggling to even keep alive and keep secure. Just patching these systems up and dealing with the failures of these systems is keeping them very busy.
79%, almost 80% of their employees say they don't even have the data that they need on a daily basis to make decisions, even though they're spending billions of dollars on that. More and more of these companies are getting to a realization that if we want to significantly increase our productivity, reduce the risk, we can't throw another billion or $2 billion at the problem and expect that to scale. We need to have a different way. This is where simplification is really starting to become a theme that we are seeing at a lot of these companies. This is where our strategy starts to come into play here. By the way, the strategy that I'm going to talk about here is not a new strategy. We are on a journey. We started with Teradata Everywhere. We've implemented that over the last two years.
We have learned along the way. We've made great progress the last eight quarters, and you've seen how the adoption in our customer base has accelerated, specifically when it comes to buying software, subscription-based business. We've also taken our time this year to take a step back and say, "Okay, this is a great starting point, but where does this need to go next?" Let's start with what we believe or what we know, what our customers are telling us the solution to this problem is. They want to leverage 100% of the data to uncover real-time intelligence and do it at scale, not a data silo here, another copy here, 50 users at a time. They need capabilities where they can trace and track how data is flowing through their organizations. Who has touched this? Who has had access to this?
In part because of security and cybersecurity, also in part because of simplification. Every time they have to make a copy of data, they end up spending more technology time on building the copy, maintaining the copy, keeping it up to date, repairing the broken data, dealing with these concepts like data drift that are all over their organizations, it's really distracting them. Our strategy is here to enable these companies to rise above that complexity and that cost and that inadequacy of their analytical landscape, and really find the answers to the toughest challenges that we have. You've seen that also in our rebranding and our messaging and our storytelling, that we are focusing much more on the answers, on the outcomes, rather than on the technology stack underneath it. I think this is an important part.
We framed this up, and we call this pervasive data intelligence. By the way, we have gotten very good feedback from customers that we leverage to test our messaging and what we are doing there. They immediately felt like, "Yeah, we can relate to that. This is what we really need." pervasive data intelligence, it's 100% of the data at any scale to all of our users and for all of our processes. We're using this to define kind of a new standard. You have known us as the data warehouse company for the last couple of decades, and we have the best data warehouse tools and best technologies. This is a higher level. We have taken this to the next level, and we'll talk about Vantage and what Vantage plays in this environment.
It has given us a core to build on that you know scales, you know is the most efficient core in the world, and that allows us to really take this to the next level. To sum it all up in one sentence, what the strategic focus is really to rise above the complexity, cost, and inadequacy of today's analytics landscape to deliver pervasive data intelligence to our top opportunities. You heard Vic say that, and you will hear us a lot more. We're using the term mega data companies, and I'm going to get into that here for a second. It's not whether it's 499 or 501 top companies in the world. It is the largest companies that produce the most amount of data in the world.
This is where we have that unique opportunity, and those are the companies that require the next level, that pervasiveness of data and intelligence, the analytical tools brought straight to the data, not just a data lake where you do one thing, a data warehouse where you do some reporting on it. They want a single platform that brings the data lakes, the data warehouses, the analytical platforms, the languages together in a single-to-operate stack. More and more of them are opting to not even operate that stack themselves anymore. We're going to talk about that in a second. It's a theme that I think you see in the industry overall, with cloud companies and cloud app companies are abstracting away technology underneath it and really focusing on the business outcomes rather than how to build the technology underneath that. What's the target?
This is just to reconfirm. By the way, when we started this year, we went into our strategic planning cycle for the year. By the way, we have done a larger strategic planning cycle than we have probably ever done before. We took a bigger horizon. When we built strategy this year, we took a 10-year horizon. For the first time ever, we said, "10 year from now, who do we think we are going to be as a company?" We all realize that nobody can predict how the world is going to look like in 10 years from now. We did a lot of scenario planning and looking into where do we think the world is heading, and it gave us a pretty good idea of the core components that are out there.
Needless to say, Teradata will be a very different company in 10 years from now. We are not telling the world precisely what it is that is our 10-year plan because we believe there is a lot of competitive advantage that we are coming out with as part of that. We based it off of that 10-year view. Then we took it back to, okay, what are the next three years? What are the next steps in the evolution of Teradata Everywhere? You saw us this year do Vantage and launch Vantage as the next step. We'll give you a little bit of an idea of what is coming in 2019 that will evolve us even further along those lines. Ultimately, we started with reconfirming or looking at top 500. Is top 500, is that the right opportunity that we're looking at?
We ask ourselves these very serious and tough questions all the time. We came out convinced more than ever that we have the right market segment. We have done even more segmentation within the mega data companies and applying our resources even more specified by industry and by opportunity and by behavioral segments that we see in our customer base. Overall, these are what we call the mega data companies of the world. These are the largest, most demanding, largest scale users of data. They leverage data for everything as a secret weapon to differentiate themselves in their industry or to potentially redefine how an industry is operating. They more and more demand tightly integrated solutions. What we are talking about here, by the way, is what our customers are telling us, right?
We have really gone into these mega data companies. By the way, we have changed who we are talking to in these companies. We've always been listening to companies, but sometimes we have been listening to the wrong level in the company. We have been listening to feature requests. I need another feature here and another feature here, and can you make this query run faster? Can you give me this kind of data set, right? We are listening more and more so to their C-level executives, even their boards, in terms of what they need to do and what they need to accomplish.
They are demanding more and more so tightly integrated solutions that can accommodate that scale and give them the speed where they don't have to divide it up in silos and point solutions just so that they can overcome the scale problem that they have. They want less and less to be even involved with having to deal with scale. A lot of companies of them have tried to become technology companies. Everybody in the last 10 years, so many companies said, "Oh, I want to be like Google. I'm going to hire lots of PhDs and maybe I even build my own hardware." There's a little bit of a rethinking going on right now.
Some companies that have done that have since closed 500 stores. They have realized that they've done technology experiments. They've forgotten about focusing on the business and the hardcore problems that fraud and cybersecurity and supply chain and churn is doing to them. Ultimately, they're also telling us that they need choice. We started that, of course, with Teradata Everywhere, and it gets reconfirmed over and over. The mega data companies of the world have complex environments, complex ecosystems, lots of them have big data centers. Cloud is certainly a big topic for them. Having said so, the vast majority of them is not planning to go wholesale just into one cloud. They want to leverage cloud for parts of what they're doing. They also believe that they need a hybrid environment where they can be in the cloud as well as in their own data centers.
They also realize that sometimes they have to make changes to some of their choices. Some companies that have picked AWS as their preferred cloud provider last year are now back this year and saying, "Well, given that we're also selling to the world's largest retailer, we realize that we probably can't be in AWS, and we need to move to a different cloud and operate there." That choice and flexibility is becoming a decision criteria, and a lot of the feedback that we have gotten was, yep, this Teradata Everywhere strategy makes a lot of sense. It really allows us to make decisions quicker because we don't feel locked in. This is not the old Teradata. It gets amplified with the new brand and the new messaging that we are telling. It's part of that. They also tell us, though, "We love this Teradata Everywhere thing.
If you could just do more analytics on top of that, if you could help us bring all of these one-off tools together, because we literally have one version of Python or each version of Python under the sun running in the company, each version of R, each data store, data lake, object store, file system that you can think, and the management overhead is just getting too big. We would love to consume this as a simple to consume stack and as much as possible as a service." Let's talk a little bit about the opportunity here. I need to take a moment to describe what this means because this is not your average company market sizing. This is not what IDC or others track or define.
The world's mega companies are a customer segment that we have defined based on various conditions and various things, we've benchmarked this year, this segment, based on our progress on the last two years, and based on what we're seeing in terms of traction with Teradata Everywhere, traction with Vantage. We have benchmarked ourselves against those accounts where we have been most successful. We looked at the share of wallet that we have increased in these accounts. We have done this by industry for all of these customers in the top 500 or mega data companies that we have. We have said, if we were to raise the entire customer base by an equal amount that we have done in the early adopters of that's 10 times the opportunity than what we are today. That in itself is in excess of $20 billion. Right?
This is not a market segment that anybody Gartner will never track that, right? This is not the overall industry. We know that big data and analytics over what, 2022 will be in excess of $260 billion of a business. We wanted to bring that down to specifically the companies that we are focusing on, and what it takes to be successful in that market. What you will see from us is a level of specificity that we are driving with our strategy into this company like we've never done before. We are truly treating our golden customer list as the single version of the truth and applying every dollar we spend in growth, in investment, and tying it back to what are we driving in this space. That level of focus that we have applied is the reason why we have accelerated faster with adoption of subscription.
It has allowed us to do these things that we said, for the last 8 quarters, deliver consistently. Every time we said we would do something, we did that, right? We're seeing that that's accelerating, and this is the foundation of where the strategy is going. Naturally, what I'm telling you here is that our focus is to aggressively grow that share of wallet within this customer base. Yes, there's also other mega data companies out there that are not our customers yet. Yes, we will go after new customers around the world, but given that it's a top 500 and we have, what? 320 or so of them as customers today, it's not about hundreds or thousands of new logos that we are chasing. We are very specific, right?
There is tens of logos at any given point in time that we pick and invest into. The vast majority of our focus is on that growth of share of wallet with the existing customer base. We have seen that, as I said, in the last two years through our focus on Teradata Everywhere and now with Vantage, the opportunity we believe is huge for us. These companies are telling us more and more so what they need. By the way, I talked briefly about the fact that we have internally also segmented that customer base for the first time. We have behavioral segments. We're overlaying geographical segments, industry segments to that, and we know the kind of different requirements that customers have. There's also some overlapping requirements that are fairly common in what we're seeing.
First of all, the business leaders and analysts are more and more focused on business outcomes and less and less on making low-level technology work. In fact, if you can do away with technology and just focus on the business problem, that's what they really want. They also are telling us very loud and clear that it needs to come with a winning user experience. It needs to be simple. It needs to be web-based. It needs to be the way the new cloud companies present themselves. We've made a lot of progress in that space, but a lot more work has to be done. They want easy-to-use platforms that just work, that scale, that take any sort of query, any sort of analytics, and simply provide the answer.
Too many times, they find themselves in point solutions that can either do only a subset of the analytics or only do the simple queries or only do 10 or 20 or 80 users at a time. Then they're faced with the impossible challenge of saying, like, "Okay, I cannot continue asking my questions. I first have to change the underlying platform or build yet another solution." They just don't want that anymore, right? They also are telling us that they want much more frequent updates on analytical functionality. They don't want to wait for big releases anymore. They don't want to wait for two years. A lot of these things are what the cloud really has enabled in terms of a user experience, right?
Ongoing new fresh software that gets updated incrementally every couple of weeks with new capabilities coming out all the time to help them manage their ecosystem. Ultimately, they want an ecosystem. They want a platform that they can build applications or apps on top of. It needs to integrate with the ecosystem that they have. If you look at these mega data companies, these ecosystems are big. They are complex. There's a lot of technology in there. They won't do away with mainframes anytime soon. They won't do away with some historic systems that they operate anytime soon. There's a mix that goes from all the way of state-of-the-art give me cloud technology, but also integrated with everything that I have implemented over the last couple of decades.
On the IT side, that leads to requirements like we need that seamless integration with our internal ecosystem. Again, these mega data companies have large data centers. Yes, they're moving some work into the cloud, and as you know, they're also moving some work out of the cloud back into their data centers. They're making decisions, right? This is no longer a switch. We're going one way or another. They're optimizing based on the scale and the needs that they have. They want experts to help them implement that, right? This is where our professional services, for example, comes in as the experts to help them integrate that across these various different technologies. They need robust enterprise security. We cannot underestimate the importance of enterprise information or security.
Why am I focusing on the level enterprise is because they have a lot of point solutions that inherently every point solution says, "Yeah, I can do security on top of that." Where they all struggle is when they take a step back and look at the larger ecosystem, they can no longer trace who touched what data in what system at a global scale. Just to give you a perspective here, we have customers that run more than a billion requests against Teradata analytic systems a month. A billion requests that they need to keep track of who did it, what application did it, is there any chance that we have any exposure in cybersecurity? The more bifurcated that ecosystem is, the harder that becomes for them. They also want Q&A and sandboxing, virtual data labs. This is something that we have not emphasized enough as a company.
Teradata was the first company that came out with virtual sandboxes more than a decade ago, and we have not put enough emphasis on this. Yet our customers are telling us very clearly, "I need the ability to elastically stand up a virtual sandbox, whether it's for a day or two weeks, make a decision if this is of any use, and potentially throw it away if it was not good, or move it immediately into production without having to rewrite or redo the work that I have put into this prototype." This capability is starting to become more and more important because governance ultimately is an important factor for these large companies. You can only put into production data that you can trust, that you can audit, that you can go in front of an auditor and say, "You know what?
Here is why we have made this decision. Here's the trace of data, and here's what the model has decided. Last but not least, they're asking for more automation, automated data ingest, data integration, autonomous platforming, right? I don't want to have to do it by hand. Here's data. Have the system figure out what the best structure is. Have the system figure out how to optimize that based on the questions that I'm asking, and just make it run better every time I ask a question, rather than me hiring DBAs or sys admins or paying somebody else to optimize these platforms. All of that is a big shift towards as a service offerings. When we say as a service, to be very clear here, as a service is not we throwing human people at it and doing services business. This is APIs are driving this.
This is algorithms driving this. This is the system driving that, abstracting away the complexity, just like other products and companies have done in your cell phones or cars, abstracting away the technology, solving business outcomes. Now, these mega data companies have one of everything out there, right? This is the part where I think I made that point a few times already. This is not one technology that they have out there. They have literally every technology that was developed over the last decades. I remember having conversations when I was a customer about Netezza and DATAllegro and Redshift and Greenplum and everything. There's always a new technology, right? Today it's Snowflake, right? Yesterday it was something else. Oh, by the way, we are watching the competitive landscape very carefully. We are learning from what the competitors are doing.
We are looking at what they do well, and it influences in part what we do and how we structure our product roadmaps. Let's make no mistake, we are not driven by competition. We are driven by our customers and what they are telling us what they need. They like a few things that have been coming up over the years in some of these things, and you have seen Teradata integrate some of these things. We have also put things into Teradata that none of these competitors have touched or are touching, right? Because in order to solve these complex answers, in order to deal with IoT data, 5G, all of these new data elements, you need more than a data warehouse.
Yes, more and more of these companies are rebranding themselves to like, "Okay, now we are a data warehouse company because whatever we did before really didn't work. Now because Teradata has been this data warehouse company, we are the data warehouse company, and we are now a better data warehouse company than Teradata is." So, first of all, they are not. Yes, they're solving certain problems. They're doing certain things. They are forgetting about 80%, 90% of the complex things that they have to solve, and that will take them years. Our point here is we're not focused purely on a data warehouse market. One or two of you analysts told me, or that was an industry analyst, after we had Teradata Analytics Universe two months ago in Las Vegas, the analyst came and was like, "Huh, I heard a lot about Vantage.
I heard a lot about Pervasive Data Intelligence. I don't think I heard data warehousing once at the conference." We're like, "Yeah, because it is a building block that everybody assumes needs to be there." Yes, we have the best data warehousing engine on the planet. The problem that we are solving is beyond data warehousing. Because data warehousing is often just the reporting engine of the enterprise. Where we are pivoting to, where we are moving to with Vantage is going to a higher level. All of a sudden, customers come to us and say, "Okay, can I do this without most of these technologies? Can I get rid of all of this complexity?" That's the opportunity here, quite honestly, that we are seeing. Again, these companies are facing unique challenges of cost and complexity.
We talked about the silos, conflicting duplicate solutions. I know I keep talking about it. I've been talking about that when I was a customer more than a decade ago because it was our biggest drag that we had. Yes, it is difficult, but once you get out of them, it opens up a company to do different things. They have considerable expense locked up in maintaining that complexity. Thousands of headcounts, in these largest companies. They have a lack of operational analytical focus. What do I mean by that? Many of these companies have hired data scientists. By the way, these largest companies, they hire data scientists. They might want to have more data scientists, but they find data scientists. The largest companies in the world, they have their own data science teams.
Too often they build an insight with data science and then somebody says, "Great, let's operationalize that," and then they fail to do so because they don't know how to make that Python code or that whatever language or framework that they have written it, operationalize it, run it with SLAs, run it against hundreds of millions of customers or hundreds of millions of transactions. This is where they often struggle and fall short. They're asking for this platform. This is a big driver of Vantage. I have an idea of a new model that I want to develop. I want to train it, I want to test it, and I want to put it in production in the next 30 minutes. For most companies around the world, this is crazy talk, right? This is like, are you kidding me?
30 minutes to have an idea, train a model, and put it in production. It's more like 30 months for most companies to do that, right? They come up with great insights and then they completely fall short of implementing that. This is one of the key areas of Vantage. This is really important. You will hear more today about customer examples and how this is real-life experience today. They need to deploy, as we said, across a heterogeneous environment. This is big part of Vantage, and you will hear more from Reema and from Stephen Brobst today on customer examples and what we're doing there.
This is why we have opened up Vantage and why the platform is a very open platform. What we have already told our customers that in 2019, we will have native support for other file systems, object stores, cloud file systems, so that now you don't need to bring the data to Vantage or into Vantage. You point Vantage at the data where you have it, right? At whatever cost level that your storage is, because you want to operationalize these things very quickly. There's an intensified pressure for results. I talked about it. This is board level topic now. This is like, how do we get more effective? How do we get more agile? How do we spend less money, right?
Companies really saying, "I need to drop my run rate by $1 billion over the next 3 years, and I need to invest into a technology that can scale. At the same time, get rid of a lot of the point solutions that don't scale." With Teradata Vantage, we set out to not just solve these problems, but really reset the bar for an entire industry. What you will hear about Vantage is it's bringing together an entire ecosystem and makes it operate as a single instance that you don't have to think about the individual bits and pieces and languages and processing engines behind it. It's meant to be that connective tissue within that ecosystem simplification to make it easy for customers to eliminate some of these data silos and bring it into a simplified ecosystem.
It's ultimately here to take even more risk out of decisions of our customers. When we first introduced Teradata Everywhere, the feedback that we got initially from the customers was, Teradata Everywhere. That takes a certain amount of risk out of our decisions because I no longer need to know if I'm absolutely certain if I want to run in my data center or in the cloud. Vantage takes that to an entirely new level. Okay, now you help me de-risk the analytical ecosystem, right? By not having to focus on how to make this work. Oh, by the way, we're doing this at massive scale and integration. That's what we are known for, and we're doing this in the cloud. We're doing this through bringing this together with the elasticity that is expected. We've put a lot into our products. We have simplified a lot.
I'm going to tell you more what we have done in terms of simplification and scale-out of our platform. What is Teradata Vantage at the highest level? We'll go into more detail to describe this here today because that was probably the number 1 question I heard from some of you last night. Okay, tell us more about what is Vantage, right? Vantage, first of all, integrates data sets across the enterprise. Sometimes I get asked, "Teradata, it's that structured data system, right? You have been a data warehouse, right? How can you deal now with semi-structured and unstructured data?" Well, it's not like semi-structured and unstructured data just showed up on our doorsteps. We started working in structured, semi-structured, and unstructured data more than a decade ago. I used to be the customer that pushed for that.
We needed to put clickstream data, call center logs into Teradata. 10 years ago or 15 years ago, that was hard.
Yeah.
That was a lot of work, there was a core of that engine that scaled so well, it turns out structured, unstructured data are just different pathways. You still need the same scalable platform. You still need this elasticity. You still need the workload management that Teradata is powerful on. Over the last decade, Teradata has built all the hooks necessary to either ingest structured, semi-structured, unstructured data or access structured, semi-structured, unstructured data in other places. Vantage just brings that together, makes it easy to do that. We've also brought functions and engines together. You've known us from having this Aster Data brand as a separate analytics platform.
One of the first things, by the way, when I came and joined this company, I was like, "It doesn't make sense to have yet another system that I need to turn on just to do analytics." Right? Yes, some of our customers have done that, they have copied data from A to B and back to A, right? It needs to come together. We also took all the functions that we had there over the last couple of years and integrated them all into Vantage. It's now one platform. We eliminated everything that we didn't need from the old technology stack, but we took every single one of these analytical functions and put them either directly into the Teradata engine or into one of our co-processor frameworks that we have built for Vantage.
On top of that, the other thing that we have done is, and our customers have asked us for this over the last couple of years, we also looked at tools and languages very differently. In the past, yeah, you could have any language that you want as long as it was SQL. Right? That was Teradata, right? The world is no longer just a SQL world. Although I have to say SQL also will never go away because for certain use cases, SQL is the most scalable, most optimizable language out there. There is Python and there's R and there's various other flavors of languages. What we have built with Vantage is for the first time do we have a complete set of native language drivers into these languages.
Not a, oh, I need to use ODBC and Python and then basically tell Python to do SQL to Teradata. No, no. Now you have native drivers for Python and R and other platforms so that the data scientists or the users that are used to certain languages can talk to Vantage in their native language. We do the translation into whatever statements and whatever function calls in our co-processor framework that need to happen. This is how we bring together this pervasive data intelligence platform, and it's so much more than just a data warehouse. Having said so, it needs good data warehousing skills. It needs good governance, metadata, master data management, data quality, governance, lineage. Of course, that's a given. You want to quickly point analytics on top of that.
If it works, you want to quickly roll that in production without having to rewrite or redo it. I've talked about this journey that we have been on to reduce risk and increase choice. It started, not quite, but it started, the new Teradata started with the launch of Teradata Everywhere. A lot of work went into that before that, by the way. We didn't show up two years ago and said, "Okay, we're going to do Teradata Everywhere. Now wait three years until we have Teradata running in the cloud." We did that work before that, right? We showed up with a product that was ready to launch, ready to consume, and customers immediately could try that out. We provided that choice of where to deploy decoupled software from hardware, decoupled compute from storage.
I know there's a company running around claiming that they are the first ones to figure out how to separate compute and storage. It's not quite that simple. Yes, we have been on that, and Teradata Everywhere was the first step. We just launched Vantage to simplify that analytical ecosystem built on top of Teradata Everywhere. Give customers the choice, but also the simplicity to run these highly complex environments and get that environment basically out of the box, get it deployed in the cloud, run the operations in a single environment, connect to existing data stores, whether that is inherent object stores or bridges into HDFS and existing Hadoop lakes, and push down processing that we're doing in that way. Teradata Vantage is that thing. What we're doing in 2019 builds on top of that.
What a lot of customers are telling us is, "We love Teradata Everywhere. We really get excited about Vantage. If I only could consume this in a consumption model versus a capacity model that you have been traditionally selling us your technology in, right? A way that we sized up boxes, we sized up TCores. You bought a certain amount of capacity, and yeah, we gave you some elasticity in that. What if we could consume this in an entire different way?" There's some really big announcements coming in 2019. I can't give you all the details, but there is clearly the next step in the evolution of Teradata. It's happening, and it's built on top of Vantage and what we're doing with that. More to come for that.
I want to bring it back down to what we internally call the strategy on a page. The internal page is a little bit more detailed, clearly for our employees, but the first thing that we did this year as we built that strategy. The next iteration of our strategy, what we did is we said, "We're going to put it on a single page, its strategic pillars, the key focus areas," internally, every meeting that we start at every level in the company starts with a strategy on the page. That's a first for us as a company. We haven't ever had that focus to do that, and by the way, the feedback from our people, our employees, has been phenomenal. They're like, "Okay, I have clarity now. I know what's in it for me.
I understand how my work fits into this." Let me tell you a little bit more about what these strategic imperatives are. These are the five strategic pillars on top of people and culture that for today's purpose, we have taken off of that, and I'll have a separate page for that to talk about that. First, relentless focus on consumption. This is we're turning the entire company to focus on ARR growth. We told you last year that 2018 would be the first year that we incent go-to-market to sell subscription. We did that by total contract value, TCV.
A good TCV deal, three-year deal or whatnot, would pay more than the equivalent perpetual deal, we really convinced ourselves and our people that selling subscription is not only possible, it is absolutely the way to go, this is why you have seen subscription percentage accelerate throughout the year, this year. A focus on TCV, while healthy for driving subscription percentage, is not the same as a focus on ARR. What you will see us in 2019 is really across the board incent the executives, the teams, the go-to-market fields, everyone in the company on ARR growth because that is becoming now probably the single most important metric for us to drive the adoption of Vantage. There's more product-related announcements coming as well in terms of consumption, as I said, in 2019, but this is a strategic pillar.
Next strategic pillar we call radical simplification. First of all, there's a customer side to radical simplifications. Our customers want to consume us in easier ways, simpler. I want to go to a webpage, I want to call an API, I want to get my answers. I don't want to have to deal with anything. That's part of it. There's a flip side. There's radical simplification of us as a company. Two years ago, I think I talked about we had 12 hardware platforms, going down to two. We are down to basically one now. Up until two years ago, every Teradata system that Teradata ever sold in the last 40 years was custom-configured and custom-built for one specific customer. If that customer decided in the end not buying it, then we took it apart and we built a custom system for somebody else.
That's the old Teradata. We've taken IntelliFlex, for example, this year to a point where we've taken away the ability to customize it, and there's only two choices that we have and give our customers at this point anymore. When they need hardware, you can have a half rack and a full rack, and however many multiples of that that you want. The rest is software defined. It's cloud-like provisioning. Even in your own data center, we treat it as if it was infrastructure that we would provision on some of the other clouds out there. No longer doing anything custom to that, we are seeing some great benefit coming out of that.
There's a lot more simplification that we believe is possible in our own business model and what we're doing in terms of pricing. Mark will talk about what the financial levers are that each of these strategic pillars are actually driving. The third pillar is pivot towards as-a-service, and we on purpose call this as-a-service and not cloud. These terms are sometimes used interchangeably, and by the way, as-a-service, as I said before, does not mean send professional services to do something as-a-service. This is meant a platform, an API, an interface provides the outcomes and do that. That also means we are shifting over the next couple of years our focus from consulting, from building low-level, stitching-together platforms, because guess what? Vantage now does a big part of that and will do even more so in the future to focusing on the business outcomes.
Those solutions, those analytics that they want to run, help them run them, help them get to processes that allow them within 30 minutes to go from ideation to production rollout. That's what we think our consulting focus needs to be going forward. Transform go-to-market and brand. You have seen the next evolution of that this year with our brand launch. Martyn and team go-to-market have done a phenomenal job to roll this out in the company, but this is nothing but a start. We're not done. We haven't rebranded the company and say, okay, check mark. No. We feel like we have started a new race for this company, and we needed a new brand because too many companies out there in the world looked at our website or our logo as, same old Teradata. What they do cloud, really?
They wouldn't even listen to all of the things that we're doing, and we said, we need a new opportunity, and that starts with a new brand. It also has really invigorated our employee base, and the excitement that goes in the company around because of that is great. There's more work to be done in our go-to-market optimization. As I said, we have segmented our mega data companies into different segments, and we'll fine-tune go-to-market and consulting towards these segments because we now know how we can leverage and get more efficiency out of that, which ultimately leads me to the fifth strategic pillar here, deliver operational excellence. This is something that, well, every company does a little bit of that. We wanted to make that a strategic call-out, right? This is about continuous improvement. This is about measuring, driving, improving everything all the time.
We're rolling out a new management system within the company that focuses on key KPIs, that focuses on how we do our pricing, how we do our discounting, how we run our supply chain, how we look at everything that we are doing and really put that together. These are the five strategic pillars in the strategy. By the way, the other thing that we did here is everyone on our ELT owns one of these pillars. There is ELT members named on every single one of these pillars, and their compensation is tied to that. These pillars are cross-functional pillars, right? We're really operationalizing the strategy in the company and not just stopping at a nice PowerPoint slide that says, "This is a strategy," and then we go back and do it the old way.
A lot of change, a lot of progress that we have made, and we're really doubling down on that as we go forward with that. As part of the brand launch, we also redefined a little bit our mission and core values. This speaks to that people culture pillar that I didn't have on the last slide here, right? We transform how businesses work and people live through the power of data. We established three core values for our people that, by the way, we didn't invent them. We worked with our culture, with our people to say, "What are the three most important values for us?" The outcome of that work over the last couple of months was we dig deep and aim high. We go all in when our customers have a problem that we need to solve.
We raise up our customers and our world, and we rise as one. The reception that we are getting from our employees and people is nothing but amazing in that space, and I think this is a core important enabler. Ultimately, it's our people that make this company what it is. It's the innovation that they're driving, it's the customer problems that we are solving, and it's the foundation for everything that we're doing. Thank you very much.
We are a medical equipment manufacturer with a broad range of products, ranging from diagnostic images through ultrasound, all the way to a lab diagnostic. The mission of the service organization, where we apply data analytics, is to keep those products healthy and to make sure they're available when a customer needs them.
It's a matter of minutes, it's important that the technology is there, it's up and running.
If I have a computer tomography system in my emergency room, I need that to be working when a patient comes in.
I think we have 240,000 customer or patient touch points every hour.
What we want to really do is to focus on generating the insights out of the data. We really need a solution which takes care of that in a most automatic and scalable fashion.
Teradata has big advantage that it really works on a global scale. We have terabytes of data in 70 countries. In the end it needs to scale. We want to have the right answer before our customers have even the question.
That includes, for example, proactive or predictive services. Something is breaking in the next 10 days, we better come and fix it before it actually happens.
Our mission is really to get from a data level to answers to better outcomes for our customers. Teradata Vantage can help us in that game.
Good morning, and welcome to our new headquarters in San Diego. Right timing, the sunshine came. I was going to say sunny San Diego, but it flips a little bit, right? Thank you for being here today. I'm Reema Poddar, and I'm the Executive Vice President for Products and Technology at Teradata. I joined Teradata 18 months ago, and since then, I have been working closely with the leadership team to execute on our product strategy. I have worked across the entire company to bring together the team to deliver the first release of Vantage, which we publicly announced in October. I'm really excited to share some of the customer stories. You will hear through the entire session today how our customers are looking forward to leverage. In some cases, they have already.
They've seen the answers that Vantage delivers, they're applying it to generate that new revenue stream for them and driving their business outcome. Let me take this opportunity to emphasize few thoughts that Vic and Oliver shared with you today. We have been listening closely to the customers. As Vic mentioned, we started the Teradata Everywhere strategy two years back. Oliver mentioned how we have been learning through those experiences, sharing those, and investing those learnings back into our product portfolio. You heard the word mega data companies. Oliver was talking about it. They are the most demanding customers, they are the most demanding users of data. They use data as their secret weapon to do business. As we are talking to the C-suite customers, what we are really hearing time and again is a consistent message across the board.
They're saying: We want to de-risk our investment. We want to eliminate cost. We want to apply our resources to the most valuable business outcome that we are looking for. Above all, we want simple, simplistic way of integrating. We want to avoid complexity. Above all, we want to have the flexibility, the choice of deployment. We want to also get the choice of where should the data live, which application should move to the cloud, to the on-premises. You get that theme across. What they're really looking for is a hybrid solution. Teradata is the hybrid cloud analytics software provider who uses 100% of the data across the organization, the enterprise, to drive business outcome for them. We enable companies to rise above all these complexities, cost, and inadequacies of the current analytic environment and landscape. That's what we are.
As Oliver mentioned, the conversations have changed. We talk to the influencers, the business influencers, who really want to drive business outcome. We focus on our customers' success, which in turn drives our success, our growth. Today, I'm going to talk about Teradata Vantage. You heard Oliver talk about it. We heard a lot of questions yesterday from many of you. What is Teradata Vantage? What is new in it? It's a single platform that really brings about simplicity, that brings all the tools, the datasets, the languages, the advanced machine learning functions, all in one platform, allowing us to really address the differentiating part, is address net new advanced analytics use cases. Not just descriptive, predictive and prescriptive analytics.
Which will allow you not to look at the answers, the analytics that delivers, but in turn gives you recommended course of action to drive net new value for your business, for our customers, which in turn drives consumption of ask Teradata, which powers our ARR growth. Why is it powerful and why is it defensible in the market? Vantage is built on top of the gold standard. Oliver was talking about data warehouse. We need the crown jewels. We are the powerful software core that we have that can scale, that can perform, that can address the high intense workload that the enterprise is looking for, that delivers the critical workload and the answers to all that they're looking for. That is the differentiating part. By the way, it takes years and years to build a powerful and advanced analytics platform.
We built Vantage on our superior core that's already there. For our competition, it's going to take a long, long time to get to where Teradata is here now. Teradata Vantage is the enterprise platform that sets the new standard, pervasive data intelligence that powers that. It's not about bringing data into Teradata to do and solve your problem. It's about how do you help solve complexity and digitization. Sorry. It provides integrated datasets, multiple datasets. It gives you the answer, all your data, the way you need it. It provides those analytical functions and engines that is needed to analyze that data. Addressing the data that you can see across the organization, not just departmental. See your data across your entire organization.
It provides the tools and languages so that you can power your smart people, the citizen data scientists, the business analysts, who finally have to use that data. They have to build, test, and deploy to deliver those answer giving analytics. That is going to give you those answer for your prescriptive, looking at your business, looking at that net new gains that you can drive, which you can otherwise cannot. All in a simple, usable manner in one single platform. Teradata is a trusted brand with 40 years of experience, innovation, investment. We haven't built Vantage from scratch. We have leveraged our existing superior code that is set as the gold standard in the industry. It's high-performance, scalable software, and it can work on the most complex queries that our competitions cannot even handle. It can work on the critical workloads that is mission-critical for some of the businesses.
Think about aviation industry. Think about healthcare industry. Those are mission-critical workloads. They run that. They have to produce, perform, and give that answer in fast manner, and trusted answer. That's what Teradata Vantage does. You heard Vic talk about Teradata Everywhere. A key differentiating component to our foundation is that, Teradata Everywhere, which is highly valued by our C-suite customers. Vic mentioned about chief digital officer, the CIOs, all of them are looking at de-risking their investment to find values, to reduce their complexity, to simplify and deliver those answers to their business, powering their employees. You saw the stats from Oliver, how employees cannot even view data across. They are not powered by those simple solutions they can leverage to draw insights and deliver those answers their business users want. The CIOs are posed with questions. Which cloud provider do I use? When should I move?
What about all those applications? Can I leave some of them on-prem, some of them in the cloud? We see that hybrid cloud is going to be there in the foreseeable future. Teradata de-risks this decision because we can deploy our software anywhere, anytime. We give the application portability with no code change. Above all, we can deploy the same software in Amazon Web Services, in our own private data cloud, in Azure, on-prem. Above all, Teradata Vantage allows that flexibility to our customers to move any time with the pricing not skyrocketing like Snowflake based on the usage. We continue to invest heavily in that core platform, and we do it because we want to make it remain best in class in the industry, and that delivers the descriptive analytics.
We have extended on top of that the analytic data types, the languages that allows us to develop predictive analytics, such as in customer journey, fraud analytics, predictive asset maintenance. Remember the critical workload we were talking about? It's not just about that. You have to draw insights, give predictive modeling, and ultimately prescriptive analytics and the sentient enterprise, in which the analytical answers provides the recommended course of action. That is what we are aiming at with the best-in-class artificial intelligence delivered with near real-time answers. You would say, what is unique again in Vantage? Let me take you through a storyline here. What happens if the analytics is not delivering answers for your business? Is that good? I would say not at all. Do you know why?
The reason is vast majority of the analytic outcomes that are generated from data science projects never even make it to production. The reason is most of the customers do not have, or they lack a repeatable process that allows you to take the entire life cycle of analytic workloads, starting from ingestion, pulling data, analyzing it, loading it. We have a customer who's one of the world's largest bank customer, and what they had a problem they had imposed, and they said, "We want to collect data from all our channels, and we want to look at how we can improve our customer journey." Their data scientists spent six months collecting data from various data storages using different technical tools, techniques. You see the overhead. You need to have resources with specialized skills. You need to have technology that you have to learn.
You cannot use the same resources across the board. Again, this is all the problem of data silos. They spend six months just to collect, and that's just collection of data. This goes back to the point of 80% of time is used by data scientists just trying to gather data from disparate data sources. They spend few weeks again to analyze the data and then draw insights. Teradata Vantage, you can do that. You can bring that downtime from six months to just few weeks. To drive that answer from the analytics, few weeks to few minutes. You will hear those stories throughout the course of this session. That is the simplification. Teradata Vantage provides a simple, unified analytic workflow cycle, not just once, but in a repeatable manner. That's the process we deliver.
We recognize that Teradata is always part of the customer's broader ecosystem. We are going to be the first-class citizen. You heard Oliver talk about how simplification, the approach that we have to take for our customers, not only is applicable for us. You saw our strategic imperatives. How do you make this complex problem simple? That's how Vantage does it. Vantage develops and has the APIs that is applied to open standards so that we can seamlessly integrate into our customer's ecosystem, and also our partners can integrate into our ecosystem. That's the power of Vantage, providing those APIs that adhere to open standards. Vantage can help simplify this complex ecosystem by delivering not just the APIs, but reducing cost, de-risking. That effort you are going to apply.
It also minimizes the data movement that every other competition is trying to do right now, building silo data warehouse. We don't. We are going to take analytics to the data where it lies. We don't have to pull data into Teradata. What you are seeing here is a simplified ecosystem, the simplified platform that helps you to look at all these advanced analytics in one go. Let's take a look at our competition. Of late, you've been hearing, you might have seen some little bit of a heat from our cloud-only competitors. Companies like Snowflake and Redshift. They have limited number of concurrent users. Think about it for a minute. If you have to serve very large enterprise, mega data companies, whose users or whose community is thousands of users, look at that limitation that they have. Can they do it?
Yes, of course. They can duplicate their virtual data warehouse, but to a limitation. Second, their ability to handle complex workload. They have rudimentary workload management, and that too with no tuning. Think about it. Again, if you have to serve enterprise level companies that complex workload, that's a huge limitation right there. Tuning is needed, especially for critical workloads. Third, if you have to view the same data from one data warehouse to the next, you would have to duplicate the data again and again to see the same data across those datasets or the data warehouse. Especially when it comes to analytics, we're talking about analytics. One analytics that is built here, another one is built on the second one, and that goes on, right? There's no knowledge sharing, no insight sharing that's happening.
This also is a cause of introducing data silos, data drift, data governance, and all those trust issues that come along with it. I call it, instead of being part of solving that complex problem that we are all faced with, they are really introducing complexity into an already existing complex ecosystem. We call that as the data wasteland problem. They are contributing to that data wasteland problem. The question is, if you have companies like us, Teradata, who have all these capabilities we address profoundly. Why would you settle for a featherweight champion when you have a heavyweight champion with you? Let's look at Teradata Vantage. We don't have to scale duplicate. With one instance of Vantage, we can serve thousands of concurrent users at any point. We have proven technology, and we have testimony, we have customers that use us.
We have proven to be the company with that software that can handle complex workload management. Above all, we can access data anywhere it sits. We don't have to load data into Teradata Vantage. All these attributes are needed to really support and make an enterprise company successful. That's what Teradata Vantage has. You heard me talk, but just don't take my words for it. Gartner says we push the boundaries of innovation. Radiant Advisors say we reduce the complexity of analytics. Datanami proclaims Teradata Vantage is going to be the center for our customers' analytics strategies. In summary, Vantage is a single platform that brings all the advanced analytic use cases to answer, to deliver those business outcomes that our customers are looking for. It's powerful because we did not build Vantage from scratch.
We are building on top of our existing gold standard innovation and services that we have built over decades. It takes years and years for anyone to build large-scale enterprise-level analytics platform. Thank you very much.
Data and analytics is an integral part. Everything that we do with our customers all have digital interactions. Informing the customers, engaging with them is predominantly done on digital platforms. Pervasive data intelligence to me is not just the collection of data from every touch point that people have, but actually being able to leverage that data and solve both business outcomes and solve business problems. One of the next frontiers in sports analytics is really on analyzing player health. If we look specifically at our team last year, when we had Rudy Gobert on the court, we played as a 59-win team. When he was injured, the stats indicated that we were a 42-win team, which is the difference between being the number 1 or number 2 seed or maybe even not making the playoffs. It has a huge impact.
The next frontier is how do we reduce those injuries? How do we find ways to help the players have better health, have better sleep habits, better dietary habits? How, when we identify a minor issue, do we keep it from becoming an ongoing longer issue for the players? There is a direct correlation between whether the team wins or loses and the amount that customers spend both in the team store and on concessions. Also, if we monitor our customer satisfaction scores, there is a significant difference between a win and a loss. Suddenly, our parking is less of an issue if we win the game.
My name is Stephen Brobst. I'm the Chief Technology Officer for Teradata. As CTO, I take kind of a different role than some Silicon Valley CTOs who spend a lot of their time just in the labs. My goal as CTO is to spend 50% of my time with customers. I want to take what I hear from customers, from prospects, from industry visionaries and translate that to what does it mean for Teradata's technology strategy, and how do we deploy products and services out to the field? What I want to do is share with you some customer experiences and what the Vantage means from a customer perspective. What does this transformation in Teradata's technology strategy, in Teradata's software analytics platform, what does that mean to customers? If we look at analytics and we break it down into 3 very simple phases.
The space of data warehousing largely has traditionally focused on descriptive analytics. Understanding what's happening in the business, doing reporting, being able to drill down, and largely SQL serviced that requirement as generated by a number of the BI tools out there in the marketplace. Data visualization tools like Tableau and Qlik or Power BI or Cognos, OBIEE, lots of different tools out there. MicroStrategy, et cetera. Long list of tools, all working very well with Teradata, focused on descriptive analytics. I will tell you that as we move more into predictive analytics, not just what happened in the past, not just developing the strategic intelligence for the enterprise, but being able to predict what's going to happen next, being able to prescribe the actions that we need to take in order to be successful as an enterprise, we need to go beyond SQL. SQL is not enough.
SQL is a great, powerful language, as Oliver mentioned in the opening, it's not enough. In Silicon Valley, where I'm originally from, and these big wars between, I'll call them the SQL bigots and the NoSQL bigots. The NoSQL bigots say, "You SQL people, this is very interesting technology, but this is old technology. Doesn't solve all my problems. Go sit over there by the COBOL programmers. Your life is over." "You are now legacy." By the way, agree with some of those observations that SQL is not good enough, just to be very clear. In Silicon Valley, there's no shortage of SQL bigots. Oracle comes from Silicon Valley. Informix came from Silicon Valley. Sybase came from Silicon Valley. Db2 and System R came from Silicon Valley. Arguably, the most important open source databases, Ingres, Postgres family, came from Silicon Valley.
SQL bigots will say, "You Hadoop people, you're a bunch of idiots. You're doing flat file programming. You've reinvented VSAM. Yes, okay, you made it parallel. That's interesting. That's good. You have no optimizer. You have no schema. You have no fine grain security. You have no workload management." This became this very religious war. At the extreme, in a religious war, both sides are stupid, right? The reality is, yes, the things that the SQL bigots complained about are largely true, that doesn't mean that NoSQL doesn't have value. Right? By the way, as Oliver said, SQL is not going away anytime soon because it's very powerful, but you can't stand still. You have to evolve. In Teradata, we began this investment, which we refer to internally, which I refer to as NewSQL.
It's not NoSQL, it's not SQL, it's NewSQL. NewSQL is taking SQL beyond its traditional boundaries, beyond the constraints of relational algebra, beyond some of the ANSI standard constraints and so on, to deliver more advanced capabilities. To deliver things like time series analytics, to deliver the ability to handle semi-structured data types like the web log data Oliver talked about earlier. The ability to do geospatial analytics, the ability to do in-database R and Python and other non-SQL languages to deliver the advanced analytics. This Vantage journey, of course, Vantage, we came out to marketplace this year with big branding and so on. The reality is this is not a journey that started this year. This is a journey that started years ago, implementing these new SQL capabilities.
As we brought more and more capabilities into the engine, what you would call the Teradata engine, you actually stop hearing us talk about the Teradata engine, because as Rima said, we just assume that that's there, right? We assume you need this foundation of great data management and all these NewSQL capabilities. I get asked all the time about these database players like Vertica or Snowflake or Amazon Redshift or whatever. These guys are competing in the old SQL domain for the most part, and they're still trying to do catch up on workload management and optimizer technology and a bunch of other stuff. For us, that's for granted. Of course, we will continue to do incremental improvement on those things, but our core focus is on how do we go beyond SQL for this analytics platform capability.
As we introduce more and more things into the database, which is great, we also recognize the need for engines that aren't necessarily going to be put inside the database, but actually sit as peers in this analytics platform. When we acquired Aster from the Stanford University spinoff company some years ago. Aster was a separate appliance with its own copy of the data and so on. Had some very interesting stuff. They owned, and now we own the patents related to how do you integrate MapReduce and SQL. MapReduce is one of the fundamental sort of programming paradigms that was introduced by Hadoop into the marketplace. Bringing that capability into the machine learning engine, and then creating that engine within this Vantage platform, this analytics platform, so that we can actually share the data rather than duplicating the data.
That data doesn't necessarily have to be in a Teradata file system per se. It might be in an Amazon S3 file system. It might be in an Azure Blob Storage infrastructure. Through QueryGrid, we might be getting some of our data from Hadoop or other NoSQL technologies. Make sure that we can get the data from the right place to get the data, and when you need the optimal performance, for the structured and semi-structured data, you're absolutely going to use the Teradata hash-based file system because no one can beat that performance. There are some cases where you might want to make trade-offs related to cost and performance and store on, for example, Amazon S3. You're less concerned about performance, but you want to optimize cost for some of the historical data or maybe staging data in a data lake and so on.
We have the ability in a transparent way to access that data without duplicating the data. With this cross-engine analytic orchestration that we do in the Vantage platform, we provide the orchestration. We make sure the data gets to the right engine through our in-memory analytics table technology, through the ability to have these machines as peers so we can do things like machine learning and graph engine capability. This is an extensible platform. That platform can include engines that we build. By the way, it's specifically designed so that we can plug in engines from the open source community, like Spark's machine learning library or TensorFlow, or engines that have not yet even been invented yet. Or engines that our customers want to build or their favored systems integrators. Or commercial platforms, maybe from the SAS Institute or Microsoft or others.
Teradata becomes this harness for scaling out the analytics to handle these mega large opportunities. Large, not just in the size of the data, but large in the vision and the sophistication, the complexity of the workload that they are working with. We do not, as part of the applications platform, the analytics capability is not the graphical user interface. That is not our core competence. We are not going to compete with the Tableau and the Qliks and the MicroStrategy and those kinds of guys, right? We build the connectors so they can integrate in, and you can use open source leaders like Jupyter, for example. Or maybe you want to use KNIME or RStudio and so on. The data scientist gets to use the languages of their choice and the tools of their choice.
We're not dictating a data science workbench, but rather connecting to the industry-leading capabilities within the organization. This Vantage platform is a critical evolution of the Teradata technology. From a database technology, which is where a lot of the guys are still competing now, yes, they have their silver bullets, they have the columnar silver bullet or the in-memory silver bullet or the cloud-native silver bullet. Silver bullets are never long-lasting. They solve a particular problem. By the way, we have cloud, we have columnar, we have in-memory. These are not things that solve problems by themselves, but rather part of a larger ecosystem. That's what we at Teradata do. Let me share with you some of the feedback that I consistently hear from our customers in the field.
Teradata Everywhere strategy, absolutely love it because it allows the customers to deploy without risk today and without risk tomorrow. I can deploy in AWS if that's the right answer today, and 16 months from now, if Microsoft makes me a deal that I can't refuse, Microsoft has matured to the point where I think it's going to handle my workload better than AWS at a better price performance, I can take my Teradata licenses, I can move them over to AWS. By the way, the licenses is just part of the story. It's the functionality. I can pick up the Teradata capability, the Vantage analytic capability. I can pick it up and move it. No line of code will change in that customer's analytic ecosystem that relates to Teradata Vantage.
I can't speak for other tools they may use in their environment, but from a Teradata perspective, their investment is protected. That gives them the confidence to make investments today knowing that those investments are still going to be good tomorrow when tomorrow the right answer may be different. I can make investments today for on-premises deployment, because that's where my data gravity is today for these big players, knowing that I can move into the cloud when I'm ready. Maybe, by the way, I will decide to do a private cloud deployment on-premises with the stacks that now Amazon and Microsoft are coming to marketplace with. Teradata's ability with a single code base, again, this isn't where you have the behavior on-premises is different than the behavior in the cloud because there's a different code base. No.
Single code base optimized at lower levels to understand the differences between a bare metal deployment versus a VMware deployment versus an Azure deployment versus an AWS deployment. Yes, we certainly do that level of optimization because the customer shouldn't have to worry about it. The functionality delivered, completely portable, completely protected, single code base, in the Teradata software. The reality is most of our customers today and going into the near future are going to be hybrid cloud and on-premises. They'll do their data science work that requires very high agility, where they're less concerned about cost, where they're very often using data that has been masked and therefore, there's no concern about sort of security in the cloud and so on, which by the way, is mainly FUD because I think the cloud is actually more secure than most data centers of large enterprises.
Put aside the FUD. They have the confidence that they can do that work in the cloud with high agility, access to lots of tools that make sense for data science to do experimentation with, and they can bring it on-premises for the productionalization, where you'd want to manage for cost and service levels a different set of criteria. The reality is most customers today have hybrid cloud strategies. They're a mix of on-premises and in cloud, and those capabilities are both important for Teradata's technology strategy. From a Vantage platform point of view, the ability to leverage the best in capabilities for open source and commercial working together, this is a key critical success factor. It's not an either/or.
It's the ability to take the best practices, to take the best software, to take best of breed in the industry, where we're focused on what is the total time to value, and what is the total cost to value. Some of our competitors like to talk about what is the price per terabyte of storing data. It's not that important. Storing data and doing nothing with it is not interesting. I want to know what is the cost for answers? What is the cost for value? What is the cost for outcome? That's where the rubber hits the road. The ability to sort of have the efficiency for the lowest cost per query, if you're complex queries for high concurrency, for the workload management, this is something that is highly valued by our customers. It's not just a SQL database.
Again, it's an analytics platform that goes beyond SQL by leaps and bounds. This space, especially in machine learning and deep learning, there's going to continue to be very rapid evolution in this space. We believe, I believe over the next five to eight years, there will be a new answer roughly every two years. Some time ago, SAS was arguably the right answer for advanced analytics. Then R became the right answer. Then Spark became the right answer. Caffe became the right answer. Right now, Google TensorFlow is the hot item. Two years from now, it'll be something different. Four years from now, it's hard to even predict what that will be, but that will be yet again, something different.
The Vantage architecture, by using containerization technology, by using a services-based approach with APIs, as Oliver mentioned earlier, allows us to extend with additional engines, which we may build, or the open source community may build, or our commercial software partners may build. We can plug them in without disrupting the ecosystem, protecting the investment, and allowing data scientists to do experimentation in their sandboxes and their data labs and so on, and then create that bridge that allows the productionalization without destabilizing the environment. If a data scientist takes some open source piece of software and invents something great, and then hands it over to IT and says, "Please put it in production." IT say, "I don't want any part of that." It's a big problem, as Rima mentioned.
There's a lot of great data science work that never goes into production, and we need to provide that bridge to bring it in production. Bring it in production with workload management, with high availability, with efficient access to data, without duplicating the data for every single engine. Vantage separates the compute from the storage. We can add engines independent of the data. We can share that data. We're not duplicating the data for every single engine. We do the orchestration for that. Minimizing the duplication of data, minimizing the movement of data, and building that bridge between the innovation part of the organization with the data scientist and the monetize it part with IT that's going to put things into production. If we look at the use cases that have been most popular in this first release of Vantage, fall in roughly six categories.
I want to be able to predict the future. I want to take historical data and use that to predict the future, largely with what's called supervised learning or training sets, using a wide variety of algorithms that are provided by the machine learning library within Vantage. Segmentation, unsupervised learning, clustering, using other techniques to understand groups of customers that are behaving together, so you can do micro-targeting to those segmentations. Understanding causality. What is the path to churn, and how did we get there? We can predict using capabilities within Vantage on a medical pathway, who's going to end up in back surgery and who's not, and which of those back surgeries might have been unnecessary, and what is the path we can take them on in order to eliminate the unnecessary back surgery, save money, and save the health of that patient.
Context, sentiment analysis, doing text-based analytics, doing sentiment analysis to understand how the customers feel about our products, our services, and so on. Network analysis, social network analysis, calling circles, understanding relationships. Understanding the path of money in money laundering schemes. There are lots of interesting uses of graph analytics within our customer base. Data science is a lot about having a good idea, having a hypothesis, and then testing it. Data science is data R&D. I've got an idea. I need to test it, and it needs to be fast and cheap to fail, because each failure is a learning.
The ability to spin up a data lab very quickly, to deploy the Vantage capabilities, do the hypothesis testing, and it's okay to fail as long as we're learning and we're doing it fast and cheap, then we go on to the next and the next, then we find those nuggets of gold. These are the six main use cases that we see in this first release of Vantage. Let me give you a few more specific examples. This first example is a major manufacturer that you all know. They make equipment which is quite complex equipment, multiple subassemblies, and they need to detect when some part in this equipment fails, which then makes the equipment inoperable. Now, by the way, detecting after it fails is completely uninteresting. Having a dashboard go red to say your machine is broken, yeah, we know that because it's not working.
We need to predict that this is going to happen, that the part failure is going to happen before it happens, not after it happens. This is not a dashboard which is describing what happened in the last two minutes. It's what's going to happen in the next eight hours. We take data from sensors. This is IoT data, Internet of Things. The things are the subassemblies and the parts and measuring things like vibration and temperature and other factors that influence our ability to predict whether a part is going to fail. In our machine learning library, we provide lots of tools for getting the data, parsing the data, organizing it, feeding it into the predictive models.
Then we can identify what are the specific factors that are likely to predict that something's going to fail before it fails, and allow us to prescribe what actions should we take in order to remediate the problem before the equipment is broken. The answer is a set of triggers that can predict that the performance of this equipment is going to degrade, oftentimes means fail, but it also might be degrade in performance and the quality of what's happening with the equipment. Taking the data on a continuous near real-time basis and generating those answers for decision-makers. By the way, decision-makers in many cases are software processes, not necessarily human processes. Right? We can intervene in an automated way in order to get high-quality operation of this equipment. The next example is a retail banking example. Large global bank.
They want to be able to detect when an account is at risk of closure and what are the interventions that we can do in order to prevent that closure. We take the interactions across multiple channels, across their branches, across their call centers, their mobile app, their internet banking, across all these channels. Taking detailed data into an integrated repository and then sessionizing it according to what is the purpose of the interaction. If I have a bunch of interactions related to something to do with my credit card, we'll sessionize those separately from the interactions related to my mortgage. Of course, we also look at the interaction between those sessions and how it impacts customer loyalty and customer affinity towards potentially closing an account.
We're able to detect patterns that indicate risk of defection and then prescribe interventions to take them on a different path. Right. That has significantly impacted their ability to manage churn within their customer base. This example is a multinational leader in the digital economy. They are focused on using business intelligence as an offensive weapon to increase their market share, to increase customer delight as measured by Net Promoter Score. They focus a lot on user experience. How can we remove friction from the buying process and from the using their digital platform? We want to be able to increase market share, particularly where we're underrepresented in certain product categories, upsell things like fulfillment services, et cetera. This customer uses a hybrid cloud environment.
They use Amazon S3 as their data lake infrastructure. They use Teradata Vantage for doing the heavy lifting on the analytics and the prediction and so on with IntelliCloud. They have been significantly growing their business. As they grow their business, they grow the use of Vantage. They've recently done an upgrade in their Teradata system. They're driving about a 30% year-over-year growth in Vantage. The business of theirs growing, our business grows very naturally. They are running many millions of queries, not a month, every day. Millions of queries every day. Many millions of queries every day. No chance to do this with the sort of low-end old SQL database wannabes that are still struggling with basic concurrency and optimizer and workload management. No chance. Believe me, they've tried. Every one of our customers, it's good for us. They benchmark against us.
They try, they look to see what does it really do, right. Marketing claims PowerPoint is very easy. What does it really do when the rubber hits the road? There are lots of examples. We could take the whole day talking about examples. One of the key themes that you're going to see is the ability to handle, at scale, the complexity and the concurrency of handling the workloads, right. We're not talking about a 20% gain or a 10% gain. We're talking about multiple factors, orders of magnitude. I'll take one of the examples up here, this multinational, this retailer, multichannel retailer in North America, thousands of stores, right. Plus an online presence. One of the issues that they had is there was a category of merchandise which is highly seasonal.
The timeframe that you have to sell this merchandise is measured in days, not weeks and not months. They have all these sophisticated models to predict how much inventory they should have on each store shelf by store, by individual SKU, stock keeping unit, right. Very complex models. They look at all kinds. They look at historical data, they look at weather, they look at all kinds of things. They get the right inventory to the store shelf. You know what. When that merchandise hits the shelf on Saturday, your best indicator for how much you're going to sell over the next seven days is what did you do on Saturday? They get the sales data and their model, before they deployed the Vantage capability, their model was taking more than 60 hours.
Remember, this is a lot of SKUs and thousands of stores, and each store is individually calculated what their inventory they need by SKU. Over 60 hours to do that. When you've got a seven-day window on seasonal merchandise and you want to take the Saturday sales and then predict what we need to do in the stores, rebalancing, shipping from the distribution house into the stores, 60 hours is no go, right? That just doesn't work. We were able to take this down to just over an hour, which meant that they could do multiple iterations, and they could significantly decrease lost sales, increase the accuracy of their inventory position so they didn't have excess inventory, because, by the way, if you still have inventory on your shelf after the season is done, this is not good.
This is inventory you're going to throw away or basically sell at some radically reduced price. It's basically garbage, right? The ability to do this, to turn this around, this kind of analytics, they could not do it with the other technologies. They cannot do it with the other technologies. This is bottom line growth for them in their sales, in their sort of reduction in inventory cost that translates directly to moving this processing into Vantage, driving consumption growth. That helps them, but helps us, too. That's what we want. Here are the key takeaways that I want for you coming out of this session. Teradata is not a stack of mediocrity where you say, "Buy everything from me." Because when someone says, "Buy everything from me," no one can be the best at everything. Teradata, we know what we're good at.
We deliver that capability with vigor, we integrate with best-of-breed players and other pieces of the stack, right? We're integrating with the Tableau and the Alteryx and the MicroStrategy and the Jupyter Notebooks and the TensorFlow and so on. Whatever the best of breed is for that customer, and different customers have different choices, that's fine, right? Best of breed of open source and commercial technologies into a best-of-breed stack. We bridge from the data scientists into the monetization of the data science to the productionalization, to the ability to manage the workload with service levels in production. Let the data scientists use the best-of-breed tools that they want to use, their languages, their tools, and then translate that into production deployment, which is where the value comes in the pockets of the enterprise. This last point is a very important message.
Teradata is not just a database anymore. You won't hear us talking about the Teradata Database anymore. We talk about the analytics platform, Vantage as an analytics platform. The database is one of the moving parts, absolutely. Think about that just for a second. Teradata has evolved from a database platform to an analytics platform. This is absolutely key. With this, it's my pleasure to introduce-
Transform businesses, transform people's lives. At Teradata, that's our purpose on this planet.
When we say our mission is to transform how businesses work and people live, how does that translate to your work and your everyday life?
I also ask you to think of Teradata in a new way. You used to know Teradata as the leader in data warehousing. Teradata has become a company that delivers pervasive data intelligence. Pervasive data intelligence is the new how, a new standard that we have set for an entire industry. This is the new Teradata that is all around you. We did the hard work. We executed on that strategy. You will see new products, a new look and feel. Every day I talk to executives around the world, and they tell me how they're struggling to integrate their analytical solutions, their data, and how it is impossible for them to get mission-critical answers at scale. A recent survey that we have done of 260 worldwide executives told us 75% of them think analytics are too complicated for them to implement, to act on, to improve.
79% of their employees don't have the data that they need to do their job.
There is no silver bullet. You can't do this stuff in three weeks. You have to have a partner that is there for you, that has been through it before, is committed to you, and will make sure that you are successful. We are real partners. We value our customers. We value our people in our company who make it happen. Success is the greatest thing that can happen, and we know that if we make our customers successful, that Teradata will be successful. We're not arrogant, but we're confident.
We're driving into this new era, the era of intelligence. To help with that, I'm very excited to announce, on behalf of all of Teradata, the availability of Teradata Vantage. Teradata Vantage is the enterprise platform for delivering pervasive data intelligence to really help solve the problems of complexity of our world and digitization. With Teradata Vantage, you really get three things. The first thing is you get all of your preferred tools and languages, your tools, your way. The second thing is you get the best analytic functions and engines at scale. With Teradata Vantage, you can see things that other systems cannot. The third thing that you get is support for multiple data sets, and it integrates everything, all of your data, any way that you need it.
We were lucky to have the first Teradata Vantage installation in the world.
There are over 110 million Sirius XM-enabled vehicles on the road right now, and that is projected to grow to over 175 million over the next several years, with 75% of new vehicles coming with our service and a free trial. That all translates to a lot of opportunity, and we intend to capitalize on it. With data and analytics powered by Teradata, we are positioned for the future. Teradata Vantage provides one common data strategy. It serves as the repository for our data. The data is cleansed, it's modeled, and it's available to be served up to the departments to operate their business. Teradata has reduced our cost and complexity.
I've done this for a long time. I really haven't seen this result ever. That's really what excited me and wowed me the most. It's just showing the power of the speed of the platform, of making it happen with the organization. With this technology, will just make us very agile, very responsive. We want to be best in serving our customers, as well as we are serving, as our network quality is. By utilizing Teradata Vantage, this is now really within reach, and that is why I'm here to share this amazing success story.
Philips, with the help of Teradata and leveraging real-time data and real-time diagnostic analytics, are able to more effectively diagnose problems and send the doctors to the more critical situations. They're integrating healthcare data from different places and using machine learning to identify abnormalities. They're doing it really fast.
What I want to talk about is Qantas, Australian airline. Their budget for fuel alone is $3.2 billion a year. A 1% improvement. It's $32 million. 2%, $64 million, you get the idea. They need to do this at scale. They operate more than 90,000 flights a year, and every single one of these flights creates 2 million data points per hour. They need to combine flight data, operational data, weather data, delays, airport data. With Teradata, they can. With Teradata, they have improved the fuel efficiency of their fleet by an additional 1.5%.
When we brought in these more advanced algorithms into Danske Bank, we increased the rate at which we caught the fraud, we detected a fraud by more than 50%, while simultaneously reducing the number of false positives. We're catching more fraud, we're reducing the number of people that we annoy by reducing the number of false positives. This is the power of these advanced algorithms.
The fact is, healthcare companies around the globe are using Teradata to harness the power of data and deliver answers and rise above all these complexities at scale. If they are able to do it, no matter which industry you are part of, you can too.
It's not good enough to just be in commercial software only. There's a lot of great commercial software out there, but there's also a lot of great open source software out there. You want to be able to bring those capabilities into your Vantage environment. Vantage is not just about things that Teradata builds or Teradata partners build, it's also about bringing the open source community IP into the analytic environment. This list is changing all the time. This space is moving very, very quickly, and if you plant your foot too hard onto one particular tool or algorithm, you will be wrong in two or three years.
Our platform is highly distributed. You all know this. We are obviously taking advantage of that. Our customers have the world's most demanding workloads. We know it. We always knew this. The same applies when you start playing with AI. What's special about our customers is that the data sets are large, the number of models are large, the complexity is high. One customer we are talking to has 1.5 million models that they want to run in production every day. There's another customer with 400 data scientists, and they will all create, delete, update, modify their models ad hoc, anytime. Our customers are used to running hundreds of thousands of queries simultaneously, seamlessly. It's all scheduled for them. When they run machine learning models, why should it be different?
The key commonality in all of these is getting the right answers from analytics at scale. It takes pervasive data intelligence. With it, Teradata is touching hundreds of millions of people's lives and has the potential to touch billions of lives. Teradata can handle the scale and complexity every single day.
What data should I be looking at? What's the data that really matters? What's the data that I could use to predict the outcomes that I'm interested in? This is the promise for Vantage. Our goal is to help you, help your decision makers, transform that data into answers that drive outcomes in your business.
That's a lot to take, I know. Actually, this is all about just one thing. This is about one platform that we are giving you, the Teradata Vantage. I've seen it behind the scenes, so trust me, when you try it will totally change your universe.
At Teradata, our mission is to transform how businesses work and people live through the power of data. Think about that for a moment. Transform businesses, transform people's lives. At Teradata, that's our purpose on this planet.
When we say our mission is to transform how businesses work and people live, how does that translate to your work and your everyday life?
I also ask you to think of Teradata in a new way. You used to know Teradata as the leader in data warehousing. Teradata has become a company that delivers pervasive data intelligence. Pervasive data intelligence is the new how, a new standard that we have set for an entire industry. This is the new Teradata that is all around you. We did the hard work. We executed on that strategy. You will see new products, a new look and feel. Every day I talk to executives around the world, and they tell me how they're struggling to integrate their analytical solutions, their data, and how it is impossible for them to get mission-critical answers at scale. A recent survey that we have done of 260 worldwide executives told us 75% of them think analytics are too complicated for them to implement, to act on, to improve.
79% of their employees don't have the data that they need to do their job.
There is no silver bullet. You can't do this stuff in three weeks. You have to have a partner that is there for you, that has been through it before, is committed to you, and will make sure that you are successful. We are real partners. We value our customers. We value our people in our company who make it happen. Success is the greatest thing that can happen, and we know that if we make our customers successful, that Teradata will be successful. We're not arrogant, but we're confident.
We're driving into this new era, the era of intelligence. To help with that, I'm very excited to announce, on behalf of all of Teradata, the availability of Teradata Vantage. Teradata Vantage is the enterprise platform for delivering pervasive data intelligence to really help solve the problems of complexity of our world and digitization. With Teradata Vantage, you really get three things. The first thing is you get all of your preferred tools and languages, your tools, your way. The second thing is you get the best analytic functions and engines at scale. With Teradata Vantage, you can see things that other systems cannot. The third thing that you get is support for multiple data sets, and it integrates everything, all of your data, any way that you need it.
We were lucky to have the first Teradata Vantage installation in the world.
There are over 110 million Sirius XM-enabled vehicles on the road right now, that is projected to grow to over 175 million over the next several years, with 75% of new vehicles coming with our service and a free trial. That all translates to a lot of opportunity, we intend to capitalize on it. With data and analytics powered by Teradata, we are positioned for the future. Teradata Vantage provides one common data strategy. It serves as the repository for our data. The data is cleansed, it's modeled, and it's available to be served up to the departments to operate their business. Teradata has reduced our cost and complexity.
I've done this for a long time. I really haven't seen this result ever. That's really what excited me and wowed me the most. It's just showing the power of the speed of the platform, of making it happen with the organization. With this technology, will just make us very agile, very responsive. We want to be best in serving our customers as well as we are serving, as our network quality is. By utilizing Teradata Vantage, this is now really within reach, and that is why I'm here to share this amazing success story.
Philips, with the help of Teradata and leveraging real-time data and real-time diagnostic analytics, are able to more effectively diagnose problems and send the doctors to the more critical situations. They are integrating healthcare data from different places and using machine learning to identify abnormalities. They're doing it really fast.
What I want to talk about is Qantas, Australian Airline. Their budget for fuel alone is $3.2 billion a year. A 1% improvement is $32 million. 2%, $64 million, you get the idea. They need to do this at scale. They operate more than 90,000 flights a year, every single one of these flights creates 2 million data points per hour. They need to combine flight data, operational data, weather data, delays, airport data. With Teradata, they can. With Teradata, they have improved the fuel efficiency of their fleet by an additional 1.5%.
When we brought in these more advanced algorithms into Danske Bank, we increased the rate at which we caught the fraud, we detected the fraud by more than 50%, while simultaneously reducing the number of false positives. We're catching more fraud, and we're reducing the number of people that we annoy by reducing the number of false positives. This is the power of these advanced algorithms.
The fact is, healthcare companies around the globe is using Teradata to harness the power of data and deliver answers and rise above all these complexities at scale. If they are able to do it, no matter which industry you are part of, you can too.
It's not good enough to just be in commercial software only. There's a lot of great commercial software out there, but there's also a lot of great open source software out there. You want to be able to bring those capabilities into your Vantage environment. Vantage is not just about things that Teradata builds or Teradata partners build, it's also about bringing the open source community IP into the analytic environment. This list is changing all the time. This space is moving very, very quickly, and if you plant your foot too hard onto one particular tool or algorithm, you will be wrong in two or three years.
Our platform is highly distributed. You all know this. We are obviously taking advantage of that. Our customers have the world's most demanding workloads. We know it. We always knew this. The same applies when you start playing with AI. What's special about our customers is that the datasets are large, the number of models are large, the complexity is high. One customer we are talking to has 1.5 million models that they want to run in production every day. There's another customer with 400 data scientists, They will all create, delete, update, modify their models ad hoc, anytime. Our customers are used to running hundreds of thousands of queries simultaneously, seamlessly. It's all scheduled for them. When they run machine learning models, why should it be different?
The key commonality in all of these is getting the right answers from analytics at scale. It takes pervasive data intelligence. With it, Teradata is touching hundreds of millions of people's lives and has the potential to touch billions of lives. Teradata can handle the scale and complexity every single day.
What data should I be looking at? What's the data that really matters? What's the data that I can use to predict the outcomes that I'm interested in? This is the promise for Vantage. Our goal is to help you, help your decision-makers, transform that data into answers that drive outcomes in your business.
That's a lot to take, I know. Actually, this is all about just one thing. This is about one platform that we are giving you, the Teradata Vantage. I've seen it behind the scenes, so trust me, when you try it will totally change your universe.
You gonna put up my slides? All right. Am I live? All right, welcome back, everyone. Thanks for coming, and we'll hopefully do this more often in our lovely new corporate campus here. I'm Mark Culhane, EVP CFO. I've met many of you, and/or almost all of you over time. I wanted to take some time today to put in perspective our strategy that we're driving to. Earlier this morning, Oliver gave you an in-depth overview of our strategy going forward. You've heard we're aligned. The entire organization is laser-focused on driving this forward. You heard Rima and Stephen talk about our new analytics platform, Vantage. That's what our customers have been telling us they want. We know where we focus in the market to simplify their data and analytics ecosystems.
They need a very scalable, highly reliable, high concurrency, strong security platform, and that's the hallmark of what Teradata has always been and what Vantage delivers. It's clearly uniquely differentiated and performs at a scale that nobody can match. Nobody in the market can match our scale and our performance, and you heard examples of that across the different customer use case examples that are unique and different, that only Teradata can perform for these biggest customers. Teradata, we are fully committed to moving this to a subscription recurring revenue business. To do that, it's all about how do we grow ARR. I want to spend some time going through each of our strategic pillars and talking about what's driving that and how that manifests itself ultimately into our financial statements.
Some of you have heard me say, and clearly, a lot of the folks in the company have heard me say, one of my favorite quotes of all time is a Winston Churchill quote. It's, "However beautiful the strategy, occasionally you have to look at the results." Which for the finance guy means it's got to show up in our numbers. We can talk all we want about a great strategy, but at the end of the day, it has to show up in the numbers. I want to connect the dots for you around how these pillars ultimately drive and show up in our numbers. Okay. Clearly relentlessly focusing on consumption, all about driving ARR growth. That's our first pillar. We drive ARR growth. We drive recurring revenue growth.
I am maniacally focused on that across the company, which other people in the company would tell you that that's what Mark's key thing is what are we doing to drive ARR and drive recurring revenue? I'm not focused on total revenue growth because we're in the midst of a transformation where eventually our perpetual revenue is going to go away, and some things we're going to do in and around consulting that I'll get into might result in that revenue declining, which it's not about during this transformation, what is total revenue doing? It's 100% all about what is recurring revenue doing. We have the entire company focused on it. The entire company is going to get paid on it. Their compensation is totally aligned, and we believe we can drive our ARR growth acceleration from where we are today for many years to come.
Let's get into what's going to drive ARR and revenue growth going forward. Clearly, we've made movement to a subscription model, candidly, that's been better than what we expected. Lots of reasons for that. We're moving away from perpetual deals, which at some point in the future goes away completely and we're 100% subscription-based company. When you're a subscription-based company, that's the only thing you're selling is ARR, effectively. You've heard lots about Vantage, how it broadens our market. In our install base, we think we have an incredible opportunity. The target market we're serving, Oliver walked you through $20 billion plus. It's a great share of wallet opportunity for us because we're, again, uniquely differentiated. It's what our customers have been telling us they wanted to help them solve the complexity, their cost structure.
It's even more about when my conversations with our biggest customers, CFOs, I've met with most of them, it's we're going to reduce their risk. They say, "Mark, the amount of risk that these data silos introduce across our organization is unbelievable, we need to rein that risk in. We need to rein that complexity out. Yes, ultimately it helps me reduce cost." When I'm in my conversations with the CFO, it's about I got to reduce the risk. We got too many copies of the same data. Why do I have customer IDs in 150 different data sources around the company? It's insane. Please help. Vantage is only going to be available on subscription.
We're only selling it on subscription, which ultimately we think what we can do for the biggest customers, you've heard from a scale perspective in Stephen's talks and some of the customer examples, we're the only one that can do this for these customers. That ultimately is going to drive our ARR and our recurring revenue. Hopefully you've now will take away that Vantage is a heck of a lot more than a data warehouse. Hopefully that came across very clear in both Stephen's talks and so forth, that we're much more than a data warehouse. The value we think that Vantage drives and the increased ability for customers to simplify that, we're going to price it accordingly. We'll price for the value that we believe Vantage drives.
Ultimately, we really believe our ARR growth assumptions can be satisfied by the opportunity just in our install base. We don't need a bunch of net new customers to go drive the targets that I'm going to lay out going forward. As we grow our ARR acceleration, it started in 2018. We had incentivized the sales force, as Oliver mentioned, around conversion, now we're shifting as of 1/1/2019 to ARR. I've done this in my past. We first had to move off of perpetual towards subscription, from there, once you get comfortable that that's working, you start to drive towards now it's all about growing ARR.
We, by the end of the year, another 18 days to go, 19 days and shopping days in this fiscal year, of our 1.2-ish, 3-ish billion of ARR, we will end the year well in excess of $400 million of subscription-based ARR. That's up over 100%. We'll be up over 100% year-over-year. That's not being driven because we're converting perpetual customers just to subscription. Lots of you have asked me, "We think your ARR growth is only because you're moving your existing customers off of perpetual to subscription." That's not truly the case because whatever my delta is going to end up being, our delta is going to end up being in perpetual revenue. A fifth of that is when you do a conversion from perpetual to subscription, about a fifth of that value is what shows up in ARR, maybe a quarter.
We're clearly growing ARR even in 2018 at a significantly higher number than that. Over time, we think mid-teens. Our three-year target out to 2021, mid-teens ARR growth. It's the target we're putting out there. We feel good about it. Again, like I said, I think we can drive that just through our install base. It's not only going to drive nice recurring revenue, but ultimately the mix profile of this businesses will be changed out into our three-year target as well, will be a recurring non-recurring business. The perpetual business will be gone. We think that's probably in the range of 80/20, 80% recurring revenue, 20-ish percent, slightly better, but in and around that 80/20 range is where we're targeting to end up in 2021. Mid-teens recurring revenue growth.
You've probably heard me say, even if we only grow recurring revenue for where we land at the end of 2018 at 10% for each of the next three years, our recurring revenue business will be in excess of $1.6 billion, in fact, probably just shy of $1.7 billion at only 10% recurring revenue growth. We feel we're going to grow out our target in 2021's mid-teens, we feel really good that we're going to grow better than 10% per year. Even at that rate, we have a substantial recurring revenue business. Our second pillar, radically simplify the business. Oliver spent a lot of time talking about this, both from a customer perspective and both from an internal perspective. This helps us not only, we think, drive ARR, but really starts to impact the gross margin profile of the business.
That's where it shows up of how we improve on that front. Let's just take a look at what are we doing there. Obviously, Vantage has uniquely positioned us to help them simplify. That clearly creates a wallet share increase, grows the ARR, but we've radically simplified the product offering. You heard things that Oliver mentioned and Reema mentioned around what we're doing to radically simplify the product offering. Oliver mentioned, "Hey, we used to have 12 different platforms.
We're down to one." That radically simplifies supply chain, supply chain costs, radically simplifies support costs to support these platforms on a post-sale basis, both whether that's from an engineering perspective or a traditional customer support perspective, and creates the opportunity for us then, given this radical simplification, to take costs down out of the business that starts to drive recurring revenue margins higher than where we are today. Ultimately, we also talked about making it easy to buy, simple to buy for our customers. I'm a firm believer technology, particularly software, is all about making it easy to buy. What we're doing from a subscription recurring perspective, whether that's a pure consumption model, if that's the choice the customer wants, or they want more traditional type subscription model, that's fine. We offer choice to make it easy to buy.
We do it in a construct of a deal that allows them to know how if they invest more and grow with us, what it's going to cost them into the future. It's a consumption-oriented model, not a capacity-oriented model. They don't have to sit there and decide today, "How much capacity do I need to buy for the next 5 years?" Negotiate like heck to try to get the best price. You don't need all that capacity today. The beauty of a subscription model is buy it when you need it, consume it as you go, and pay for it as you go. That flexibility, which Teradata in the past wasn't that flexible to do it, didn't offer all those choices.
That helps simplify from our customer's perspective of how they can invest and grow in a predictable manner with us at all, as well. All of this simplification then starts to drive recurring revenue gross margins into the future. Our 2021 targets, mid-70s. I've said in recurring revenue businesses, 70% is the minimum threshold, 80% is best in class. Very few recurring revenue companies achieve 80% overall gross margins. That becomes some rarefied air. We clearly, we're low to 70%, 72%, 73% we've been putting up. We're going to drive it to 75%, if not better, by 2021.
Ultimately, the gross margin profile of the business changes with a revenue mix change, along with improvements of radical simplification on the recurring revenue gross margin, and also what I'll talk about some of the things we're doing on the non-recurring revenue things, ultimately start to drive gross margins to the mid-60s. It's a huge pillar of what we're focused on and what we're going to go drive and do, and we feel very good about it. We know where to go, what we're doing. We've laid it out as part of our strategy, like we said, we're aligned to make it happen. Our third strategy, pivoting to as a service. Shifting from a consulting-first oriented business to as a service first business. I want to reiterate what Oliver said. This isn't as a service with a bunch of consulting people out doing a bunch of services work.
It's all around driving automation. That also impacts our gross margin profile of the business, right? We will be managing our consulting business very differently going forward, given how we're aligning it to the new Vantage platform and the strategy. Our focus on mega data customers, et cetera, means we're going to manage it and look at that business very differently. Other things that we're going to do around how the as-a-service manifests itself from a product offering perspective also has levers that pull and impact gross margins. The drivers here, this autonomous platform, our continued investment in that, automating things, less human effort needed to be involved, automating systems, processes, APIs, things that the platform just does that humans don't have to go in and turn knobs and do different things and so forth, contribute clearly to the margin profile of the business going forward.
Our focus on mega data customers allows us to optimize what we're doing there, how we support those customers, how we automate this autonomous platform, how that manifests itself in the support area of the company, how we're focusing consulting around driving consumption of the Vantage platform, which drives ARR, obviously. It's all around the high value, high margin types of things that we're going to focus on going forward and de-emphasizing the lower margin aspects of our consulting business today. That likely manifests itself in less consulting revenue out into 2021 and how we transition from where we are today to where we're going on consulting. The result is the margin profile of that remaining consulting business is highly more profitable, highly more strategic to driving our ultimate overall view across our customer and our customer profitability as we look at that and things like that.
Ultimately, we're also going to end up leveraging more of a partner ecosystem than we've done in the past. We don't need to necessarily do everything we do today. We don't necessarily need to do that. We can leverage some partners to drive some of that as well. That then says our non-recurring revenue margins also start to help contribute here in how we look at our non-recurring business and how that changes from where we are land in and around today to where we're headed, right? That also is a driver, given the mix assumptions and improvement here of how you get your overall gross margins from 50 to the mid-60s. Transforming our go-to-market and our brand. You've seen a lot what we've done around the brand and how we've repositioned Teradata, not only with our customers and prospects. Hopefully, you're starting to see it.
We hadn't done a lot of significant outreach to the financial community on the repositioning of the brand. We started that at Analytics Universe, which some of you attended. Several of you weren't there, but it starts. That's the fourth pillar. We think it reduces operating costs, clearly will help drive revenue, but reduces operating costs, which then manifests itself in better operating profit profile to the business. Around our transforming our go-to-market mega data customers. We're aligning our sales motions to these mega data customers in a much more focused way, allows us to streamline and optimize how we go to market, where we're going to invest. Allows us to take a look on, we have existing customers outside these mega data customers, and they're still important. We're not going to abandon that.
We still have those customers to serve, we think we can do it in a much more efficient model, much more of a commercial-oriented model. Less dedicated teams, more shared team concept, much more like a commercial model versus our true mega company, which is much more like an enterprise model. That obviously lowers cost out of the go-to-market machine. That drags with it the ability for us to look at what geographic rationalization can we streamline, what does that look like, what opportunities do we have to take a look at that, to streamline that, whether it's from a management perspective, an outright country perspective. What are our most profitable countries that we should focus on, and the ones that are less profitable, do we need to be in that market, one? Two, if we do, how do we do it in a more streamlined way?
That also then helps drive cost out of the business. By doing that, the overhead machine behind that is all around the sales support and all the support and care and feeding you have in a company to support your sales organization starts to get simplified, standardized, much more streamlined, creating opportunities yet for lower sales support costs across the company. We're embarking on that as part of this as well. Then obviously, ultimately, the new brand positioning, Pervasive Data Intelligence , clearly is broadening our market opportunity, our relevance in our market. I get asked, how do you guys maintain your relevance in a rapidly evolving technology market?
Vantage is the first piece of that, the brand, as we evolve, Oliver alluded, there's more things coming later in 2019 and beyond, that we think we continue to be that key player, uniquely differentiated, solving problems that only we can solve for the biggest players out there. That ultimately allows our Vantage platform to be the analytics platform for the biggest companies, biggest data companies out there. We do that, it's going to manifest itself in our financials very nicely. All of this drives operating performance improvement, right? Which then ultimately increases operating income. We are embarking on an operational excellence program. Some of that is external focused. Again, how does it help improve margins? It ultimately helps improve EPS and free cash flow for sure.
When we look across these drivers, we have to become more efficient, more automated. We're going to make investments in automation and efficiency throughout the company. Some of that is investments to modernize our systems and processes to more best-in-breed technologies, replacing a lot of the manual processes we do today. A lot of it is how we simplify the organizational structure around the company to be laser-focused on what we're doing on Vantage and growing ARR. We've outsourced certain back-office functions to lower-cost jurisdictions to operate more efficiently and at lower cost, versus saying we don't have to do all of that in-house. From a customer perspective, we've talked a lot about it, we're simplifying pricing, we're simplifying deal structures, we're simplifying the execution to make it easier for customers to buy Teradata.
All of that drives efficiency and cost out of the business. Ultimately, all the things we're doing around the radical simplification as a service that's going to improve margins also helps drive our operating income improvement. Our target out to 2021, 20%-25% operating income in three years. We feel very good about it. It's the one we have the most control over. We can't force a customer to press hard, sign here three times. One thing we can do is manage the cost side of the business. We will do that. Obviously, if we improve our operating margin profile, EPS also improves. We see more than a doubling of our EPS out in 2021 from where we are today. Both 2017, where we land at 2018. That's not through buying a ton of stock back to get us there.
That's on an assumption of the same weighted average shares outstanding we have today, we may have in 2020. We won't, of course, because we'll continue to buy the stock back. This is not being driven because all you guys going out and buying a bunch of stock over the next three years to achieve that, no. It's going to be achieved inherently through the financial performance of the business. That ultimately says, from a free cash flow margin. By the way, the 20%-25% is, we're not plowing new ground here. This business has been in those ranges in the past. It's not like we're going to get there for the very first time. It's very doable. Ultimately, free cash flow margins out to that 20%-25% range as well in 2021 from where we've been.
We don't see any reason why that's not that $400 million-plus level that the company's achieved in the past. Even if total revenue's roughly flat in three years, because you're out of the perpetual business, you've aligned consulting, strategically focused, which means there's less consulting revenue. You're growing recurring. Hey, if 10% growth on recurring and $200 million less in consulting, I'm not saying that's what it would be, but if it was, it'd be around $2 billion. 20%-25% means you got $400 million-$500 million of free cash flow. You guys can decide whether that's meaningful. Do your discounting back to today and determine whether the current stock price is expensive, cheap, fairly valued. We leave that up to you.
We're going to go focus on our strategy, our execution, which ultimately manifests itself in these financial targets. The rest takes care of itself. In summary, what's going to drive our success is clearly Vantage enables a share of wallet increase opportunity. We think it allows us to drive our ARR growth assumptions just focused on our installed base. We don't need lots of net new customers to achieve these targets out to 2021. That opportunity exists right now today in the existing customer base we have in these mega data companies. We're moving away from perpetual to subscription. We're making it easier to buy and easier to consume. Our radical simplification, whether that's on the product offering side, the operational excellence sides of things we're doing. We start to see both recurring revenue, consulting margin improvement that drives overall gross margin improvement.
Our go-to-market aligning, transforming that business affects the OpEx side of the business, all of which then drives to the operating income performance we're laying out. Ultimately, that hits the free cash flow targets. The good news is we don't believe we have churn and huge renewal risk. The subscription ARR, this $400 million I've been talking about, there's not a significant portion of that that's up for renewal in the next two years. Our maintenance-related renewal business has virtually had no churn, so we don't see a substantial risk with that as well. We don't believe we got to worry that there's a significant churn risk here that could derail these targets. Clearly, we think we have plenty of runway to increase our ARR to achieve our three-year targets. With all that said, out to 2021, we are now a complete subscription bookings mix company.
We are mid-teens on ARR growth as well as recurring revenue. Recurring revenue gross margins are mid-70s. Consulting margins are approximately 20-ish, which means gross margins are in the mid-60s. Operating margins in that 20%-25% range. EPS has more than doubled, and free cash flow is in that 20%-25% range. That's our three-year targets. That's what we're driving towards. How do we get from where we are today to there? For 2019, we're going to give you more color on that on our Q4 call. I'm not going to get into specifics today. We haven't finished the full year. However, across our key metrics, ARR growth, recurring revenue growth, gross margin improvement profile, operating margin, free cash flow, we expect improvement in 2019 over 2018. We expect improvement in 2020 over 2019.
Ultimately, we are going to land at these targets and in the range of these targets in 2021. It's not a hockey stick. It's not a little now and a little in 2020, and then bam, you get there all in one fell swoop. It's not perfectly linear either, but there's measured progress across the metrics over each of the next three years. We're bullish on where we're headed and what we're doing. It's why the company has bought back a lot of stock in 2017, $350 million, bought back a lot of stock in 2019, $206 million through the nine months, and more in Q4. We'll see where it ultimately ends up.
Because we're bullish in where we're headed, we believe in the strategy, and we think our excess cash is best used to go drive return value to shareholders through stock buybacks, because we're bullish that we believe in 2021, the profile of the business, the valuation of the business is dramatically different than what it is today. With that, I thank you for coming. I'm going to ask Vic to come back up. Obviously, we will update you on the progress over this next three-year journey. It's a journey. It doesn't happen overnight. The nature of our business is very evolutionary, not a transaction with our customers. We're going to be with them all along the way, and not just one big fell swoop and then walk from these customers. That's not the nature of the relationship we have with these biggest customers.
Vic, I'll turn it back over to you. That's the presentation stuff. We'll do Q&A in just a minute. Last night when I was wandering around, a lot of folks asked me, said, "You seem happier than you did two years ago." The answer is, yes, I am. I'm much happier than I was two years ago. You've heard we have clarity. We have a great team. I've done transformations before, part of that is we see all the stuff earlier than you do, right? We see what's happening. We know what's going on. You can lead through change, if at the end of the day, you turn around and you're out there by yourself, you failed, right?
The idea of successful change is you have to bring along a team who can do it, that team has to include everybody in the company. When I first showed up here and I'd wandered the floors, it was pretty quiet, pretty dark. A lot of questions about, "Are you here to sell the company?" It doesn't happen today. I get emails lately that just stun me about how excited people are about Teradata. Our folks are with us. Our customers are with us. In this transformation, we had the number one thing you need to be successful, customers who appreciated what we wanted to do and wanted to do business with us and are grateful for the change we're making. I can tell you that I am 100% confident in what we're doing here.
I know we've carved out a market that nobody else is after right now. Do I expect somebody else will come along? Absolutely. Do we have competition today in some areas? Yes, we always will, we always have. Instead of being a victim, our role is to be an aggressor. I always have a visual, I tell the organization about it. I carry back and probably, I don't know, half of you in the room probably aren't old enough to remember Indiana Jones movies. There was an Indiana Jones movie where Indiana Jones comes out this guy comes out, this huge guy with a sword, he's swinging around and screaming and yelling, Indiana stands there for a while and pulls out a gun and shoots him in the head. I like a pistol. I'm not very fond of swords.
We have to have the attitude about having clarity around who we are, how we win, make sure we are totally focused on that, we communicate to our people. I can tell you we're going to do that. We're going to win. We're going to win along the lines that we talked about. I've said before, I think there's a huge difference in an organization between confidence and arrogance. Arrogance is death, confidence is what you need to succeed. If you do not believe you're going to win, you won't. You cannot do what you don't believe you can do. I found over life, if I believe enough in things, almost anything. I crawled on broken glass for a long time before I got my wife to say yes, she'd marry me, I stayed at it until she did.
We've been married tomorrow 50 years. I know what we're going to do here. I know there are skeptics in the audience. I understand we have given you, Teradata has, over the years, a reason to be that. We understand the world's changing. Our job isn't to follow, but to lead, and lead in ways that we have core competencies in. With that, we're going to do some Q&A. I'm going to ask the presenters to join with us here, and we'll take whatever questions you've got. I guess we have to get our own chairs, too. I don't know. There you go. You'll have to talk loud.
This one's like this.
Okay. You get in so I don't sit out.
Get out there. Yes. Okay. All right.
We'll have a couple of mics in the aisles here. If you don't mind, if you'd state your name and the firm you're with. We'll start with Karl, right up here.
Great. Thank you, Gregg. Karl Keirstead at Deutsche Bank. Great presentation. Thank for hosting us. Mark, thank you for all the details you gave on the outyear targets. That's super helpful. I'd like to zero in, if I could, on the assumption that to get to those 2021 targets, Teradata is not going to see significant churn. Clearly, you've got a number of ELAs that are coming up for renewal over the next two to three years. If I could just press, what gives you the confidence that you're going to renew all those ELAs and your customers are not going to shrink them as they move to cloud-based alternatives? What gives you that confidence?
Let me take that first and then maybe Mark can give some more color on that. It's back to our strategy and to the track record that we have seen over the last two years. When we launched Teradata Everywhere, there were a lot of unknowns. When we went to the customers and we saw their reaction, we saw a change in behavior. We saw that they really appreciated that new look that we took in terms of what Teradata is, and they started opening up and telling us what they need next, which led ultimately to Vantage, us releasing Vantage, right? There's a very clear message coming from our customer base in terms of what they expect us to deliver for them, and Vantage is that next step, and we are talking about that there's more coming in 2019.
We've also renewed several of these ELAs and other things in the last two years, and we saw what happened in these cases and how we have dealt with that, right? This gives us the confidence that overall, where we are coming from, we feel that there's a very strong base, very strong renewal rate. It's never going to be 100%, right? It is not something that is a big thing that we worry about because that increased focus, that increased functionality, starting with Teradata Everywhere, going to Vantage, it's what's creating that interest. At the same time, it's these executives that are telling us they actually need help simplifying their infrastructures. Mark, you want to add something?
Yeah. Yes, I would just echo that historically, we haven't seen it. That doesn't mean that that's necessarily a perfect predictor of the future. However, our customers and where we focus have told us explicitly, "This is a hybrid market for us. We are not going to take and lift and shift things we're doing that are mission-critical at the scale that we need it done and move that to the cloud anytime soon." We said we understand that. The hallmark of Teradata Everywhere strategy is if you have those software licenses on a subscription, you get the portability. You have the ability to move it to the cloud when you want, when you need to do it with the same, not a single change in a line of code, as Stephen mentioned earlier.
If there's an assumption that this is going to move all to the cloud and we're going to get run over by the cloud-native companies, I respectfully submit, I totally disagree. We offer our customer base choice for the cloud today. They are not choosing to go do that today, but in the future, if they want to, we have an option for them to do that as well that is seamless for them, and that was one of the key tenets and hallmarks of Teradata Everywhere. That's why we have confidence. We don't think we see a significant churn risk, specifically given the scale that only we can perform for these biggest customers.
Okay. Wamsi?
Thanks. Wamsi Mohan, Bank of America. Appreciate the details on the presentation today. I was wondering, your traditional go-to-market looks like you might have to change that in some meaningful ways over here, given your strategy is much more aligned at sort of having discussions at the C-level versus maybe more with the IT side before. How are you thinking about this go-to-market? How much more of a partner dependence or SI dependence do you expect over the next few years, and does it change your economics as well when you do that? Thank you.
Thank you, Wamsi. Let me take the first part of that. We talked about our strategy being focused on these mega data companies, right? We started talking about top 500 two years ago. We've learned a lot along the way. We have improved our go-to-market model along the way. We've introduced new ways of strategic account planning that traditionally we haven't done. We have learned how to address C-level executives and how to listen to what their strategic needs are. Is there more work to do to get there? Absolutely. We can now build on the learnings of what we have done in the last two years. We will continue to fine-tune that.
As I said before, in the strategy this year, we have further segmented the mega data companies, and we know how to differentially treat these segments where most of the growth of ARR within these segments will come out of. That means where we will spend most of our investment dollars in terms of driving that growth. Ultimately, we just feel very solid that based on the experience and based on that increased focus and the feedback that we're getting from the customer base and the successes that we have landed and the customers we have converted, that we are on the right path to do so. We know what the next steps need to be, and you will see us focus on that.
In 2019, we'll further fine-tune that and align the incentives of the leaders of all of our people very solidly behind that go-to-market model that covers these mega data companies, while at the same time also taking care of all the other customers that we have, but in a different commercial inside sales type of model, which also we have tested over the last two years with great success. That gives us a great coverage model, I think, to go into that.
I'd say that the other thing is the focus on "answers" as opposed to the plumbing allows you to have different conversations with different people in the organization. Focus on the people who are creating outcomes, who are creating the business value. Those are the people that actually have the budgets that will grow the consumption of Vantage as opposed to the plumbers.
Keith?
Hi, thanks very much. It is Keith Bachman from Bank of Montreal. I wanted to ask you on Vantage, how much has been new technology innovation and will be to technology innovation? The context of the question is many times over the last number of years, companies, when they face new market dynamics, make declarative statements on strategy change without real change in products underneath it. I did attend the recent customer event in Vegas, and I think there was, in my perception, general confusion around what Vantage really is and what has changed. In the past, Teradata has actually had strategies identified where the data warehouse was a node in a network and trying to get the middleware activities. I am still a little bit unclear about what is new in Vantage from a technology perspective.
When you are going to customers, they say, "Okay, there are new APIs or there are new things." They are actually writing checks for new products. If you could just talk about what the underpinnings of technology are today and what they might be. Thank you.
I think we are going to have Rima tell us a little bit about the integration that we have done there. There is a lot of innovation happening in that space overall. Rima can tell us more in detail what that is. There are also technologies that we have simply integrated that we have. It is a mix. This is not brand new. As Rima said before, we are building on a core that we have. Ultimately what you are seeing, and Stephen can comment more on that, in the use cases, it is that bringing together that simplification together with new things. This year, we added things like time series support, like 4D Analytics that Teradata never had before. There is brand new components together with bringing together other things. Rima, by the way, she probably managed the largest cross-functional team that we have ever had in Teradata to make Vantage happen.
Rima, maybe you can tell us a little bit more about that.
Yeah. Thank you, Oliver, and great question there. It's a matter of obviously existing and new innovation Oliver mentioned. We have also proven that through 4D Analytics. Let me take a moment to explain what Vic and Oliver continuously said through this whole session. Our focus is to really make sure that our customer is successful. What does that mean? It's not just through technology. It's through how we bring automation into the mix to provide, shorten that overall downtime for our customers. That means you have to instill innovation, not just with technology, but looking at the end-to-end process and say, "What are the timelines that it takes and what is the creativity we can apply through automation?" Taking that manual effort out. That means it is not the planned downtime alone, but even the unplanned downtime alone, because that's cost again for our customer.
Shortening that, it is making them successful and us successful in turn. That's one. The second one, we are creating innovation within ourselves, within our company. We have come out with concept of test as a service. Like you heard a customer speak, I also alluded to the fact is how can we reduce the time taken to build, test, and deploy? We are applying that same logic within our existing operating mechanisms to reduce our time taken to build answerable outcomes for us and for our customers. In an effort not just to use it internally, but to hand it to our customers so that they can use that test as a service as a tool to reduce their regression cycle.
Creativity is not just through technology. The innovation is not through technology. It's also looking at means of how we are improving our processes to deliver quicker results.
Let me sort of directly answer your question. What is the difference between the Teradata database and Vantage? Teradata database, there's still a foundation there and it's a component of Vantage. These analytic engines, which are again, containerized and delivered as services with the extensibility, that's brand new. That did not exist before, right? One of those engines is a machine learning engine that's actually, in some sense, a repackaging of what Aster did, but with the separation of the analytics and the storage. Then there's engines which are completely new, which we'll be delivering next year, like for example, TensorFlow and Spark from the open source community. This would not have been possible if you just think about Teradata as a database. It's fundamentally different.
Okay, Katy?
Thank you. Katy Huberty, Morgan Stanley. Just a quick clarification to follow up on the last question. What does the revenue model look like for a product portfolio? Does Vantage supersede IntelliFlex, or is it an add-on on top of the core that you're selling? Can you just comment on that? I'll ask my question, which is, coming into this year, you had a goal of signing some tens of new logos. Can you just talk about where you are in meeting that? Is that even the right way to think about the business? Because Mark, you sort of de-emphasized the need to bring on new customers. On the other end of the model, do you have any metrics?
Do you track, I assume you do, what market share is in the wallet share of the installed base, and what a reasonable goal of wallet share would be on an annual basis going forward?
Maybe let me start off with the Vantage versus IntelliFlex question here, right? Our strategy is clearly to move beyond hardware, or so to speak, away from hardware as a meaningful building block in what we are doing. Vantage, on top of Teradata Everywhere, of course, will always run on hardware. The cloud is built of hardware. Yes, we need to have the expertise to optimize Vantage to run best in the various different platforms of cloud. Yes, we have, by now, a very simplified IntelliFlex platform, by the way, that since the middle of this year, the latest iteration of IntelliFlex that we released is no longer custom. It is now a very standardized software-defined, just behave just like the cloud, because it allows us to abstract away from that. Our business model is removing hardware more and more from the conversation.
It's about the subscription, it includes all the as-a-service and all the hard work that you need to run, whether it's in your own data center or whether it's in a public cloud or in our cloud. The focus is shifting from hardware as the center of the universe, which it was for Teradata five years ago, to an, yeah, of course, there will be hardware and an enabler in somebody's data center, but by us simplifying that, there's less focus on that. The conversations nowadays that we have with customers are tracking with that. We are having way less conversations about hardware boxes anymore, and much more about the capability of something like Vantage, right?
Teradata Everywhere, so to speak, forces us to abstract away from the hardware because you have choices where you want to run this, you don't care what the underlying hardware is. By the way, if you look where the whole industry is going, if you look where other cloud providers are going, everything is going away from hardware because hardware just has complexity and nobody wants to deal with that, right? That's a big part of our strategy is put software subscription consumption first and enable that through whatever is the best possible platform in the different deployment choices that we have. We work very closely with AWS as well as with Microsoft Azure to help them test their infrastructure, scale out their infrastructure.
A lot of learnings in the last two years when we first showed up at the doorsteps of the public clouds, we literally took public cloud data centers to their knees because they've never seen software run so efficient and extract so much out of their existing hardware than they have. They are very fast in learning that, it has helped us scale in these environments, right? De-emphasis on hardware, focus on answers, focus on Vantage as a subscription offering and soon to be a consumption offering in 2019 that we said.
To reinforce, Vantage is the new version of Teradata. It's broader than a data warehouse, it's only sold via subscription.
Yes. Very good.
Your question was sort of what share of wallet do we have inside our existing customer base, and how do we think about that? It's basis points. It's not 1% across our installed base customer. Across our focus, we have probably less than 1% wallet share today. We think it's an enormous opportunity to grow that spend inside our existing customer base. It doesn't mean we're not going to focus on net new logos into the future. It just means I don't believe we need to land 50 new logos every year over the next three years to achieve these targets. These targets are not dependent on a huge driver of, you got to go get a bunch of new customers to do it. We don't. That drives upside to these targets, we believe.
Maybe to add one more thing to that. Yes, we signed net new logos. We have de-emphasized on reporting out of that. Yes, we hit the goals that we had for the year in terms of new logos that we wanted to sign up.
Derrick?
Great, thanks. Derrick Wood at Cowen. Could you give us a sense for how easy it is to transition to Vantage from a technology adoption standpoint? Then Mark, you've talked about revenue uplift when maintenance to subscription, and when you go to a subscription contract. Since you're talking about Vantage being a broader platform, do you think that that's going to provide more of a revenue uplift at initial deal? Is pricing going to change at all from being based on TCore? Is it still going to be TCore priced?
Maybe on the first part of the question. For the existing customer base in the mega data companies, the adoption of Vantage is very simple. That was a big part of what Rima and team have driven to make that as transparent, as easy as possible compared to what we have done in the past. By the way, our customers have been telling us very clearly, "A weekend of downtime to upgrade systems? Sorry, doesn't cut it anymore. I don't have that." A lot of that innovation, by the way, went into some of these things, whether it's elasticity, whether it is getting into Vantage. For an existing customer, that is very simple to adopt.
For customers that don't have any Teradata technology today, we have migration services that we have built over the years to help them when they have a Netezza box or when they have a Greenplum box or when they have dot, dot, any of these services to get that data on it. What we are seeing, by the way, is now customers coming and even saying, "Hey, I put a couple of these cloud instances out there. Can you help us consolidate them back into a Vantage instance? Because by themselves, that felt very easy, but now they become very painful for us to operate and run on.
What we've historically seen, if a customer is completely converting off all of their existing perpetual licenses to all subscription, we've historically seen that be one and a quarter to 3X uplift, depending on how many additional software are they buying. Into the future, given Vantage, over time, I think we have the opportunity for that to be larger. I don't know if it's larger than the 3X in the initial transaction, because again, this isn't a transaction-oriented kind of thing a one time. They will iterate and say, "Okay, we're moving off a couple of these. We want to put them on Vantage." Then six, nine, 10 months later, they're bringing more to it and more to it and more to it, particularly in a consumption-oriented model.
Yes, over time, you could look at that and say, "Hey, I think we probably could do better," but I don't know if it's in the initial fell swoop, the initial adoption of it, do you see that? We're not telling customers, "You don't have to give up your perpetual licenses. Keep them, continue to pay that historical maintenance. Happy to have you do that." You don't have the portability aspects for those, the ones you do on subscription, and we'll wait till the customers come back to us and say, "We'd like to convert all those," versus try to lead and convince them to do it. To your last question, is pricing changing? Yes. Pricing for the software side of what we do, given what Vantage drives, is changing coming January 1.
Zane?
Thanks very much. Zane Chrane with Bernstein Research. Great presentation today. I was wondering, as far as your ARR forecast through 2021, how much of that do you expect to be coming from conversion of existing workloads inside your current customer base versus new workloads that those customers are building that are maybe being enabled by the new technologies with Vantage? Separately, would you ever consider giving a renewal rate on a quarterly basis? It seems like your churn rates are very low based on the ARR you've been adding. Just to make that more explicit, would you maybe consider giving the churn rate on a regular basis? Thank you.
Again, on the first part, on the ARR growth, is it driven by conversion versus new workloads? We see it primarily by expanding and new workloads that are happening. These types of workloads that we saw some examples here today even. These are workloads that were previously done off platform, that were previously done in other environments, and that are now starting to come into this environment because of Vantage. Also, as some of these companies are growing, they need more because they have all of a sudden more sources, IoT. We talked about new types of analytics that we have brought in there. We believe that a healthy part of that ARR growth will be new and expanded use cases of even some of the examples that Stephen shared with us.
In many cases, those expanded use cases are reusing the same data that they already have, which means that it's relatively rapid to actually deploy the new capability.
Tyler?
Hey, thanks. It's Tyler Radke from Citi. It seems like you've been pretty pleased with the overall bookings performance this year. You had upside to your subscription mix targets. I think, Mark, you talked about a 55% increase in backlog in the most recent quarter. My question is, given the strength, and you kind of have this strength in a year where you've been comping on TCV, and sounds like you have a pricing change that's been previewed to the customer. How much of that strength has been prepurchasing in anticipation of this pricing strength, and what gives you the confidence you can accelerate ARR next year? You do have the change to pricing, and reps will be compensated on ARR versus TCV.
We actually think that quite the opposite is happening. There's no pre-purchasing happening because the customers are telling us they want to buy more just-in-time. A.k.a., this is the consumption model that they're asking for, right? They don't want to pre-purchase, we have taken the go-to-market organization away from that concept of let's pre-sell as much as possible for X years of capacity, because we don't think that's the right way to look at that, right? Our customers want answers, they want flexibility. They want to do it just in time. None of the actions that we have taken are those of pre-purchasing something. Yeah, TCV leads to longer contract terms. Yeah, got that, but not to more peak core consumption up front, right?
We believe that the position that we're coming in with and the switch in the go-to-market to a focus on ARR will be a healthy driver for that in 2019.
Pre-purchase is kind of old style way of buying.
Yeah.
What we see when customers move to consumption-based, they actually grow faster because then they're sort of not buying a box, then trying to fit in the box. They use what they need to deliver business value, and there's no box, there's no constraint.
Jennifer?
Thank you. Jennifer Lowe from UBS. I just wanted to follow up a little bit on Vantage and going to Katy's question about new logos. I know that that's sort of a secondary focus versus growing wallet share within the existing, but it seems like with something like Vantage, you know, if you get into a new customer, they're able to extract data out of their existing data assets in addition to new Teradata investments, maybe faster with something like Vantage. Is that a scenario that you could see playing out where, you know, because you're able to get so much value with Vantage out of existing non-Teradata assets, maybe it drives those deals a little faster?
I would say that actually sort of the opposite in the sense that the customers that are already there and already have the data, it's much easier for them to use Vantage because the data's already there, and then they exploit the data, and they create value, and that drives sort of the consumption, right? Somebody who's not a Teradata customer who doesn't have a strong foundation, it takes them time to build up that foundation. Again, that's very important because that builds future pipeline of growth and so on. If you're talking into the point of your question, what's going to be faster? It's going to actually be the customers who already have lots of data there, and they're just finding new ways to exploit that data. That's my opinion.
Hence our focus on share of wallet, right? Having said so, the conversations are absolutely starting with the prospects in that space because they have the same pain points, and they are now seeing that other customers are getting those benefits, right? We will never be in a rapid-fire, quick sales cycle environment. These are mega data companies. These are large-scale environments, right? Does Vantage make it easier compared to what it was before? Yes. Will a consumption model make it even easier than what it is today? Yes. We are layering in the right things, let's make no mistakes. We are dealing with the largest multi-multi-multibillion-dollar companies in the world. For the scale that we operate, again, not just turn on a departmental small little system, but to help them simplify a much larger architectural thing, that will take time.
It takes time, it's something that we are used to. Having said so, the de-risking part of Teradata Everywhere, the de-risking part of Vantage with the existing customer base is certainly something where we're seeing, okay, they're faster making decisions because there's less risk to that decision for them.
I'm going to step back just a bit, okay? Because we have at Teradata the Vic standard, right? If we can reduce the explanation to where Vic understands it, everybody in the company gets it, right? I try to think about why is this different, why do people not. Let's take Vantage and what is it, why is it different? I think it's important for everybody in the room to get away from thinking about what Teradata was and what it is. This platform is a platform, I think about it in real simple terms, and why it's key for us. The ability to ingest data from everywhere, not just from our Teradata platform and process on it. The ability to use multiple engines to do that. A platform to develop analytics on the top.
It becomes something that you can ingest data from everywhere, not just what we own today to drive analytics. We allow expansion and increased rate of analytics development because you have a protocol that's consistent. From a business perspective, it provides access to a broad field. You heard the discussion that we had a little earlier from the customer about the ability and what it does for speed to have one source of the truth. That is incrementally powerful and profitable for our customers. That drives business outcomes in the way something never does. We don't have to think about things the old way. We don't have to go in and make them put everything in Teradata. That's not what makes this successful.
It is the ability to extract data and solutions from anywhere in the world and put it in a common platform to drive quick outcomes for our customer. Very different than what we've been, okay? A lot of the things we're doing, the other comment I want to make about new customers and all that, it's great. Remember, we're in a transformation here. You know, it's like the old saying, it's hard to remember the objective was to drain the swamp when you're up to your ass in alligators, right? We have to make sure that as we move down the road, that we are ready for that. We have to get. We got our existing customers, we get them, then we're going to grow onto the new ones.
It's important that when we go out as Teradata and execute against our strategy, that we do what we've always done, and that's kick ass and do exactly what we said we're going to do. We've got to be prepared everywhere we go to show up as Teradata. We don't want to show up as somebody who comes in and throws software in their lap and says, "Go find 15 SIs and come in and make this work." That's not who we are and not who we're going to be. It's important to think about the new Teradata. I know what we always did, the kernels we got, all of that's great. It's what makes us live long.
A lot of people say, "How do you know you're great?" I said, "Because we've been around 40 years, we've got competitors that are 18, 20, 40 times as big as we are, and they haven't killed us yet." We must have something, right? I don't understand the technology, but I know it survives and wins, and our customers like what we have. Thinking about that new Teradata, what we have is part of it, but it's not where we're going. It's why this is so unique and different. I have to stand back at times and think about exactly what does that look like. Everybody's tired, I draw a triangle, right? On the bottom is ingestion of data. The ability, and Reema's working on this, to cleanly ingest data from multiple points, that's the Holy Grail. Ask anybody.
If I can ingest clean data from any data point into a platform, that's the Holy Grail. A common protocol to develop analytics saves it. It reduces cost, complexity, and risk. That's how I think about it. That's the Vic explanation of where we are and why it's different. Technology is a part of it's key. Why should we do any different than what we tell our customers? We tell our customers, drive answers through Teradata analytic platform, technology-supported business outcome lab, right? That's what we're doing in our own product. Technology supports it, but we're driving business outcomes. I don't know.
Pri?
Hi, Raimo Lenschow from Barclays Research. Two quick questions. The $400 million in ARR, is that a pure subscription ARR or does that include cloud upgrade rates and cloud? Second question, when you move to a consumption-based pricing, how does that affect pricing? Is it still that 1.25x-3x uplift?
The subscription-based ARR is subscriptions. That's not maintenance software rewrites, whatever. It's everything on a subscription contract, whether that's deployed on-prem or in the cloud.
The second part of the question was, help me.
It was about pricing when-
Oh, yeah. The consumption model, right?
Right.
Early indications in our work that we have done there is that consumption model actually accelerates consumption of Teradata Vantage. The pre-work that we have done and the tests we have done with customers show that it's a potential significant uplift on CAGR in terms of their adoption of that technology, because they're no longer bound by capacity boundaries, but they can, at a moment's notice, consume just in time what they need, and that usually leads to more experimentation, and that usually leads to more outcomes that then drive more consumption of the platform. Okay. We told you we would get you out of here before noon. I do know we have a number of people in here who have flights they're trying to run to. We'll probably conclude the Q&A here.
We do want to thank you for coming, your participation both here in person and on the webcast as well. Please stay tuned. We've got some exciting things going on here. We're looking forward to reporting our results in several weeks here. Again, thank you for coming. We do have box lunches outside the room. You can take those and go, especially for those who were on the run. Again, thanks for joining us.
Thank you.