All right. We're going
to get started. Thank you everybody for coming. Thank you to everybody that's on the webcast. For those of you that don't know me, I'm Rick Lunde. I head up Investor Relations And Corporate Development here at Veeva.
Please don't hesitate to reach out at any point today or in the future, if you have questions or if you need anything, I'm always available. Before we jump in, just a few quick logistics, We've got a pretty full house today. So please just be accommodating if any folks come late, try to make room for them to find a seat to sit down. A quick reminder, please silence your cell phones if you haven't yet. If anyone needs to use the restroom, it's just out the door past the food and to the left.
And then finally, please hold all questions till the end. We'll have kind of a consolidated block of time with everyone on stage. For Q And A at the end. So just a quick look at the agenda for today. We've got a pretty good lineup.
We're excited to deliver it to you. And before we jump into that, Bear with me for a minute while I read a quick disclaimer. Okay. During the course of today's presentations, we will make forward looking statements including statements regarding trends, our strategies and the anticipated performance of our business. These forward looking statements are based on management's current views and expectations, and are subject to various risks and uncertainties.
Actual results may differ materially. Please refer to the risk factors included in our most recent filing on Form 10 Q, which is available on the company's website at veeva.com under the Investors section and on the SEC's website atsec.gov. Forward looking statements made during today's presentations are being made as of today, October 4, 2018. If the presentations are replayed or viewed after today, The information presented may not contain current or accurate information. Veeva disclaims any obligation to update or revise any forward looking statements.
In the presentations, can be found in the appendix of today's presentation, certain results have been adjusted to reflect the application of I will pass it off to our founder and CEO, Peter Gasser. Thanks for coming.
All
right.
Thanks, Rick. Welcome, everyone. Thank taking the time to be here. And thanks for your interest in Veeva. All right.
Let's start it off. We'll start off by showing you our vision and values. This is how I manage Veeva. That management team manages Veeva. I show this slide many times every quarter.
I would say definitely more than 20 times start of every board meeting, significant management team meeting, company leadership meeting, company call, customer summit, significant customer meeting. It's really an operational thing how we manage Veeva. And vision, that's what we're doing. It helps keeps us aligned and grounded, and the values are how we make decisions along the way as we pursue our vision. So our vision, building the industry cloud for life sciences, that means we're making cloud software, data, professional services, and have a network partners to complete our solutions.
We're bringing that all together to help the life sciences industry become more efficient and effective And we think by doing that, we're going to help bring the right medicines to market and get them to the right patients. We're going to do our part. That's building the industry cloud for life sciences means to us. Now our values, that's how we make decisions and the very operational. It starts with do the right thing.
That's a moral thing. Treat others like you would like to be treated, do the right thing for the customer, the employee, society set an example of what a good company should be like. And that's our number one value. We take it very seriously. Customer success has a specific meaning inside of Veeva.
It's for the people in the companies, like the person that works at Pfizer, the companies themselves, So the company like Pfizer, Novartis, etcetera, but also for the industry, the life sciences industry. Success for the people is they have to enjoy working with us. They their projects that they depend on us for have to come on in on time. It has to be a good partner For the companies, our products have to deliver our ROI. They have to be on time, on budget and deliver what what we say and they have to get better over time.
And for the industry, success of the industry is about getting more efficient and effective. More of the right medicines made delivered to the right patients. That's what customer success means to us. Employee success, our next value, that's about our employees. And we have to provide them an environment where they can contribute, but also learn where they can be challenged and respected.
And we have this model that we call Captending Your Own Shipt. That's we are about each employee, taking things into their own control, having the right level of autonomy, and finding the place where they can contribute the most. There's not a lot of rules around things about employee success. And I measure it actually at the end of somebody's career of Eva. Do they, when they leave or tire whatever?
Do they have a sparkle in their eye? And they think, Hey, that Veeva was a good one. And that's if you look at my job, that's probably the most reporting the most I don't know what that one is. Sorry. So that one is that part is probably the most rewarding part of my job when you get right down to it.
So employee success is something we take seriously. And speed is about getting things done today rather than tomorrow. Getting back to customers quickly and completely, making a decision and moving on. And this is the one that's super hard to maintain as you get bigger. And this is like fighting against gravity.
It was very easy when we had 2 or 3 people in the company because, man, speed was all you had, right? Now we have over a couple thousand people and we have to retain that speed, retain that speed. So this is our vision and value is very operational part of the company. Some key highlights of the things you'll see today. You'll see about how we're continuing to innovate, and then across all of our products, how we're bringing out products in new markets to expand our TAM, how we're making the right things to be the long term leader and like in a few of our areas, the commercial area, the R and D area of life sciences where we're very established, and that's going to be great for the industry and great for Veeva.
You'll hear about our unique cloud platform Veeva Vault and what its unique things are and why it's important. And then you'll hear about our business model. The Veeva Way, how we go about running our business. So we start off with the Veeva Way. This is our operating model, how we run the business And it starts with picking the right strategic markets.
We have a process for that now. I can tell you when we started the company in 2007, we didn't have much of a process of anything. Right? We said, let's try to do this. And, you know, and then we, we went after it.
Now we are in multiple markets and we have a process. How do we assess this strategic market, is it clear? What are we making? Who are we trying to make it for? What could we sell it for?
How many of those people are? And how much would it take to make that product. So we think about it a lot and then we commit to it. And we stay after it in the long term, and that means bringing innovation whatever product area. Don't just do the same old thing.
Bring innovation, innovation, innovation, and stick with it over the long term to have product x on. So we don't want to go into a market unless we can have the best product in that market. That might take 10 years, right? And that's okay. That's the discipline when we did at the very first part of the company, we always said product excellence.
And what that means is don't have too many products But whatever product you have, make sure it's excellent. And the key thing from there is don't say yes to too many products. You got to only say yes to a few. So we make great products. We get them into customers early.
We get that early adopter experience, get that feedback, get the customers live and successful. And then in evangelical, we use that for reference selling. So our customers that are live and successful, especially inside of an industry, are very to help our selling model, keep our sales and marketing expense down to reasonable level. That ensures strong growth and profitability. We use that to invest in the next strategic products.
And that's what we've basically been doing at Veeva for 11 years and what we continue to do. And we like it. It's good work. This leads to good financial results. You can see, we're a eleven year old company.
We've had 9 years of consistent high growth and profit. Operating margins north of 25%. He's a very great results and thanks to the whole Veeva team that made these great results. Today is about understanding a little bit of the why. How do we make these great results?
How do we plan to have great results in the future? If you look at the business, there's really three areas. There's the commercial cloud that's selling into the commercial side of life sciences. The the sales and marketing side. There's the development cloud.
That's our products on Veeva Vault that is selling into the R and D side of life sciences. And then there's outside of life sciences where we have quality 1, selling into industries other than life sciences. We started the these areas of the business in this order, 1st commercial, and then development cloud and then outside of Black Sciences. And that's the order I'll talk about them. Inside of life sciences, it is important to understand this that we have systems, our development cloud for drug development, our commercial cloud for commercial systems.
We're the only vendor that sells cloud technology into life sciences that has serious and significant offerings on both sides, the drug development side and the commercial side. And these are the important things for life sciences companies. They need to bring innovative new products to market, get them through the drug development process, get them approved, commercialize them, before the patents expire. That's the life of a life sciences company. These are strategic areas we're the only company that has offerings in both of these areas, technology offerings, comprehensive ones, it makes us the most strategic vendor to life sciences.
That's something we set out to do many years ago, and I feel that's something that we are achieving now. Okay. Now we'll go into the commercial side. Our main offerings there are CRM suite and our commercial vault. CRM suite that started with Veeva CRM, built on the force dot com platform.
And now we've surrounded that with a suite of products that help complete that set of products. And that's what you'll hear from Paul Shawa about the CRM suite. Commercial Vault is our Vault application, promo mats, Medcoms. This is a way to create content used in the commercial and medical area, approve it medical, legal, regulatory review and distribute it out to the many places that need that content. And again, you'll hear more about that from from Paul.
So these are our two areas. And if you look at how we've innovated in commercial, there were really sort of three blocks so far. 1st, 2017, we had Pharmaceutical CRM built on salesforce.com specific for the U. S. And we're trying to make a go of it as a startup.
We did that. And then in about 2009, 10 or so, we took that globally with CRM. That was a hard thing to do. A lot of specific requirements in the global CRM. No company had ever done that before.
Had a CRM system that is that works really well globally inside of life sciences. They had specific ones for different regions. So we set out to do that, and we've done that. Then we put the suite together with other applications, network aligned, open data events. We've done that and we're taking on the integration burden for our customers If you look at what's next, the next major phase in commercial, the next wave, that's about AI and data science.
That's about 2 products we call nitro and Andy. Nitro, we and Andy we introduced last May at our Commercial Summit, Nitro is available for early adopters today. Andy is our AI offering. That will be available at the end of next year. So those are early days about what's next.
When I talked about product leadership and product excellence, that takes time. You start out with your innovator you move to your early adopters, early majority, middle majority, late adopters, your market share goes up over time and your product gets better over time. In commercial, we have CRM and our closed loop marketing system and ProMats. Those are clearly in product leadership positions. There, we have over 50% market share on both of those for core CRM and for core promo mats.
And our focus there is to be the leader and liked over the long term. These are our franchises. And CRM, particularly, is our home state. That's where we started. And the whole CRM team knows their mission of leader in light.
And I'm really proud of them, bringing that through. The majority of the world's pharmaceutical sales reps use Veeva CRM, and we want to make that better and better all the time. And you'll hear about that from Paul. Then we have like Engage and Nitro, which are way over in the early adopters and innovator side. Our idea is to move them from the left to the right, And it takes time and it takes persistent effort.
There's no shortcut. At least I haven't found it in my 30 years of software. So now let's look ahead. I'm going to focus in on the Nitro and Andy for commercial. What we're doing there is that's really the next wave in our commercial products.
It all starts on the data layer. And that's what Nitro is. It's a commercial data warehouse. We are making a package commercial data warehouse where we bring all the data for life sciences in, in a very simple easy standard way that's built on Amazon Redshift. So we get the data together because AI needs data.
AI does not operate without data and it needs clean data. And the engine will sit on top of Nitro And the way to think about Andi is quite simply, Andi is an artificial intelligence engine, it should wake up every day and think, okay, Doctor. Bob is a customer of this life sciences company. Is there anything that this life sciences company should do with Doctor. Bob today?
And in many days, the answer will be no, nothing to do. But in some days, it might be, I should send a suggestion to this field person at the pharmaceutical company to do something with that Doctor. Bob go to see him, send him this email, reminding him about this piece of content, invite him to this event, send him a reminder that he's going to be at the speaker meeting, whatever it is. But also, Andy may send things directly to the customer. As well on behalf of the pharmaceuticals company.
So it's the one to one marketing done at a very intelligent level. And we think this will revolutionize, really, how sales and marketing is done inside of life sciences over time and it should make every pharmaceutical sales rep more productive. And we feel good about that. That's going to help get the right products to the right patients. It's actually an important issue.
Not all the times are the right products prescribed for the right patients because it's difficult. There are millions of doctors around the world. There are many products. There are many indications Things are getting improved all the time, new clinical trials. How do you get that information flow to happen as fast as possible?
It's the amount of data needed to do that is overwhelming for a pharmaceutical field person. They they cannot consume all that data in all that order. That's where AI can help them. We feel that Andy can make the pharmaceutical sales rep of a company helped to make them as good as the best pharmaceutical sales rep in that company. Give them the tools they need to do the job.
So we're very passionate about this one, and it is definitely the next leap in commercial. So if you look at then go over to the development cloud, that's where we build our products on the Veeva Vault platform, and we have a comprehensive set of things here, all the way from clinical data management to our new safety product, regulatory quality and manufacturing clinical operations. It's a really comprehensive set of applications that no other company has. Henry Levy is going to go into the details around here I'm going to talk to just about the high level status where we're at, and then I'm also going to talk about some of the futures in this area. So innovation in the development cloud is really done was done in 3 phases.
We started developing the Vault platform in late 2010, we brought out our 1st R and D product sort of late 2011, and they were content management applications. To manage your electronic trial master file, your quality docs, that's about your standard operating procedures, your regulatory submissions, So it was content management applications. Then we brought out data oriented applications to manage your quality management system your product registrations, electronic data capture, clinical trial management, and data applications, all in the Vault platform. That's the real uniqueness of the Vault platform. So that was the 2nd wave And now what's next is a whole set of new applications on that platform, really completing the picture, things like publishing, training, our safety applications, turning our EDC system into a full clinical data management system.
So we're, as you can see, we're much earlier in the development cloud than we are in the commercial cloud because we started later and it's very comprehensive. We're in the early days here, We're attempting something that no other software company has attempted inside the life sciences. I feel, what we have to do here is really, really execute on it. If you look at the how we're getting to product leadership in the development cloud, really, we're early. We have our ATMF product, probably our first product that we announced.
It's in the middle majority area there. It's still got a lot of room to grow. And it's our most mature product. Our other applications kind of in the middle, and we have many applications over on the side, and we have safety, which we haven't even We haven't even released to a customer yet. So we have many, many things to go in life sciences, take us many inside of R&D, take us many years to move from the left to the right.
If we execute well, this is, again, a very long term franchise for us. This these applications are the things that life sciences companies use to create their products to get them approved. Big business processes. We're very excited about this. I feel like we're on the cusp of achieving which is something we had this vision in 2011, and it seems so far away.
We were this little CRM company, and we were tackling this. And I'll let you know that most people said, that's not a good idea. You're the CRM company. You don't even know what you're doing over here. And it's true.
We didn't. We put people on it, and now we know. And so I'm really proud of the team for executing well on this. Now if we look ahead in the development cloud, that's we have some really exciting things going in the development cloud. That I think is groundbreaking.
If you look at clinical collaboration, this is one part of the R and D process. Clinical. This is where you have a product that looks promising in research. You have to try it, try it in the areas in humans. To find out is it safe?
Is it effective? Is it cost effective? What are the data points? Clinical and collaboration, it starts with the sponsors. These are pharma companies.
They're sponsoring, they're paying for a clinical trial of a new medicine. The CROs contract research organizations, they help the sponsors They have efficient processes. They have capacity of people to do it. They help the sponsors. And then you have the sites, the research sites.
These are places like the Mayo Clinic, UPAN, UCSF, they do the clinical research. They see the patient. They measure the tumor. They test the blood pressure. They draw the blood.
They see if the medicine is working out there. So this is a complex set of things, right, that happens. And basically, the outcome of the clinical trial is the data. Did it work or not on this patient? How what is the proof of that?
The outcome of the clinical trials of data, it's not a new molecule, it's the data. How do these groups collaborate on the data? It's not efficient. It's actually paper and email. That's how they do it.
Email attachments, paper, typing and retyping. And there's thousands of people involved in this ecosystem, and none of them like that type of work. It's it causes delays. It's not modern. This is actually a mess.
It's a backwater and it hasn't improved in many years. What we want to do is clean up that mess, and it's going to take time And there's a series of steps that we need to do to do this. So the clinical network is a concept we announced at our R and D summit only about 2 or 3 weeks ago in Philadelphia. We had about 1400 people there, and we explained what we were going to do. So it starts with the sites, the clinical research sites.
1st, we are going to make applications for those clinical research sites on our Vault platform. They have a variety of needs. They're doing something very specific with very specific business process around the globe. We're going to make them applications on our Vault platform to help them be more efficient. And then we're going to build something that we've never done before, which is something in the middle.
We call that the clinical data exchange. That's a piece of software that sits in the middle. That's what I call a network application. That is not that is for the coordination of data across companies and across the ecosystem. Across CROs, sponsors, and sites.
Again, that's something we haven't done before. We're very excited about it. You can think of the clinical network as the conveyor belts of information, the way information should flow in the clinical trial process So for example, one of the things that needs to happen at a research site, if you're doing a clinical trial, there are requirements You can't just be anybody doing a clinical trial. There are requirements. Who is the principal investigator?
Do they have the background to do that? What is their resume? And that's an official document that needs to be filed with the application to the FDA. At the end of the day, if the trial is successful. That starts on the clinical at the site.
It needs to flow over to the sponsor. So the clinical network will say well, on this study, that resume has been approved at that site, and it'll put it into the trial master file of the sponsor automatically because we know that. We know that it needs to be kept at the site and at the sponsor. I'm making a simple example of the resume of the investigator. There are many, many, many other types of of information.
So for example, when a patient says that, yes, they do consent to this treatment, this clinical treatment that hasn't been proven, they have to sign what's called a consent form that has to be kept by the site that needs to go to the sponsor. 2 different the same document. It needs to live in two different places. The clinical network will manage that flow of information. So over time, we think the clinical network is really going to change the industry.
It's going to make the industry more efficient and effective. It's going to change how clinical trial is done. It's going to help the industry. Clinical network is not something we're charging for separately. The clinical data exchange is not, the customers who have the Vault applications will be able to connect into the clinical network.
And that's something when we look at being the leader in light those are the types of things we're talking about to authentically help the industry and to build our franchise It can be a win win win. It can be a win for Veeva, for the industry and for our customers. The first use cases of that clinical network are coming in mid-twenty 19. Now the first application for the clinical research sites. That's available now.
We already have our first early adopter live. It's a large a large clinical research center. We call this site docs. This is for managing the essential documents that are used during the clinical trial process. There are many other applications that clinical research sites needs.
And we may get to those over time, but this is our first application. We have our first early adopter. So it's very, very early for us, but we're really excited about it and we're excited about helping the research sites. So we'll develop team, a team of product people, a team of field people that really live and breathe at clinical research sites and help them make their process is more efficient and effective. All right.
So that's inside life sciences. You know, we got some really big things we're doing there. In commercial, we got artificial intelligence in development. We got the clinical network. Couldn't be more excited about our progress there.
Now let's talk about the 3rd area, Veeva outside of life sciences, which is our newest area of the business. It's that's centered around QualityOne. This is our offering outside of life sciences is built on Veeva Vault. It's specifically tuned for outside of life sciences is the quality applications, quality management system, quality documentation for SOPs, training, a way to do training and certifications on procedures. This QualityOne Suite does share code with our quality suite inside of life sciences.
It shares code, so we get leverage there, but it also has its own development team. It moves on its own pace. It has harmony. And that's something that we've developed over the last year and a half. How can we do these things, share a platform, share some application components, yet have autonomy.
Because the quality needs in a consumer packaged good company is actually very different than a life sciences company. We're focused on the initial target industries, process manufacturers like consumer goods, chemicals, cosmetics, and also industrial products. QualityOne, it's a pretty comprehensive solution. It's pretty deep. There's a lot of things in there, training, document control, non compliance report, CAPA corrective and preventative actions, supplier, supplier quality audits, change control.
I have a manufacturing process, I need to change one part of it. What's who approved that change? How is that change being done? How is that change being documented? So it's a very comprehensive system.
It's interesting Veeva is the first company to tackle quality systems in this way. The first company to actually do it. And the reason why is pretty straightforward. You need a platform that handles content documents and content and videos and things like that and data. Otherwise, you couldn't tackle it this way.
There's a lot of content in this. On the manufacturing shop floor, you're going to have videos about how do you operate the machine, and it needs to be viewable by the operator. And if you have a new procedure for that, that needs to be pushed out. You need content like that, but you also need data, the workflow of how do you do a change control management? Throughout multiple factories and make sure you got it right.
So we're very excited about this area. It's a deep application. Progress in QualityOne this year, we're progressing really well. We're doing it in the Veeva way. Get those early adopters, improve that product, get them live and successful.
We had our first user conference for the outside of life sciences. I believe is in May, and that was in Cincinnati, actually. So it's a different flavor. It's outside of life sciences. We have 31 customers now.
That's up roughly 100% from this time last year. We have our first seven figure customer. So we're proving that we can tackle enterprise class customers and processes We are expecting about $10,000,000 plus in revenue, total revenue this year. So we're proving that we can scale up this business. We did an expansion to Europe this year, focused mainly in France, Germany and the UK.
That's going well. Little different flavor in Europe. It's interesting we're actually finding the most interest in cosmetics for whatever reason in Europe, right, cosmetics and chemicals. In the U. S, it was more CPG, and then it moved into cosmetics and chemicals.
So it has a different flavor in Europe and, it's going well. So we're really happy with our progress. In the last year. If you look at our learnings, in this phase of doing things outside of life sciences, the most important thing is the learnings. How do you incrementally learn?
How do you incrementally get better every day, every week, every month, every quarter? Get a little better. Get a little better. So what we learned is the Veeva Way really works well outside of life sciences, our reference selling model, and the things that we do in customer success yes, we've had to tune it for sure, but the basic model is working. Expansion to Europe is also working well.
And we've learned that there's interest beyond QualityOne inside of chemical companies, cosmetic companies, CPG, they're interested in our regulatory application that we use inside of life sciences because they have to register chemicals, they have to register cosmetics, they have to register consumer packaged goods companies. They want slightly different things, but it's very, very relevant. The clinical sorry, the consumer goods and cosmetic companies are very interested in a practical clinical suite of applications because, you know, cosmetics, you're putting things on people's skins. CPG are making claims. They have to be supported.
And we're learning that the common Vault platform is a great benefit and industries outside of life sciences also see this benefit of our platform where they can take our delivered applications and extend them in a consistent way. If we look ahead for QualityOne, it's really keep turning the crank. More customers refine our products, refine our processes, We're looking to start to establish that long term leadership in QualityOne, which takes time. And you'll see this from Veeva people quite a bit. Execution matters most.
It's about what you do every day. I know our strategy is good. Can we execute on it? How fast can we execute on it? How fast can we get better?
How fast can we learn? That's really what we're focused on in the QualityOne. And we have customer success in mind because we know the reference selling works. If we authentically help these companies, word will get around. Now at a high level, Veeva is about expansion, and you saw that from the very beginning.
I had we had pharmacy RM, a small company, a little startup. We had our first office was 1200 square feet, and I thought, well, 1200 square feet. Why would we ever need that much space? It's funny to think about now, but it's true. That was 11 years ago.
So we've grown a lot. In terms of everything, employees, customers, everything. But there's been 2 major expansion points for Veeva. 1, is when Veeva became a multi product company. And that started in 2010 when we hired our very first person, and we said, We've got to figure out what can we do on the R and D side of life sciences.
What could we do? And we hired one person and that's where it started to figure that out. Over time then, we had to make products and we had to separate our company processes. We were the pharmacy or M company. We had to separate company processes from product processes.
And that is a gut wrenching thing. It took 5 years. There's so many little details to get into when you do that, if you wanted to do it well. It took 5 years. But at the time, I deeply did not want us to be the CRM company with a few little things over there on the R and D side.
So I viewed it as my main job to make that happen. And we knew it would take time and I think we've done it well. We're really a multi product company. The next one is what we're into right now. That's in 2016, we hired our first we assigned our first person to be full time dedicated to figure out how could we bring Vault outside of life sciences.
And that involves separating our company processes from our industry processes. Because we're the life sciences industry company. Those things were commingled. So now we're separating everything out. And it's the same details, the same small details that matter in all areas of the company.
How do we have our platform served to industries? How do we have our platform served to companies? What processes are the same between in sales, between life sciences and outside of life sciences? How do we do a combined forecast? What's our project methodology?
Is that our company project methodology or is that our life sciences methodology? And how is it different? So it's a tremendous amount of details. So this is a very aggressive goal as well. This is the transformation area of Viva.
If you any of you're familiar with that book from Jeffrey Moore, the zone to win, he talks about the transformation zones. Where it's really hard, you're doing something fundamental. This is the fundamental thing we're doing. It's going well, but it's early. We're in the early days of But again, we deeply don't want to be the life sciences company with a little bit of extra stuff outside of life sciences.
That's not what we're trying to do. We want to be great in both areas. We want to use our experience outside of life sciences to really get better inside of life sciences and vice versa. So we're, as you can tell, we're pretty excited about this. It's a bold mission.
Alright. With that, I want to step back, talked about the Vault platform just a little bit, because that underlines a lot of things that we do, and it's important to understand. So if we look at that Vault platform, we started coding it first lines of code in late 2010, it's an application platform. Many application companies have those Workday would have theirs, ServiceNow would have theirs, salesforce.com, etcetera. You have to have it.
You're going to be a broad application company, you need a platform to provide leverage so that you're not coding the same things multiple times. But every platform is unique and it has its own special sauce. Ours is that it handles content and data very well and very well together. That's unique. I think we're the first to start out to really do that.
And it's also meant to handle industry specific complications. For Veeva, for our application, it has to we have to be able to run right to the complexity and do something very complex about registering some are about submitting some drug application to the right authority in Japan in the right format. It's very, very specific. So our platform is good at allowing very specific things to happen, and it's good at content and data. That's probably our special sauce.
The Vault Platform has 2 customers. 1 is internally at Veeva, so that we use to build our applications fast, consistent with high quality and for our, then it's for our customers. They use it to extend the Vault applications and to integrate with it. If you look at our progress in last year, we made great progress. Over the last year, we migrated to AWS to Amazon Web Services when we started the Vault platform, AWS in 2010 was not mature enough to handle this kind of a regulated industry.
Now it is. So we have to continually advance and continually advance our infrastructure. We move to AWS, very hard thing to do. But we had to do it, we're happy with the results. And then it's all about features and functions and scale.
And now application and platform is never done. It always has to get better, and you need to also support the new applications. So when new applications like safety, like EDC, like QualityOne. When they come, they put pressure on the platform. We do new things in the platform.
We make it available to all the applications. And then a big part of what we did is sort of the under the cover, the thing that's the iceberg part that's under the water that you don't see, which is really getting ready for the next leak. And that, that's a big leap. If you look at this Vault Platform today, it supports 100 of Veeva application developers. What we need to get it ready for is to support thousands of Veeva application developers.
And that's hard. There's a different set of things that you need to do. You need to think about scale. You need to think about autonomy for different application development teams. You need to think about independent release cycles.
You need to think about even more freedom. You need to think about how can I make more applications without disturbing the platform? So it's hard work. And that's what we've been doing in the last year laying the groundwork for that, and that'll take a number of years. It's a lot of progress in the Vault platform.
So in summary, what are we doing? We're on a path to build a multi $1,000,000,000 cloud company, and we need to do that continued innovation and expanding our markets. We can leverage our long term leadership, both in the commercial side and the R and D side of life sciences, and we can leverage our unique cloud platform Veeva Vault. And we do things in the Veeva way with our vision and our values and our reference selling. Alright.
With that, I'd like to bring up Matt Wallach, my co founder. He's going to talk to you a little bit about the perspective on the life sciences industry.
Okay. So I'll talk a little bit about life sciences industry. I'll give you a little bit of context. I'll give you a sense of where we are in terms of customers and the market opportunity in front of us in general. So the life sciences industry has been a healthy industry, No pun intended for a very long time.
Part of what keeps it fresh and exciting is a lot of investment in research and development. And obviously, this is this drives a lot of what we're doing with the development cloud. But even more than any other industry, the life sciences industry invests a lot in R&D. One measure of that is the number of potential medicines that are in development. And that number has been steadily growing every year for the last I think probably 20 years.
And if you look over the last 5 or 6 years, not only is it continuing to grow, But a lot of those drugs, almost 75% are now 1st in class. So they're trying to satisfy some unmet medical need that drives a lot of innovation. And these number of therapies in development is a real driver for companies like Veeva, selling into clinical because they only clinical trials. If they're successful, you need to register them. If you're going to manufacture them, you need all kinds of quality systems.
And if you're going to give them to people, then you have to track all of the safety. So this is a bit of the engine that keeps us going. We could be very successful in development cloud. If this was actually flat, if it just stayed at about 9500, we would grow a big business here. But it also continues to grow.
So we're growing into a growing market. And then on the commercial side, the launches are a big trigger for investing a lot in the commercial side. And it's been, I would say, a steady stream. It's not growing exponentially. Although there are a lot of initiatives at the FDA to try to allow drugs to get through more quickly.
And if you look at the year to date number, 43 approvals year to date, actually will end up. We assume it's going to go up. We actually made the slide last week, and it went from 40 to 43 since then. We had to update it last night. So now that it's not going to happen 3 a week, for the rest of the year, but we do expect there will be more approvals and this year will be the largest number of approvals in the FDA for the U.
S. Market. And I think forever will be a record. Now beyond just the number of approvals, there's 2 things that are interesting. One is there's also lots of new indications of existing drugs.
You look at something like Merck's KEYTRUDA, which has, I think, 15 or 18 different indications now, Opdivo at BMS. It's a bunch of drugs that are biologic, because of the way that they work in your body. There's lots of new indications. Each new indication is like a launch because you may have to go talk to another set of physicians. That's not included here.
And then the other thing is these are not just run of the mill products that are being approved. The very first digital therapy was approved. This is a pill with a sensor in it that talks to a patch that puts the data up into the cloud. That was one the first time that's ever been approved. The very first gene therapy.
So our result of the big genomics project from 20 years ago mapping the human genome. Well, now we have the very first one. It cures a genetic form of blindness, a company called Spark that was approved in here. Alnylam's drug, the first drug. It's a messenger RNA drug.
It actually changes the way that your cells talk to each other. It's like mind blowing stuff, that was approved in here. And each time something like that gets approved, there's another whole group of innovative people that want to be part of that. So we enjoy being part of this industry where the people that work at our customers, they're there because they generally care about human health. And extending life.
We can drag on that and we have a lot of people that are inspired by our part of that ecosystem of helping. But from your perspective, they continue to invest more and more in R&D. There's a lot of things under development. They're very, very innovative And as they continue to launch these drugs, there's new commercial engines. So we have winded our sales in both the development and the commercial side.
If you look over the last 5 years, we broke into the top 10 in terms of companies that sell software to life sciences companies, last year, we're actually number 1 on this list. And it's an indication that we're having success across different product lines. Would have been hard to get to number 1 in such a short period of time if we were just the CRM company. We would have never gotten there. And so Peter talked about how we're the only company that focused on both, actively focused on both development and commercial, I think that our lead here in terms of companies that sell into life sciences is going to increase over the years.
And it certainly puts us in an important position where we feel like we're a real partner of the industry. They feel like we are a strategic partner and we're really treated like a strategic partner at many of our customers. We don't feel like a vendor. We feel like we have a seat at the table, because we have a view into the whole industry. So not only do the products reflect what we believe are the best practices, but we see how companies use those products big and small, U.
S. And global, Japan, China, and we can be a real partner in helping companies get the most value out of our solutions over time. Last year, we talked about an 8 plus $1,000,000,000 TAM, $3,000,000,000 in commercial cloud, $4,000,000,000 plus, and that Plus was safety a year ago and more than $1,000,000,000 in Vault Quality 1. We're moving safety into this new Vault products. So now we've got a clean $3,000,000,000 in commercial cloud, $4,000,000,000 involved from the products that we had a year ago.
So between safety, data workbench site docs and training, that's more than another 1,000,000,000. And we'll continue to count TAM only in billions. We're not going to go to 9 point something 1,000,000,000. So we're above $9,000,000,000. Those new Vault products, the majority of that additional $1,000,000,000 plus is safety.
That's the biggest one of those products. Henry will talk about a data workbench, which is part of an expanded offering around clinical data management, that adds more opportunity the training product and the public and the site docs product are a little bit smaller than those other 2. And altogether, that's another 1,000,000,000 plus. So overall, we're going after now, total addressable market that is over 9,000,000,000 dollars, $8,000,000,000 plus of that within life sciences. You look at customer counts, this shows success across, and this is just Vault but it includes commercial vault, so promo mats and medcoms.
But in each of the Four main areas of vault, where we have had very good success. So in regulatory, we have more than doubled the number of customers year over in the last 2 years In quality, we have more than doubled the number of customers over the last 2 years. In clinical, we have nearly doubled in the last 2 years. And exactly the same in commercial nearly doubled in the last 2 years. So this is success company is having success in one Vault application and buying others, and it is more companies coming in, to the Vault family.
If we look at the average Vault products per Vault customer, we've been tracking this over the last few years. It's a very significant jump, and it's just year to date. So since the end of our last fiscal year end of January earlier this year, we have jumped quite a bit. And at the time that the number of companies using it has also jumped quite a bit, Now to put it in perspective, if you take, fiscal 2014 there, 70 customers 1.5 times each, about 100 installations of Vault, just 5 years ago, 4 years ago, even. If you do that math today, it's about 12 50 installations of Vault.
In under 5 years. So certainly an indication that more companies are buying Vault, but really an indication that they are buying more vaults per company. And as this number continues to rise, we think that the competitive moat gets deeper and deeper and deeper, it would be very difficult to come and compete against Veeva's development cloud. We have a lot of applications, some of which are becoming the market leader, where would you start? So the competitive mode gets bigger every time, companies adopt more and more and more.
And the Vault platform becomes a real enterprise platform for those companies. And then slicing this data by cohort, we've been doing this for a few years. If you bought Vault the very 1st year it was available, you're now using 31 times more from a on a dollar basis and you're averaging almost 3.5 volts. The next year ten times more in a few years of using Vault. And this is not surprising to us.
This is what it feels like. That's why we keep including this slide, because it feels like this inside Veeva, and this is a nice way to summarize it in the slide. And have you looked at the companies that bought it just in the last 6 months? And actually, it was, yeah, it was Q2, so end of Q2. So in 6 months, their average is over one and a half already.
So it means either they bought their second Vault within 6 months of buying the first or they bought more than one Vault. When they started, and we see both of those. So the ability for companies to deploy multiple vaults, the desire for companies to deploy multiple vaults continues to grow. And it's very good for us and for the industry. And we switched to CRM, So this is the average number of commercial products per CRM customer.
This also is continuing to grow in the right direction. If we do that same math, is about 300 projects or 300 deployments of products 4.5 years ago. It's about 900 today. So we've also shown great expansion here. And as companies deploy more commercial products, it makes each one of those commercial products that much more valuable.
And when we do them in an integrated way, we're also eliminating integration between things and managing multiple vendors. And so it really becomes a win win for us and for the customers. And then lastly, just to talk about what's remaining. So, and this is just within life sciences, if we look at the commercial cloud, and what this takes is our top the top 50 companies, so the top 50 pharma company. So this doesn't include the whole industry, but this is all of our largest customers.
You look within commercial cloud, the 20 around 25% is how much we have sold versus if they bought all of our commercial products. So this includes CRM, network, open data, CRM add ons, some key opinion leader data, and it includes Nitro. So if every one of the top 50 pharma companies bought all of our products, we would double twice in commercial from where we are today, and this is just subscription revenue. So this has no services in So just subscription revenue, we can double twice. And then in Vault, we do the same analysis.
We take a look at the amount of revenue that we have from all the top 50 companies versus what we would have if they all bought all vaults. And this includes regulatory clinical, it includes the new, stuff within clinical, including CDMS, which Henry will talk about It includes quality and it includes safety. We're only about 10% penetrated there. So just within life sciences, we feel like we have a lot more to do, after what has felt like, it feels like we've done a lot in the last 11 years, but, when you look at it this way, is what keeps us busy and how, why we're getting up early every day. So with that, let me turn over to Paul, Shawwa, to drill down into Thank you.
Hi, everyone. I'm Paul Shawa. It's great to be here with you today. I'm responsible for commercial cloud strategy at Veeva. I've been with Veeva for seven and a half years.
I've been working for technology companies for the last 19 years serving life sciences. For that whole time. I get to share with you, a little bit about more of our commercial products and in life sciences, What I was going to do is walk you through our products, what they do, what they enable for our customers, the value they bring to our customers, I'll share a couple of customer examples, and then we'll look a little bit into the future and talk a little bit about Nitro and Andy, some of the future products and where we're going. The best way to start is just with a little bit of industry context, because that's what drives the products that we invest in, but it also drives the decisions that our customers make to invest in products from Veeva. So really quickly, the summary, the shift to specialty medicines.
You saw some of the stats that Matt had presented around, specialty drugs in the pipeline. This has been happening for a while. We've been seeing this shift and our customer's product portfolio are shifting from more of the small molecule mass market drugs. To more specialty, biologic drugs, oncology, rare disease, orphan drugs. We're seeing that shift happen.
Those drugs tend to be for diseases that have smaller patient populations, but the pricing is much, much higher. So the way that they take those drugs to market is very different. It needs to be very different. It needs to justify the value in the price offering for those drugs. And it's also creating a little bit of a shift in terms how payers want to pay for those drugs and reimburse for them, which is shifting more from a service to a pay for a specific outcome that you achieve from those drugs.
So that combination of those three things that are happening is forcing life sciences companies to rethink how they go to market. They need to be more flexible and nimble and agile and change and be flexible in their commercial model. Customer expectations, customer meaning the doctor, the HCP, first of all, a number of customers is in is changing a bit because HCPs are often now employees of hospitals. So the diversity of customers is changing, but their expectations are changing as well. Their consumers, they have devices and smartphones and iPads and FaceTime just like you and I, and they expect information when they want it in real time.
And life sciences historically hasn't been able to deliver to meet those digital needs, and that's starting to change. So what this is all leading to is, it's forcing life sciences companies to be more efficient, more effective, more agile, and how they take their drugs to market. So what Veeva's strategy is around this is to enable that shift from where we started 10 years ago, 11 years ago in face to face. We started with Veeva CRM, and it was all about making that sales rep more effective, giving them a better experience, making their job easier, saving them time in the field, but also making it easier for home office to manage that system and make sure they keep that up to date. And we've largely accomplished that over the last several years in the life sciences industry, solving that, making that face to face interaction really effective and very efficient.
We're now on the phase of moving the industry to be more digitally enabled. Our customers, the life sciences companies, they recognize that they need to be faster, they need to be more digital, they talk about digital transformation. We're enabling that shift, and I'll share some statistics with you about how that's going in the industry. And then beyond that, as we look forward, we think about intelligent engagement. The life sciences industry has a lot of data, data that they generate, data that they buy, how do they use that data to be smarter about how they allocate their sales and marketing resources.
They have a limited amount of resources, how do they spend them most effectively, and we're gonna help them do that smarter with data. So that's where we're driving towards in the products that enable that vision are all of the products here that you see in commercial offerings. I'm going to start, I think of these as 3 pillars. I'm going to start on the outer end. Here, the execution side and that CRM suite.
And I'll do a little bit of a drill down here, so you understand some of the products within that. That's really about field execution, starting with CRM as the core and then all of the surrounding pieces around CRM that reps touch. Making them more efficient and execution. On the other side is commercial content, and that's Vault and Vault Promomax. As companies want to do more digital engagement with their customers, they need more content and they need to develop that content more efficiently.
And that's what commercial content is for. So I'll spend some time drilling into what those are. And then I'll wrap up with the intelligence layer, which is Nitro and Andy. You heard Peter introduced those to you. I'll go into a little bit more detail so you understand how we're connecting this insights, the intelligence that you generate, with the execution because that's really a key part of this.
CRM suite. So CRM suite is about execution. It's all of the things that touch that field, that field rep and the tools that they use to engage with their customers. So the plan that they're planning and managing their territory, all of the customers that they need to call on and plan for their interactions. It's the actual, engagement that they do with them.
So the, whether they're in front of them face to face and selling digitally or whether they send them an email or whether they interact remotely over a remote meeting. That's the top layer layer with CRM and all of the digital add ons. To CRM, like approved email, like engage, the engaged family, such as engaged meeting. On the bottom is the foundational layer. You need to know who your customers are and that's where open data and network come into play.
Open data is customer reference data, and HCOs, the actual institutions, the accounts, the hospitals, the IDNs, how they're related to each other. So that you know who to call on and target and what their, how they influence each other. And network helps to keep all that data up to date. Align is it takes the strategy that you have in home office, how you want to go to market and Align makes that real. It says, how do we define our territory size and our structure?
And who is calling, which reps are calling on which customers? And how frequently should they call on them. That's generated from a line. Events management is another critical piece of field engagement. Its events are actually the, it's the 2nd largest promotional spend from a life sciences company.
So number 1 is the field rep. And number 2, our speaker meetings. So it could be any could range from anything like an event like this, we're at a physical hotel and a location where you have a thought leader presenting to doctors to a small lunch and learn meeting at a doctor's office or within a hospital. To a very large event where you may have thousands of people face to face, like a con Congress or a conference. Those are all considered events.
They have spend at the event, and it's required from a transparency law perspective to manage all that spend and report that accordingly. Events allows you to do that very easily, very seamlessly and also run a more efficient event, a wave that gets the sales rep better involved in who's coming to that event, who they invite and making sure they have visibility to that. So all of these pieces together, the rep touches every single one of them, And if they're different systems and if they're not integrated, it's a terrible experience for the rep. We integrate them all together. We make sure IT doesn't have to worry about the integration and we make sure the rep has a great experience, and that's seamless to them.
So that's where that's what CRM suite enables for our customers. The second pillar that I want to talk a little bit about in more detail is commercial content. So this is Vault Promomax. So all of the content that a pharmaceutical company uses to promote to their customers, whether it's a website or brand.com site or an email marketing campaign or a sales that a sales rep has needs to be approved. It has to go through approval process.
And that process historically starts with an advertising agency with an idea and it ends up as a finished asset that could end up on a website somewhere. Copy, graphics, texts, all that needs to get approved. That process takes a long time, while promo mass is focused on reducing the time of that process, the end to end providing visibility and knowing where things get caught up and making that process faster. On the bottom, is digital asset management and brand portal. And that's the digital asset management layer is about storing and managing all of those individual pieces of the content, the graphics, the logos, the copy, storing all those pieces so that you can share them across the company.
So you can share them across countries. So you can share them across brand teams. So you can share them across communication channels. And when you share content, you reduce the overall cost of creating content. So you don't have to create it over and over and over again.
Significant problem, very expensive for customers. This is an area we can help an enterprise company save literally 1,000,000 and 1,000,000 of dollars in their overall content spend. So that's what commercial contents for the approval process. And then doing that more efficiently, this becomes more important when you're trying to do digital at a much faster pace because to do digital well, you need content. So CRM suite commercial content, every Veeva product, has a roadmap.
And that product gets better three times a year. We ship 3 releases a year. We've done it since the beginning of EVA. There's a roadmap for every single product. I wanted to share 3 simple examples of some capabilities that we've delivered very recently.
Sunrise UI is one example. This is related to Veeva CRM, a new user interface, for Veeva CRM. This was rolled out August 10th. So just less than 2 months ago, we pushed this out and the within days, the vast majority of all of our Ipad users had Sunrise UI on their device. It was just truly a seamless experience.
This accomplishments never really been done in Enterprise Farmer before, being able to change the user interface of a life sciences rep, virtually in days. Why is this important? It's important because it's a new innovation. We're keeping CRM fresh. It's back to what Peter referred to as Leader And Light.
We want to keep the system fresh. They all have you as a CRM. We want to make sure that it continues to work and work really well for them takes advantage of everything that's new faster and more efficiently. It also puts Veeva CRM on the iPhone because just like you and I, sales reps, they use iPhones, they use iPads, they use desktops. So now they're going to have a very similar experience across all those.
And when they get a real time alert, can end up on an iPhone and enables it will enable this intelligent engagement idea that I'll talk about in a little bit. It also expands the possibility of users, because some users can't use an iPad for whatever reason, particularly in some emerging markets where they're not able to carry an iPad because it's just too expensive. And an iPhone is more attractive to them. So it could and even has the potential to expand the user base as well. This is part of the application.
Another example is brand portal. This is part of commercial content or Vault promo maps. Brand portal, I talked a little bit about reusing and sharing content. This is an internal portal for pharma companies to take an individual brand and have all of the marketing materials around that brand easily accessible to anyone. They could put their brand colors, can highlight specific assets, they can make it easy to find.
It's a big problem in a large enterprise organization to find content. This makes it simple and easy to manage. And the last one I'll share is augmented reality. This goes back to closed loop marketing. Closed loop marketing was one of our first add ons to CRM.
We're still making this better. And we're focused on driving innovation here. In fact, what we've done is when Apple delivered their augmented reality development kit. We quickly took that. We tested it and we're rolling out augmented reality, the ability to do AR content.
Within Veeva close of marketing. So this is the idea that you can take an iPad, for example, and you can show a three d image within a piece of content And why on directly on a 2 d device? And why is that important? And like sciences, you can imagine a disease like blindness where you may wanna show the actual experience to a health care professional of what that feels like from a patient's perspective or how a medicine actually work treats a patient and view that in 3 d. This kind of innovation we do all the time.
And this goes into our product and we do this every 4 months three times a year, we have a new release. To give you a little bit of context as to, I shared 3 ideas, a little bit of sense of how this fits into the overall portfolio. Just this year alone, we've had 2 major releases so far. The 3rd December. We do that every year.
We've had 120 major enhancements in the releases that we've done across all of our commercial products this year alone. I shared 3 of them with you. I want them to give us, give you a sense of the level of innovation and commitment that a customer gets when they buy into a Veeva product. Now the types of things that we build into those, into our products, industry best practices, if it's a that the industry does and every company does it and they all do it differently and they all do it over and over and it's costly and it's expensive for them. We've standardized that.
We build that into our products that saves our customers lots of time, lots of hassle and lots of money. We also build innovation in that our customers sometimes don't even know they need yet. They don't even know to ask for it because it's not necessarily something they thought about. They think about how they operate their business today. And sometimes not necessarily what they need to do to operate their business.
So we also think about innovation and we think about regulatory requirements as well. So as the regulatory environment changes, we build those capabilities into our product. An example is the Ohio regulation that made it easier to track the distribution of controlled substances. So if it was a prescription drug and it went into an institution, it required an additional license. And when that regulation was published, we took that regulation.
Our product team built that into the product because we knew the whole industry was going to have to do it. We made it easy for them. That's an example of an enhancement that gets built into the product. Okay. So now I want to transition a little bit to what's happening in our customer base and some of the trends that we're seeing as we look across all the commercial customers.
First is long standing, long time CRM customers, they're continuing to expand. They're adding more users. They're expanding into new geographies. And I'll and they're adding add ons as well. So they may have started with CRM even before some of these add ons existed.
And now they're expanding and they're buying things like align in open data and events and network. And I'll share some customer examples of 2 companies doing that. The move to digital. We're seeing digital finally becoming a reality in life sciences. It's taken a long time the industry really hasn't had to do it for a long period of time because they've been successful without it, but there's also a regulatory barrier that's just made it a little bit more difficult.
So because it's easy for you and us to send emails to someone, it was traditionally hard for the life sciences industry to send an email because of the regulatory requirements around that. So we've made that a whole lot easier, and I'll share some data on how that's doing. And then small and medium sized companies, even pre commercial companies, The trend we're seeing is they're going all in with multiple VIVA products right up front because they don't want to have to deal with piecemealing together commercial infrastructure. They want to make sure they're ready for their launch events. And I'll share an example there.
I'll start with, one top 10 pharma company. This company has been a customer for, for a long time since 2009. One of the early customers of EVA They've expanded over time, 15 countries, over 5000 users. They were an early adopter of approved email. So they were early.
They gained competitive advantage in the marketplace. They became a digital leader faster than the rest of their peers. And today, they're still a digital leader. They've expanded since then to global promo apps, again, to power what they're doing on the digital side. All of the content that would go into that email, they need to approve that and make that efficient, but certainly that's one small piece of what they do, all of the other content in the company needs to flow through the Chroma Met system, and it does for this company.
And then just recently, there, they've announced by the end of 2019 that they're going to be expanding to 40 plus markets, and that'll be over 20,000 users. So we're seeing expansion from long time existing Veeva CRM customers. And second example is quite similar. Customer since 2011, They've expanded the CRM user population to 15,000 plus users by 2014. They added approved email in a few markets, few countries, NMA just recently, did approved email for the Globe, events management all over again, for compliance and managing these expensive events and then global promo maps as well to drive digital.
So common trend, two examples of 2 long standing customers that continue to, expand and invest and get value from our solutions. Our job is to make sure they continue to get value, and that's part of that continuous innovation story that you heard. So these are 2 large companies. An example of a small company. This is a really small company.
This is a pre commercial company. Their product is not even approved yet. It's not in the market. They're expecting the product to be approved in the fall of this year. No one knows if that will happen.
However, they need to be ready. Because that's the most important event for a pre commercial company is the launch of their first product. Their portfolio, their product is focused on oncology, should it get approved. They decided to go, and buy a number of commercial products, all at the beginning and to implement them all at once. And the reason is commercial readiness.
Again, they want to be fully ready for their launch. They don't want to have to piece together all of these different applications. Very interesting one. That's a trend we're seeing. But this one is particularly interesting because they're also an early adopter for Nitro, a Nitro product.
Why Nitro because during that launch, you need to have really good visibility into how you're performing in the marketplace. So you can change and react very, very quickly. And small companies, it's very difficult to get access to a great commercial data warehouse. They want to put that in place. So that they're ready.
So they've implemented, most of these products in 4 weeks and they're now ready for commercial launch pending approval. Digital in pharma, how is this going? So one good way to measure how digital is doing Pharma is to look at some of the stats around, approved email. And these are market statistics. 64% of Veeva CRM users now have approved email from where we launched in 2014.
So pretty, pretty significant attach rate What's also interesting is the number of emails has also gone up dramatically. Now we've added more users, you'd expect that the number of emails to go up. It's gone up. 13 fold. So the number of emails that have been sent in 2015 versus projected 2018 we took this 1st 7 months and we projected it out through the end of the year, has gone up 13 fold.
That's not fully surprising because we've added more users. But what's even more interesting is the users that are using the system are sending 5 times more emails than they were just 3 or 4 years ago. So they're more users and they're using it more, which means they're getting value out of it. And a statistic that's not on the slide here is Also very interesting in that the open rates of emails is consistently around 35% from customers from essentially day 1 when we launched this in 2014 through today in 2018. The response rate from Our customer's customer, the doctor, is sustainably high.
They're appreciating getting content and interacting digitally with pharma companies. So digital is starting to work in the industry. And I'm, predicting that this will continue, this trend will continue. One other of the digital products and within CRM is engaged meeting. Engage meeting is for doing a remote meeting between a sales rep and a customer where the sales rep may be in their home office.
And the doctor could be in a hospital or they may be at home or somewhere else. And they connect online and they're able to share content and do voice over IP or connect via phone line, whichever they choose. This is earlier, this is early stage. So it's much, much earlier than approved email. We have 20 over 20 customers, the majority of that 20 are the large enterprise.
So they're experimenting. They're playing. They're piloting with this, and they're doing it in multiple countries. You see the number of countries is almost double the number of customers because what happens is these large companies are getting the demand from all over the globe. So a large, a top 10 pharma company would do this in 5 or 6 or 7 different countries to test out the experience.
This is different than a proved email. There's a lot of change management. Reps haven't really done this before. Doctors haven't really done this before. And they need to learn.
The interesting thing here is that companies that are doing this are getting really great results. So they're comparing a face to face call with the duration of a remote meeting call, the remote meeting call is four times longer than a face to face call. Now why is that? Well, typically, it's because they've agreed to meet at a specific time. So if you walk into someone's office face to face, they may or may not have time for you, and they may have a patient who they're waiting to see.
If you schedule time and you agree to meet at a specific time, you generally tend to get more time. So real high quality calls, And I expect that this will, will follow a trend in in digital where companies learn how to do this and over time will scale, but it will take some time. Okay. So that's where we are with digital in the industry. I want to shift over to that third piece we talked about face to face and digital.
And then that next, we want to move the industry to intelligent engagement. When you talk about intelligent engagement, you have to think about artificial intelligence. It's a key ingredient to doing intelligent engagement because there's lots of data and how do you make sense of that data? Now to do intelligent engagement well, AI is one piece of that, you also need 2 other things. You need data, because AI doesn't work if you have any data.
It needs data. It needs to be organized data. And then you also need a delivery mechanism. You need a way to get that insight or that information to somebody who can actually do something with it and use it. So I'm going to talk through both of these things.
Delivery mechanism and the data, I'm going to start with the delivery side. The delivery side for Veeva is actually relatively easy. And it's easy because we started working on this 3 years ago. In 2015, we announced a product called Veeva CRM Suggestions, built into Veeva CRM. So every Veeva customer has access to suggestions today.
Many have turned it on. Today, over 40,000 suggestions flow through our suggestions every single day for field reps, and they're able to view directly where they do their job, right, in Veeva CRM, suggestions that are made and tailored specifically for them. And then they can take action on it. So the suggestion may say schedule a call and they click a button and they schedule that call or send an email and they click a button and they can send an email So it's very easy. It's right where they're doing their job.
It's not some place else. So there's no barrier to execution. So the delivery side of this we've made easy, and that's part of EVA CRM suggestions. Let's talk about the data side because that part is different in critical to AI. The data side, the data layer The foundation that you need for doing artificial intelligence is very, very messy today.
In fact, most companies their environment for data looks even more complex than this. This is considered this a simplified version of what a large pharma company's data management landscape would look like. So let me explain a little bit. On the left hand side, you see all of the data sources. So data sources are one of 2 things.
It's either data that you generate like CRM activity data, what my reps are doing in the field, that's generated data, or it's data that you purchase. That's often called 3rd party data, like sales data or formulary market access data or patient EHR data, that's data that you buy. Regardless, the data is messy. It comes in in different, sometimes in different formats, in different shapes and sizes, and sometimes at different frequency seeing, you have to get that data all into one place. You can't make sense of it unless it's all together, and that is generally called the data warehouse.
Now the data warehouse in life sciences is custom built. That's the standard because there's no other great option. Every most pharma companies they take horizontal technology and they custom build their data warehouse. Now the horizontal technologies have gotten better, but still they have to custom build. They have to build all these integrations, And then everything in this box right here in that, in that dotted line, within the dotted lines, that's all stuffed within the data warehouse.
They got to build the integrations and they use things like ETL, extraction and transformation and loading to get data in and they build staging in operational data stores and aggregated data store stuff that they spend literally months and months and months building. And then you got to get the data out of the data warehouse to put it into the BI tool so you can use it and make sense of it. And And the majority of these companies spend all this energy to do BI business intelligence to look at reports and analytics and get insights. This is really hard. It's company spend lots of money, lots of time, services and hardware building this infrastructure.
This is precisely the problem we're solving with Nitro. It's a big problem for our customers. So what does Nitro do? How is Nitro different? A next generation data warehouse.
Next generation sounds trite, but let me try to explain why it's next generation. First is all of that data. On the side, we're going to organize it. And we're going to build connectors into that data, and we're going to productize those integrations to that data. So the farm industry generally uses, by and large, the same sets of data from the same sets of vendors, we're going to take the most common ones we're going to pre build integrations into those data sets.
And we're going to maintain those over time. So we'll have a roadmap of integrations, just like we have a roadmap for features in Veeva CRM. We'll have a roadmap of partners and companies that we integrate to. So we'll make getting that data into the data warehouse easier. 2, we clean up that whole mess within the data warehouse.
It still exists, but Veeva takes care of that for our customers. So for our customers, completely transparent, and we pre build everything within the data warehouse, pre build the data model. What does that mean? Well, it means a pharma company doesn't have to go literally every pharma company go and define what a doctor like in a product and the relationships between them and how to aggregate them and which metrics, they don't need to do that. Veeva will do that form.
We'll standardize that for everyone. And then we'll make it easy to get the data out and get it into the right place, and we'll make it ready for business intelligence and artificial intelligence. Because nine times out of 10 companies have built their data warehouse for BI and not for AI, and we're going to do it for both. There's two lines on this slide, which I want to call out. They're super small.
They're in the upper right hand corner that connect Viva Nitro with Viva CRM and with Vault PromoMats. I'll use the one that connects to Viva CRM as an example. Because it looks insignificant, but it's a really, really big deal. And I want to try to explain why that is. In the traditional way of building a custom data warehouse, you start out with your CRM system, VIVA CRM, which is what most companies have, and you integrate that into your custom data warehouse.
And on day 1, after your custom data warehouse is built and you hit the on button, they're they're in sync. They work. The problem is Veeva CRM is a fast moving system by design because it's got to keep up with the business. The business requirements change Veeva delivers new functionality 3 times a year, customers add new functionality multiple times a year, CRM gets better and it changes, all the time. If you don't change the custom data warehouse and keep that in sync, you can't report and run analytics or run AI on the changes that you made in the CRM system.
The problem is that those changes that you make in CRM take a long time to make in the custom data warehouse. Why is that? Because they're 2 separate systems often run by 2 separate teams So there's projects. So they do something over in CRM, and they forget to tell the data warehouse guys, or it's a separate project. It's a separate release schedule.
And because it's so much effort and energy, it often gets forgotten about. And over time, what happens is it's so challenging to keep those 2 systems in sync because it takes months months, they actually stop trying. So what goes into the custom data warehouse is just gets old and stale and it's likely the number one reason that 3 or 4 years into a custom data warehouse, you'll literally start all over. Just say, yeah, the thing doesn't work anymore. It's falling over.
We got to rebuild a thing from scratch. And that's been the challenge in the industry. And this is the problem that we're solving with this integration to Veeva CRM and Nitro. We're going to make that sync automatic. So if you change something in Veeva, Veeva CRM, if Veeva changes something in CRM or if our customers change something in CRM, that change is automatically going to flow over to Nitro.
We're going to make that automatic. This is a massive transformation for, we believe, for our customers. And it will change how they think about data warehousing and how the speed at which they're able to turn something on at CRM and get that reflected in the analytics and in the AI. So if you turn on suggestions in Veeva CRM, imagine not being able to know how many suggestions did I generate, or which ones were were used and which ones weren't. We'll make that easy.
So that's what Nitro solves. Nitro is still in the early days, but we just signed 3 early adopters in the U. S. Market. I just wanted to call out 2 of them.
1 is a commercial company, they're replacing a legacy data warehouse. Legacy data warehouse was it could not meet all of the needs. It was focused on a slice of the data that they had. An interesting story I spoke to one of the project team members for this company. And on day 1 of the project, day 1 of the project for this Veeva project, they literally turned Nitro on, and the data from CRM flowed into Nitro.
And they put a BI tool on it, which is very easy. And they looked at the results and they learned something about their sales coverage that they never knew before. First day of the project. If you build a custom data warehouse, that could take months to even get the data in there. Forget about learning a new insight from it.
So they're not live yet. They're in the project stage, but they're all they're they're already starting to see some, yeah, some results. The other company is a pre commercial company. So their product's not approved yet. And this goes back to the idea that we're making the data warehouse accessible to companies that could never have imagined having a data warehouse before.
It's now easy for them to do it in critical for them to do it because they're about to go through a launch. And they want to know exactly what's happening in that launch. And nitro. They view Nitro as the most efficient way to get there. So we're excited about the early adopters that we have, with Nitro.
And where we're going in quick summary. So we're applying a product excellence approach to a custom data warehousing problem. That's fundamentally the difference. We're turning this into a standard industry product, something that's been messy and custom with loss of services for a long, long time. And that will establish an ecosystem of partners and services providers that are able to all work on the same the same system, the same product, the same data model.
So the same kind of ecosystem that was built around Veeva CRM, we believe will be built around Veeva Nitro. Will stay current for the reason that I described because we'll always keep view the CRM, which is the fastest moving transactional system in sync with the data warehouse, and then we're going to build it for specifically for AI. Of course, BI Business Intelligence but for artificial intelligence as well. So we're on the journey now to getting to intelligent engagement, we talked about the delivery mechanism. We talked about the data layer and the data foundation and how Nitro is going to find that and make that easy.
And then your Peter reference Andy, the artificial intelligence engine, We're also delivering the AI engine. It's called Andy. It's going to be available in late 2019. And I just want to show you one piece of how it fits in. To the overall ecosystem of driving intelligent engagement.
So on the right hand side, This was you saw this already. This was the delivery mechanism. You viewed suggestions. You took an action right in CRM, right where you need to execute something. We're plugging in, we'll be plugging in Andy to that.
So Andy, think of Andy, as Peter described it, as waking up and figuring out looking at it a wide variety of data and coming up with something that a human being could never have imagined, could never have pieced together, could have never identified that pattern, because one, because they don't have access to all that data. And even if they did, they wouldn't have been able to come up with the pattern in their brain. And Andy generates that suggest It puts it right where it needs to be and they take action. And a suggestion could be something very simple, like you haven't seen this customer in 4 weeks, go see them. That's very, very elementary, or it may be something that's super sophisticated, which could be there was a cancer patient in an office last Thursday who had this lab test result asking a very specific medical question, and therefore, invite them to this speaker meeting with this thought leader.
That's pretty complex and hard to solve. A sales rep, an account person could never figure that out, Andy will solve that for them. And then there's a feedback loop. If they take that action and he's learned something, it was a good suggestion. If they don't take that action, if they dismiss it, and these learn something as well.
Maybe it wasn't a great suggestion and those suggestions will get better and better and smarter over time. So What we walked through was where we started with CRM in face to face and making that more efficient moving to digitally enabled. And then our vision for going to intelligent engagement, which is driven by Nitro and Andy. And hopefully this gives you a flavor of how we're going to execute on that. I'm super excited about where this is going.
And I'll leave you with just the final thoughts of what we're trying to do in commercial, expand CRM leadership, and that's continuing to happen. We're going to continue to drive that innovation. All of those the 120 plus enhancements that we deliver every 4 months, that's a big part of establishing that leadership. And and having our customers expand their footprint, growing the add ons. So that's the CRM suite and all those products and our customers continuing to get value from all of those.
Helping the industry to continue to move to digital, small companies going all in, which we talked about, and then, of course, being ready for AI. With that, I want to thank you all very, very much for, for listening today. I hope you enjoy the rest of the rest of the day.
Alright. Thanks, Paul. We're gonna take a a break, about a 20 minute break. If I could just ask everyone to try to be back in your seats, at about 10 before the hour or about 2:50?
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Alright. So up next, we have Henry Levy, our general manager of Vault CDMS.
Do you want me to wait until people say? Well, hello, everybody. I hope you had a good break. I'm Henry Levy, and I'm the general manager for our VoLTE S. Product.
And, everybody says they're excited to be here. I'm excited to be here because I feel like I'm continuing a conversation that I started last year for some of you who might have been at our Analyst Day last year, I focused very much on the clinical suite. And what I discussed last year is the fact that over the last 20 years, there's been an infusion of new technology into the clinical space. The cloud pretty much came to the space, yet performance didn't change. Actually, in some areas, it got degraded.
It got worse, which is a little bit antithetical. It's difficult to believe that Over 20 years, there's been improvement in technology in one space, but we haven't seen major improvement in the outcomes. And today, I'm gonna take a bit of a bigger, lens, and I'm gonna try to answer the question of why. What are some of the root causes of why we haven't seen progression? I'm gonna start by introducing you to the development cloud again that Peter, started and taking you through the progress of each of the areas of the development cloud.
Then I'm gonna go a little deeper into the clinical data management space and get into that one of those root causes. And I'm going to explain a little bit about how clinical data management occurs which hopefully will give you a little bit of perspective of the direction that we are taking. And then I'll finish by bringing the cloud together and highlighting how when you bring it together, the value is multiplied. And I hopefully will do a good demo for you of one of those areas where you can add a lot more value by bringing the cloud together. This is the development cloud.
It starts with the execution of clinical trials, which is critical to bringing a new drug to market, and that execution of clinical trials has a clinical data management component, which is all of the underlying data and then a component of clinical operations, which is how to run the clinical trial. It has a component of quality which is about ensuring the overall quality of It has a component of regulatory because we are in a regulatory environment where you have to submit just about everything, everything that we do we have to submit to the authorities, and then it has the last component of vault safety, which is we are treating patients. And because we're treating patients, we have to ensure expected and you did not mean to occur, you have to report to the authorities. So those are the 5 components as And as Peter said, nobody else in the industry can claim that they can do all 5 of these in one platform. And then we believe that even within each of the areas, there are significant claims of differentiation for us.
And when we talk about that development cloud that has been recently validated at our R and D summit. Peter highlighted the fact that we had this summit in September in Philadelphia, It was the largest one ever. We had more than 1400 attendees, and they represented more than 250 customer companies. The session, it is all about reference selling. We want our customers to talk to each other, to learn from each other.
To talk to each other. And we create those opportunities. We present our roadmap. We listen to our customers. And one way that we listen is We bring heads of regulatory together, and we also bring CIOs of our small and medium pharmaceutical company clients together.
And this year, we had about 20 to 25, and it was fun to hear kind of a quote for summit, which was they all talk to each other. They all are sharing what they're learning. They're all excited about Veeva. And when one of them jumps in and says, wanna come back next year and I wanna present to you how to implement 10 volts in 18 months. I mean, that is, that is the message that we wanna here.
That is what development cloud is all about, is we wanna hear a CIO say that they're committed to Veeva and that they're committed to Veeva because their speed. In 18 months, they can implement applications that probably historically could have only implemented one of those applications in 18 months. So that quote really represents what we're trying to do from a development cloud perspective. Trying to add more value. We're trying to simplify things, and we we're trying to drive speed.
So let me give you a little bit of an update on the clinical operation side. As I said, clinical operations, it's about executing clinical trials And there are 3 major applications in this space. The first one, which is our oldest application and most mature application, is eTMF, where we have over 200 customers. And for you who may not understand this space, eTMF is the electronic trial master file. It means that during the execution of a trial, there's lots of documents.
And each and every one of those documents must be maintained. And you have to put them all together, and you have to submit them to the authorities, and the authorities, specifically the MHRA, will audit you to make sure that it is perfectly complete. And if it isn't, you will be in trouble. So that eTMF is really critical. The second one is study startup, which is pretty much the biggest block other than getting patients on board on a trial, is starting the trial.
There's regulatory processes in every country, and you want to get every single site, so you can start doing the trial, and that's the technology helps you do that. And then the last one in the, the newest application, which is clinical trial management or the CTMS, it's the overall execution of a clinical trial. From an Etmf perspective, we are just adopting. We are really not in a acceleration mode And the most exciting part is that we have a critical mass across sponsors and CROs. CROs are companies that you are running clinical trials with, that you don't have the people to run that that trial, so you outsource the execution to the CRL.
And that happens in about 50 percent of trials. Now, Peter explained to you the Viva clinical network. That Veeva Clinical Network comes to life in the in the discussion between sponsors and CROs. When a sponsor says CRO number 1, can you please run this clinical trial? You really give them a lot of accountability, but there's one thing that you must maintain.
And that's the eTMF. It means that at the end of the trial, you as a sponsor must have all of the documents for that clinical file in your ETMF. That is required by regulation. It is required for oversight. So what happens?
I am sponsor, I tell that CRO, you have to use my TMS. And that sounds easy. But the CRO on the other side says, My gosh, I have my own TMS. All my processes are maximized for my TMS. Now you're telling me to work in yours.
So what happens? They increase price, or they say we can't be as efficient or as effective. They say, okay, use yours, but then give us all the documents. And that cost of transferring documents from one place to one other so that you have them on a regular basis is significant. It is not just about moving a document.
It's about mapping the document because in their system, they might have it called something. In your system, you might have it called something else. So it is a really high cause that in the clinical network space, goes away. In the clinical network world, those two vaults talk to each other. You can let the CRO run their own trial be maximized for their effective in process, and then let the network just talk.
That process of you use my system goes away. Can just use whatever you want. And then behind the scenes, everything is moving, and it's not just moving at the end of the trial, it's moving in near real time, which increases the oversight that a sponsor can give on that at that CRO. On a Tuesday, I can go in and see that the TME TMF is up to date. If it isn't, I can call the CRO and say, Hey, we're falling behind.
That's something that you could never do before. So what we're seeing is clinical network has the potential to maximize the value of eTMF without us investing in eTMF. We're investing in the industry, and that investment increases the value of our technology. If we go to the site startup or study startup space, our best news for the year is that we actually sold and engaged a suitable company. And because we are a rapid implementation, they actually went live about a month ago.
So now we have a top 10 company using our sites and study startup, working with ATMF, which we think is going to show the value of the overall clinical suite. And if we finish with CTMS, CTMS is a pretty complex application. It's deep. It's embedded in the organization, and we've been pleasantly surprised by the rapid adoption of CTMS. As of Q2, we had 28 customers.
That is pretty fast for an application that came out about 18 months ago. And because of that excitement, because of the fact that we're seeing that adoption, now starting to engage in the enterprise side and the top 50 pharmaceutical companies. So if we think about clinical operations, what we're seeing is continued progression. ETMF is now settled. Clinical Network is going to add more value, study startup is starting to to accelerate, and CTMS is starting to grow outside of the early adopter space.
Pretty exciting. If we go into the regulatory space, let me just take a step back and say that in the regulatory space, we've had 3 major applications, submission, submission archive, and that handles a lot of the document piece. When you do a regulatory submission, I was in the industry, maybe, 20 years ago, when you still had to print everything out and put it in a truck, and and you would actually drive a semi and sometimes 2 semis and drive it to the FDA. So it's a massive amount of documents. And submission and submission archives is about managing those documents.
Registration is the data side of the business. Every time that you submit a an application, you have to track it. Every time you sell a drug in a country, you have to track it. And that tracking of registrations is highly complex. Now if you look at those three pieces, by themselves, the about 90, ninety five percent of this regulatory space.
And we were doing really well in that space, but our customers really said you need to do more. And let me explain why. In essence, when you were doing a submission, you were starting to do the work, do the work, do the work, you got to 90 completion, and then you need it to publish. Publish is the part where you structure the data, exactly how your authority onset in each individual country, and then you can submit it either electronically or through printing. It's kind of, I'll say, a relatively manual job and we had not really applied ourselves to that space, and we had not attacked it.
But our customer said, I do all my work in Veeva, and then towards the end, I had to pull all the data out, put it into a different system for publishing, take the results of that publishing, and put it back in to Veeva. And one customer actually said, is the equivalent of you flying or buying a ticket for San Francisco to JFK, but then flying from San Francisco than landing in Newark and walking to JFK to pick up your bags. It is not a good thing. So we have to go into pub It is not the most exciting part of the business, but we've applied innovation, and now we're doing ongoing publishing. We're a soon as you create a document and you'll see that in the demo, it is automatically published, which which means that at the end of your submission, press a button, the publication is there, and that means that your flight is now SFO to JFK.
You don't have to stop anywhere in the middle. So we have 140 regulatory customers, publishing is ready for early adopters, and bringing publishing is a really interesting milestone for us. And the reason I say that is that in the space of regulatory, we've kind of reached a completing the suite space. And in those 4 applications are pretty much the majority of what is in the regulatory space. Now what does that mean?
It means that we can now really innovate. We have all the scope. We're attacking the entirety of the process, and now we can go deep. We can really innovate within regulatory, but even more exciting. We can now focus on integrating across the development cloud.
It gives us the scope or the ability to not just complete the things that we were missing. You know, customer you're missing this, you're missing this. We're not missing anything major at this point in time, so we can really focus on innovation and focusing on Cross Vault integrations, which will lead me into a little bit similar. Form both sides of the document and data space. Quality docs is all of the documents that you have to manage.
QMS is all of the data that you have to manage in the quality space. But we also had a little bit of an incomplete story. So in the quality world, if you were in a company that that really has to track quality, it it's about, you know, having a an event to occur, something is not great. And then tracking the investigation of why it happened, coming up with a conclusion making changes to your documents or processes, and then there's the last step. And that last step is making sure that the change that you made has been trained inside of reorganization, that you know that every single person on the floor that should know not to do what was done before incorrectly, has been trained and that you can track it, and that you can prove it when the authorities come, you know, a year later, and they say, Hey, a second.
You had a big issue here. What happened? Well, we did this. We did that, and let me show you the evidence that we trained everybody so that could never happen again. So we're excited that we can now talk about training this training solution is now open for early adopters, and in essence, it completes the story.
You can now have an issue, do the Capa, figure out what you need to do, and then train your individuals and track the training of those individuals. I want to be clear that this is not an LMS, a earning management system. This is not a technology to manage all of your training content and training delivery, it's the ability to complete that story of tracking when something happened and you need to train your, your population that you can do that. And really, from a quality perspective, that also helps us complete the suite. So if we look at the quality space, we believe that we have the majority of the scope and that now we can get into innovation.
We can try to make quality better, more effective, and we can also now look at the integration across quality and other areas. And not coincidentally, when we do the demo, I'm going to focus on a, use case that is quality to regulatory. So now that we have, in quotes, completed the suite in quality, completed the suite in regulatory, it gives us some capacity to think about how to bring them together in a more effective way. If I then go into the safety space, as I mentioned, This is about taking care of our patients. It is an incredibly deep area.
It's also an area where there has been very little innovation in a decade. The technologies that exist today have existed for 20 years, and they've been relatively massive, difficult to implement, expensive to implement, and it really has not improved. Because of that, based on our announcement safety, we've gotten a significant amount of customer interest, and we're excited to say that we are on track for delivery in early twenty 19. Now if you think about that message, which is this is really, really expensive, really, really hard to do, it means that our SMB customers, the smaller ones suffer. They have no ability to pay for this, or they have to spend sometimes 20, 30, 40% of their money, which they should be doing in running clinical trials, buying these technologies because they have to track their adverse events.
So we think that there's a great opportunity to focus in the SMD market for our early adopters, and we'll do that. And we already have great interest for early adopters But this is a really deep application, and we expect that the early adopters stage should take at least a couple of years. So I've covered the clinical operation space. I've covered regulatory and quality, which have that completing of the suite. I've talked about safety, which is coming next here, and now I'm gonna go a little bit deeper into the clinical data management space.
And this is the part of the story where I am digging one level deeper into our discussion last year. So as I said, last year, we said, clinical had a lot of new technology for 20 years, yet things have gotten worse. That's not that doesn't make sense. So I wanted to spend a little bit of time telling you why, but before I do that, let me focus on our EDC progress. We put out our new, our EDC solution about 18 months ago.
And just to give you a little bit of perspective, if a customer wants to be an early adopter see, it means that they're putting their clinical trial in our hands. I just wanna repeat that. This is not something that they can run an early with us and then kind of do something else in case it doesn't work. If this doesn't work, there, there's real consequences and therefore, we've been incredibly pleased that in those 18 months, we have 16 customers. And we're even more pleased that there is one of them in the top 20 space.
So we now have a top 20 customer that is running pilots with us. And if we can demonstrate that, that, that, that trial can be executed effectively, they will continue to grow. And let me tell you a little bit of why. We now are working in 9 different therapeutic care including immuno oncology, which means that our technology can handle complexity. The components of doing adaptive trials and doing different types of trials is something that we can handle in our technology.
We're running Phase 1 and Phase 2 trials, and we're starting conversations about Phase 3. And then from a milestone perspective, let me give you a parallel. A clinical trial starts and ends, and there's functions that only happen the end of the trial. Similar to, if you implemented a financial package and you started to use it in, in January, you would use a lot of the transaction pieces, but you don't sets, we start, we build the database, and then we start to run the trial. But the end of the process is when all of the patients have come in, All of the drugs have been given, all of the time has happened, and I need to close the database or lock the database.
So really, even though we started our first trials last year, we haven't actually used all of the functionality, which means our customers are still saying, Hey, have you finished the trial? Has your data been included in a submission? Well, we're excited to say that next week, the first trial will lock in Veeva EDC, and by the end of October, we'll have 3 trials that lock in our technology, which means that our data will be included in submissions to the authorities, which is a really important milestone. It's really critical that our customers can say, wait a second. You've actually run a trial.
You've actually had patients. You've actually closed it. You've actually had your data used for a submission. That gives us a significant amount of credibility so that we can continue. And then even more excitingly, we have improved performance.
The amount of weeks that it takes to build a study on a standard level is about 10 weeks. We have seen consistent execution at 7 weeks. So again, we're able to handle complexity. We're able to close a trial and we're seeing improvement. So we're very excited about the progress in the EDC space, but as we engage more and more, we're hearing that EDC is part of the problem, but not the entirety of the problem.
In order to explain that, I'm gonna take you through a little bit of history. Those of you who are all, as old as I am, you might be able to remember the 1980s. I see a few of you that not. But in the 1980s, before the digitalization of clinical trials, pretty much everything was on paper. So when you ran a clinical trial, you actually had the pharmaceutical company send these massive packages that had CRS or case report forms.
These forms came in triplicate. This was pieces of paper in triplicate with carbon copy paper in between. I'm not exaggerating. That's what you did. And the direction for the investigator was to write really, really hard.
Because you have to make that piece of paper go through three times, and then they would rip either the pink or the yellow color, depending on which one it was, they would put it into a FedEx package, and they would send it to the pharmaceutical company. And at the pharmaceutical company, they would enter it into a system by hand. That sounds terrible. Some of you probably don't know what triplicate paper or what carbon copy paper is. You you got your hands really dirty.
But what's important is that it was simple. You knew how to do it. So it was very hard. It was slow. It was not that effective in capturing data quickly, but all of your data in the pharmaceutical company was in one place.
It was actually relatively simple once it got into the pharmaceutical company, and the problem was actually at the site. So what happens in the 1990s? I was lucky enough to be a part of 1 of the first EDC implementations in 1994, and there was so much optimism, because EDC was gonna get rid of that triple 2 paper. That triple 2 paper would disappear, and it would get the data faster into the pharmaceutical company, and that was really, really good. So it was all about optimism.
And the idea was ADC would be able to handle all types of data. Every single piece of data would come in, and I could handle it all seamlessly. So what happened in the 2000, EDC takes off. Everybody's extremely excited. Now we have 50, 60, 70 percent of trials being run-in EDC.
But what happens when you add some of the other types of data? Let's say labs. Labs are relatively easy. It's just any of you who have been to the doctor and have gotten a lab taken. You get this sometimes, this report with about 10 pages of just stuff and numbers, and it says, leaders in this and that, it's really simple data, but it's long.
And what happened is that when you loaded the lab data, into the EDC system, performance died. Performance at the site. You had stories of investigators pressing a button and leaving to go to the bathroom so that they would come back. And when you came back, the page had changed. So what happened?
The EDC provider said, look, we're gonna try to solve this problem, but for now, EDC is just for that data that entered at the site, and you're on your own a little bit because you need to solve the problem of bringing the data together. And what happened Well, they did. Pharmaceutical Companies built internal tactical solutions. They built internal databases and spreadsheets, and they used fast to try to bring things together, and it just became a bit ugly, and they waited, and they waited, and they waited for the vendors to actually solve this problem. So what happens in the 2010s, which hopefully all of you can remember, that in 2010, it gets worse.
Why? Because we have proliferation of data. MHealth brings new types of data, new environments. And there is still no solution that is holistic, or modern to do clinical data management. So that means that we have a really ugly inefficient and expensive environment within the sponsor even though the site might have had some improvement in their life.
And if you think about it and you go back to maybe 15 years ago, this is what CRM looked like. About 15 years ago before Viva got in, in, in the game. Just to make it come to life, I wanted to show you the example of what happens with one piece of data, blood pressure? If you go you're in a clinical trial and you go to a site and they take just the blood pressure, then your physician will take that blood pressure. They will enter it into HR on one side, but they also have to track it for research purposes, so they'll actually write it into a piece of paper, and then an assistant will enter that blood pressure into EDC.
So not a great but definitely better than the triplet itself. Then when that goes into the, into the sponsor side, we have what happens with cleaning. And let me explain what data management cleaning is because I've talked about cleaning being difficult. There are Four levels of cleaning. Which is kind of interesting.
The first one is the simple one, which is did they enter the information exactly as as it happened. That is a one to one check. I can just look at the HR, or I can look at somewhere else and say, the state is the same. The second one is, if I look all of the blood pressures that I just looked at, are there any trends that tell me that maybe I did something in my protocol design, in the study design that maybe creates some problems that means that a physician at the pharmaceutical company looks at the data for one patient, but looks at all of the data. For example, you look at a lab, and the lab says, this guy has a, you know, high rate of hemoglobin on this date.
Well, that should have been an adverse event. So is there an event entered into the system. Yes. Well, and if they had an adverse event, they should have taken some type of medicine for that event. Well, is there concomitant vacation.
No, there isn't. I need to go back and say, Hey, what happened? Was this your mistake, or is it that data didn't didn't get included? So again, medical cleaning, which requires looking at not just one piece of data, but all of the data for a patient. Then the last one is statistical cleaning.
Statistical cleaning means that you have all of your data and you run some statistical algorithms them, which tell you if there's some anomalies. And the best reason for that is fraud. If you have fraud in a clinical trial, usually the data looks good. It looks complete, but if you run some statistical analysis, you'll see that there's a piece of data that just doesn't fit. So now you think about that.
You have data being entered in EDC and coming from a lot of different places, and you need to clean it. Well, that cleaning happens in each one of those processes in different databases. Each one of those is done in different places. A lot of work is happening to map that data. And then when you need to report it, it's happening in separate database.
So what does that mean? That the burden on the site is still there. Even though it's better than it was before, it's still there. That data is replicated. And by replicated, it is mapped and moved, which means a huge amount of cost in people and technology, trying to do things to bring that data together and to actually do something with it, and that that explodes when I use a CRO.
If I have a CRO, now there's data moving even more. And if I have a co development partner, a partner that is actually running the trial with me, gets even worse. And that was just for blood pressure, that CDC data, that's blood pressure. What happens when I have a urine test. And what happens when I have an MRI taken?
And what happens when I have an Apple I watch Mine is a Garmin, but I have something else that brings them health data. All of that data has to come together, all of the data has to be integrated, and is a pain today, and it's something that we needed to address. So how are we addressing it? We've launched viva vault CDMS clinical data management system. One application with multiple module EDC, coding, and data workbench.
EDC encoding exists today. Data workbench will be a available next and data management that you don't have to bring all the data together yourself, the burden of integration changes and in many areas it disappears. How does that actually manifest itself? We're expanding the capabilities with involved introducing a data lake and a translation layer, and we're leveraging the capabilities that we've proven in CRM and that will continue to prove in nitro to generate productized APIs. There is an ecosystem of players in the lab space and the imaging space that exists today and that we can work with to create productized APIs so that when you engage with us, that data can come into our environment, one place to handle all of the data so that we're solving not just a problem at the site, but also solving the problem within the sponsor.
What does that lead to? Time to submission. We I was at a customer this week that actually has between 30 90 days A after a trial start, after a trial finishes, and their access to their clinical data. That is, that is, that is unbelievable. The trial is over.
And there's so much work to bring that data together. It takes between 30 90 days for them to, to, to look at it. That is a delay that could cause a patient their lives, and that will go away. So it will simplify the IT environment. And then as I mentioned, I was at the Society of Clinical Data Managers in Seattle last week.
And when talked about about this with a couple of data managers who have done this for one indication or one program, they believe that this cost is over a $1,000,000, that there is the opportunity to save a lot of money in custom work and contract to work to bring all of that data together. So we think that there's a real clear business case for Veeva CDMS. So I spent some time on each of the major areas of the development cloud. I want to now transition to what is the value of the development cloud as a whole. This is the development cloud.
It's 11 applications as of today and some coming soon in vault safety. And if you look at it, there are 3 major areas of value of the full development cloud. The first one is one that I've already, I've already highlighted, which is that that CIO from a, from a, a medium for a company that came to our summit who says, you know what, I'm not going to engage with 20 or 30 different vendors and to figure out what, you know, what's their best area and how do I choose that one, and how do I do that one, and then implement them separately, and then try to rate them. I'm gonna establish a partnership with Veeva. I'm gonna go all in on Veeva, and I can have vendor rational I can then figure out how to implement the development cloud to get the most value out of Veeva and I, I can save a lot of procurement time.
I can save a lot of IT time. I can save a lot of business time by establishing a partnership and being able to take them a of my business and solve it in one space. 2nd, on the right hand side, as I've mentioned, reducing data and document transfer and integration. I'll give you an example of that where documents don't need to be created multiple times. Data doesn't need to be created multiple times.
But the reason that I joined Veeva is the middle. What the development cloud enables is us to reimagine processes. It is the potential for getting rid of processes. And that is what transformation is, and it is critical for us to push that envelope. And I'll do a demonstration of that transformation in a second.
Before I do that, that demo, let me just highlight the value of just not replicating something. If you're running a clinical trial, and you need to have a site participate in that trial, there's one additional requirement, which is they need to fill a form called the 15 70 2. That form is entered by an investigator or a site, and it has to be uploaded today into a clinical somewhere. Then that data has that document has to be exported so that it can get imported into the study startup solution that that company might have, then it has to be exported from there, and then brought into the ETMF because it has to be there. And then at the end of the trial, it has to be exported from the ATMF to be brought into the submission system so that it can be submitted to the authorities.
That is a lot of effort. For nothing. And if you work in a platform, in a development cloud, then you just have the investigator uploaded 1 and then each of these technologies just references it. It sounds simple, it sounds a little trite, but that is a huge amount of effort a huge amount of places where people can make mistakes, and you have to do quality checks, so the simplification value is huge. But here's an even more exciting example, which is about real process re imagination.
Variations. So let me try to explain variations. As soon as it's you, as a pharmaceutical company, decide and submit to sell a drug in a country, one country. What your commitment to that country is is that you're going to maintain, compliance in that country. And that means that you have to tell them every time that anything changes of.
Let me just explain that. If I have a factory in Kentucky that is developing that drug, and one of the materials that is used for that drug is sold by company G. And I decide that company G is not doing job, and I have to go to company a, just because I change companies that provide me the material, I have to then submit something to this to the country that I am selling that drug. So that sounds okay. That sounds easy if I have one product and that product is sold in the US.
That's okay. But what happens if that product is being sold in 50 countries? Well, now I have to submit a variation to 50 countries. And what happens if I have 2 factories? 1 in Kentucky and 1 in Dublin.
If I change the 1 in Dublin, do I know where that drug is being sent to which countries? And what happens if I have 50 or a 100 products? And I'm selling them in a 100 and 50 countries. And I have 4 or 5 or 12 or 15 factories. It is really, really painful.
A medium pharmaceutical company can have through 5000, 500 to 3000 very per year. And a large pharmaceutical company can have 10000 or more variations per year. And each one of these can take weeks to execute. The issue here is that this is taking away from you focusing on your new drugs. You have to do this.
This is maintenance. This is stuff that you have to do to sell the existing drugs with and it's the same people. It's the same regulatory team that's just doing it, which means that if you do that, you might not be doing any work on your real new drugs that is going to drive better patient care and, of course, better revenue. So we need to bring that and make it simpler. This, unfortunately, is the process that needs to be done in order to drive a variation.
You don't need to read it, but I'll tell you to focus on three areas. The first one is step 4 is 18 steps, and that is an assessment. If I if you remember, I just told you a 100 drugs in 150 countries with 15 factories, tracking that, when you say, Hey, what is the impact of this change? That can take 3 to 4 weeks, and not many companies are confident that the result is correct. The second point is that this is a central and local problem that this is usually happening in a central location, a central factory, but the impact is local.
So the opportunity for miscommunication is crazy. And then lastly, content. The content actually is relatively similar. I would say that probably 90 to 95% of what you submit in every country is the same, and only 5% is different. Yet today, it's so hard to share end that most of the regions are redoing the work.
So this is our incredibly painful space and one that needs to be fixed. So if we're lucky, we can now go into a demo, and I'm going to show you what that looks like if we are in the Veeva space. We start in vault quality because the trigger is a quality event. This is a QM oversight dashboard, it tells us where are we having problems, where we have a supplier that might be bad, or a supplier that actually has an issue, and we need to drive a change control. So down here, we have a raw material maker that we know has a problem.
We can click on it, and we can see that Superform. And in fact, has had some major issues, and that there's one that is affecting our drug. If we go into that change control, we can see that we can, from the change control, trigger a change to documents, or a change to action. If I'm going to change that manufacturer, I have to, of course, select a new one, but more importantly, that first line is I have to file a CMC very for Vodafir. So if I go into that change control, I see that even though this is in the quality space, the main thing that will in is a regulatory event, which is the replacement of Vodavir salt.
That's the compound. If I click on this, then I'm now in Volt Rin. And this is the value of the development cloud. This is the magic of bringing all of the data from quality into the rim space. I can see that the active substance is already populated and that I already have all the Vodavir Vodavir Base Findaxias available.
All of the stuff that has been that 90% that is common is already been brought in, so that I don't have to repeat that work. So I can go into this space, and if you remember first step that I said that took 17 steps, I go in, I go into impact assessment, I tell them what type of impact assessment I want to do, I press next, and then that thing that took 3 to 4 weeks takes about 10 to 15 seconds, and I can see that there are 6 countries that are using this compound. That's because we're using registrations. And out of those 6 countries, 3 are in the EU, which means that I only have to do one submission for that. And then the other 3 are a couple of different, countries.
I can say, okay, let's do some activities. I create the related records, and I can go to those activities And if you look at those activities, now I have 4, 1, 4 Belgium, which is the lead country for the EU, and 34, Canada Malaysia and the US. If I go into the US, I can say, let's look at the submission. I can click on that submission and create the content plan. And when that content plan comes up, I can see that there's a variety of things in it, and that the majority of them, as you'll C are green, which means that that 90% has already been brought in from the existing dossiers, but then there's one stability test that has to be done in the U S, because that's U S specific law.
And I can really get into that space, complete that And because we're here, I can show you that if I go into submissions archive, I can see the actual published content. So a process that, you know, and this is a fit. There's a few steps that I did not, generate, but this is a process that would have taken weeks for a lot of people to execute that can be executed in probably 1 or 2 hours. If we go back to the presentation, 43 steps that go down to 11, and the majority of those are automated. You have multiple systems, to one unified system.
You have this complex collaboration between one region and another that is unified. You have the potential that your assessment wasn't successful, and that you don't know if you actually went to the right countries. And if you don't, you won't be able to sell that drug. That's revenue lost. And in the new world, you have full compliance.
In the old days, you track this with spread sheets. Here, you have full visibility, and of course, it's efficiency. And as I said, this is maintenance activity, This is not innovation drugs and what better than Veeva coming in and making that go away. So I spent about 38 minutes with you, and I wanted to just maybe summarize a couple of key points. The first one is that if I look at 2 years ago, when I joined Veeva, the conversations that I was having with customers were, Hey, do you want the TMF?
Do you want regulatory? Let me tell you how valuable they are. Now the percentage of conversations that are about the platform, about let's go to Veeva Way, has significantly increased. We usually start there and then go into the details, which means that the development cloud strategy is working. We're seeing the value of that.
2nd is that the success in EDC has fueled an expanded strategy into CDMS, and we think it's going to really solve the core problem that is making the industry slow down. Has transformative potential because eTMF by itself is valuable, but with network, all of a sudden, we can get rid of an industry power of data movement that is actually improving the way CROs and sponsors are working together and the way sponsors are providing oversight for their trial. And then as you saw from Paul and from Peter, we have a lot of work to do. So our focus is on execution and making sure that we understand what our customers need, that we listen to our customers, that we adjust, and that we always focus on customer success. I hope this has been educational in some ways, and I appreciate your time.
I will now call, Dan and Matt to the floor. Thank you
so first, I'd like to introduce Dan on Singer. Dan started his career at Accenture. AMC. Okay. Started his career at Accenture and then, ran, the US IT at ASI was one of the top pharma companies, for 5, 6 years.
And now, for about a year, is it a year, yeah, an intracellular?
About 6 months. 6 months, yes.
The last 6 months has been CIO at intracellular therapies, which is a publicly traded clinic stage company. So when we talk about commercial stage company, it means they have products that are on the market. This is a pre commercial. So they're still in clinical trials and looking forward to their first launch. So Dan, thanks so much for being here.
Thanks for having me.
And a lot of the folks in the room and probably listening So you spend just a moment just kind of define what intracellular therapies is all about?
Sure. So, intracellular is a well, first, we were founded in 2002. We are, I'm not sure if this thing on here.
Just keep going. Okay.
Just keep going. We'll roll with it. All right. So, we were founded in 2002. We were, leverage the technology from the laboratory of a Nobel Laureate Doctor.
Paul Greengard. And we are a clinical staged company here in New York City. We focus on neuropsychiatric and neurodegenerative diseases. And we just submitted our first new drug application to the just last week. For bipolar disease, Alzheimer's agitation associated with Alzheimer's disease and other depressive disorders.
We have another compound that are in earlier stages of clinical trials related to Parkinson's disease. So it's an exciting time to be with the company.
So let's take a step back and talk kind of broadly about the industry. You've been serving the industry as a consultant now. In leadership positions for 20 years, more than 20 years. What would you say from one of the biggest business changes that you've seen over that time, something that's really changed the life sciences industry.
Besides me becoming more important.
That? Well, I mean, maybe we should start there. No.
I mean, in all seriousness, the pervasiveness of technology and digital and healthcare is, has been a tremendous change. I mean, if you think about 20 years ago, who have thought we'd be looking at facial recognition as applicable into clinical trial right? Can I look and see that I'm adhering to my medicines by putting a tablet in my mouth and that the iPhone is looking back and ensuring that that's happening? That's pretty impressive, right? And that's a big problem in the industry.
Who would have thought that my watch could take an EKG while I'm sitting here and then send it off to my doctor. I mean, these are the types of things that are truly innovative and When I think about all of that technology and what happens, there's a ton of data that's going to start coming back. And that data is what makes decisions much, much easier to make as a company as far as where do we start placing our bets from a medicine perspective.
And kind of along those lines, one of the things we talked about earlier today was artificial intelligence. So as a CIO, I'm sure you get called by lots and lots of companies, Where do you see some practical applications for AI in this industry?
Yes. Well, let me maybe first start with, I I was watching a video on YouTube of all places, with a physician here in New York City at a major hospital, And the whole concept was is how do you apply deep learning to the medical field and to his data? And so He pulled together, genomic data, medical record data, lab data, mobile data, wearable type data, that sort of thing, and aggregated it altogether. And he was able to, with high levels of accuracy predict the onset of a disease state within a year. And I'm not talking about 50%, 60%.
We're talking 80%, 90% of accuracy. And when I take that, that, that's kind of the panacea. It's exploratory. It's, but it's there and it's going to happen. When I break that down to what can we do now, it's the same principle.
And so the principle for me of aggregating data not that long ago as a part of a project, where we needed to look at a specific safety signal that was occurring. And our Chief Medical Officer at the time hadn't seen something like this in his time doing it. And so we needed to kind of figure out what what the heck was going on here? And so we needed to pull data from across all of our studies, different indications. It wasn't just for the one we were trying to get approval for.
And try to see what was happening. Now I can't obviously get into the specifics, but let me give you a kind of a made up scenario that hopefully illustrates it. Which is, we were able to see in this example that women over the age of eighty who happen to be malnourished were susceptible to getting this particular, adverse event. It just so happens that that adverse event wasn't relevant to the patient population we're trying to get approval for. And what that means is then we can then, from an approval defense standpoint, back to the agency, say, Hey, look, We understand that you're seeing this in the data, but it's really not a thing to be worried about.
And that's important because that means that, the patients that need that medicine have access to
Yeah. That's a deep, deep example.
What a relevant one, right? I mean, and you can do the same type of thing and on the commercial side, too, when you're thinking about what is the next best action for my Salesforce to do? If I'm pulling in my my activity data and pulling in my digital type data and all these different streams, I can then inform my reps as to what is the best way to engage with a physician now, not in general, but right now?
Yes. We talked earlier, then there's so much data now for reps. It's hard for them to absorb at all. So like no mere mortal could do all of it. So the machine can actually do that better.
So you see the potential there as well? Absolutely. And you've been a pharmacy out during the years that cloud was sort of invented and became popular and now has become a standard in many areas. How does the role of the CIO change or how has it changed during that time from kind of pre cloud to today?
Yes, I mean, I think I think if you're if you look at how complex and you heard Henry talking about it before, I mean, that's a microcosm across the entire chain in pharma, but it's complex. And when we think about what it was, I had these things in how I was maintaining these applications, not just the software. I had hardware. I had a network. I had all these different things that I had to deal with.
And guess what? I start getting measured, not on the value of the product. I'm getting measured on uptime. How many tickets I'm getting? I mean, these are important, but as a CIO, that's not what I want to worry about.
I want to worry about, are we getting business value to our stakeholders? And so that's where from my perspective, cloud has really kind of changed the game. So if I give you an example of in a previous life, I had a civil CRM system, and we were moving over to Veeva CRM. And one of the key aspects to me was it was taking us anywhere from 6 to 8 months to get a major upgrade out and then months to get just kind of little things up and running. And really my team, as we migrated, the conversation really started to shift before it was, Hey, how come we have this outage?
Hey, how come these issues are ongoing? What's the status of this? It started to change as to you know, I don't have those issues anymore. Those are your problem, right? They're not my problem anymore.
And that's huge for me because now my team can really sit and talk about what are the business functions that we need? How are we going to make it better? What are some of the the new and innovative things that we can do as an organization. And if I extrapolate that up then, to my level, It's the same thing. I'm now talking innovation, right?
I mean, you'd never want to be in your executive committee talking about an outage. I've been there. It's not a fun thing, right? But quite frankly, I think I can count in the years I've worked with Veeva, maybe one outage and it was for a very, very small amount of time. And I said it to the stakeholder at the time.
I was like, oh, well, this is in Veeva's hand. Oh, okay. We're good. Right? If that were mine, it would have been a completely different story.
Yes, then it's all hands on deck for you. That's right. So then given that given your ability to focus more on adding value and understanding the business, what are your highest priorities as a CIO today?
Yes. So again, I've been there maybe 6, 7 months. Our CEO brought it brought in really kind of across three three perspectives. One is, as I described earlier, we've got a nice pipeline that we've been working through and we obviously are looking to continue building capability in that area. And so part of my job is to make sure that we've got the enabling technologies across the R and D side.
And if you think about some of the stuff Henry just presented right along those lines, right? Probably more important in the shorter term, but certainly as well in the longer term is, I need to be launched and revenue ready. So as a pre commercial organization, We're all hands on deck right now, getting ready for launch. And that means building out capabilities around CRM. Building out capabilities around revenue management and how we're going to interact with different stakeholders within our ecosystem.
So how do you think about the different technology choices around commercial? So having used Veeva serum in the past at a much larger place, What's the approach that you're going to take this time?
Well, so my view, I like to kind of look at what's well established within that's out there in the marketplace. And as a small company, I don't have a lot of luxury of placing the wrong bet. And so being able to look at things that are leading class or standard like a Veeva CRM, for example, to me, you'd be hard pressed to find many sales reps that are out there that haven't used Veeva CRM. As an example, right? And so it's a pretty safe bet from my perspective to be able to put something stand something like that up similar like promo mattes, same type of thing.
And so I'm looking for the things that are aligned with my strategy, a near 0 footprint, on premise. I want a platform approach. So again, similar to what I just heard, and I swear I only caught the last few minutes of it, but when I look at that kind of platform approach, to me, that is what this is about, is I need things that need to be able to extend beyond one application because I need to extract value as I go as I bolt things on, right, versus taking applications all over the place and it becomes costly and the integrations become very difficult.
I'm going to open up for questions in a few minutes. So you want to start thinking. So what are the different vault products? So you're just talking about CRM and you have a decision to make in the future. What are the different bulk products that you have at intra cellular?
Yes. So we currently in production with quality docs and e trial master file, eTMF. And we're in process right now with the quality management system. Okay. So QMS.
So you had quality docs looking at QMS. How not
to ask an obvious question, but how does the fact that you had quality docs influence what you're thinking about QMS? Like, does it make it an easy decision? Did you have to still sell everyone up the chain and all, everyone? Or does it, at some point, become, logical?
I mean, I think it's logical. I mean, first, let me take you back in my own history of the equality docs like application. Right? And so I've lived the nightmare of having a document management system on premise. I've lived the same nightmare of having it hosted, not the cloud, but hosted.
And so when I came in here, this is the first time I've seen quality docs. I was pleasantly surprised. I mean, from a usability perspective, it's fantastic. I mean, I can't even believe how easy it is to navigate through. When you look at maintainability, I mean, as I said, it's your problem now.
I don't have to worry about that. Configurability is also another selling point And so when I to start knowing that it's not going to take me a significant amount as my business grows and I get a better context for how we're going to operate, then I can make those changes later. But more importantly, to the question that you have, it's interoperability. And so let me give you an example, and Henry kind of touched upon this, But if I have an investigation within our, within our company, and that requires a corrective action. And let's say one of the corrective actions is a, an update of a standard operating procedure.
And then of course, that standard operating procedure requires that whoever is executing that standard operating procedure has to be trained. And that training has to be done by XDate. Right now, those are, in many companies, those are 3, 4, 5 different applications One of the reasons why I like the fact of going to QMS is that concept of the platform approach. And so you've got now You've got investigation in CAPA and QMS. You've got the routing for approval and updating the SOP and quality docs.
You now have training, which currently there's a small part around just assigning training, but that's going to expand into being able to track training. And I envision and I hope that this is a part of where that loop will close is that as soon as I finish the SOP, That should set off a trigger back into my QMS saying that that activity is complete. Same thing with the training, as soon as everybody has executed the finished training, That should be automatic. I shouldn't have to worry about that anymore. And those components of that particular Capa are already automatically closed up.
So I mean, long story short, but that's where I, when I kind of think of this, to me, that's an important consideration when choosing QMS.
Now one of the questions that investors ask me is, is there a limit to the number of things that a company will buy from Veeva? So is our could you have too many, like, orange eggs in that basket? Or how do you think about that?
Yes.
That's a tricky one, right? I mean, On the one hand, you look at, again, my strategy of a platform, Well, let me give you an example. So I read an article today or not today, this weekend that showed the clinical process continuum from the protocol development all the way to the clinical study. And let's just say for purposes of this discussion, 7, maybe 8 different kind of key processes within there. And they highlighted the number of companies, that play in that space, but it was unique.
So they only allowed Veeva, for example, was only in one spot, one process, not across. I counted there was 100 different companies That's not products. That's companies. That's amazing. And then you think about the fact that I'm not using all 100, but it wouldn't be unheard of today for me to use 15 to 20 different pieces of technology.
That's crazy. And that's why I kind of like Henry's message Because now all of a sudden, the more I can consolidate, the simpler it's going to be. I mean, that's fantastic. So from that perspective, This is great. And for a company my size, leveraging that best practice and industry standard is huge.
Now I will say as a pragmatist being with one company is a little scary, right? But that being said, there's no evidence that I've seen in the number of years that I've seen Veeva, but that's a problem. And I have lived that with other companies that have grown fast and got fat and happy. I've yet to see it with Veeva and all hold you guys accountable for that. So
Great. Well, I'm no longer fat, I didn't, but and I'm still happy Alright. So let's open it up for questions, from any of the attendees here. And we have, roving mics in the back there, Frank.
Thank you, Sandy Draper at SunTrust. Dan, if you could talk a little bit, I would assume at a company, an intracellular size, you guys are, using CROs. And when you think about the different technology that you want to control versus you basically handed over to the CRO and say, you pick your technology, you know, how you do your practice. How do you think about where you want to insert your directives around technology and where you're willing to just hand it off to a CRO?
Thanks. Yes. It's a good question. And it probably differs from study to study, but ultimately, I need to hold my CRO accountable, right? So if I've outsourced fully to a CRO across the data management and that sort of thing, for example, I need to be checking on them.
And it's not good enough for me to say that a CRO says, Hey, we're on track. I want to get extracts of the data, which means I still need it's my data. I still need to bring it in and we still need to do levels of review to ensure that things are still working appropriately. Does it mean that I need to have my own EDC for a particular study, not necessarily, but I do need all of the data that comes from it And that platform, again, is where I would see is important to me, whether that's an overall data warehouse or whatever, I still need that that ultimately because if I take it to the next level, not just from a study perspective, I take it to a pooling of data across studies, which ultimately goes into submission, I need to look at safety data, for example, across all of my studies. If I have different CROs doing studies, that's hard to do, right?
I'm also going to pay my CROs to do a lot of that work. So I like to have that data that to me is really the most important part. The application, not as important. That's probably not entirely fair. But it's how do I get that data and then do something with it after?
Sterling Auty with JP Morgan. Dan, thanks for doing this. Really appreciate it. Want to go back to, you mentioned the 15 to 20 piece of technology through the process. I'm going to ask the question this way.
What are the other vendors that are important within those 15 to 20 for your company? And how is the integration if there is integration between the Veeva solutions of platform and those vendors?
Yes. So I'm going to answer the question not with my current company, only from a standpoint of, as a smaller company and back to the point over here, we're right out pretty reliant upon the CRO technology. And so some of the things that we're bringing in is to look at that end state data, if you will. If I look at the prior company where I was the America's IT head and globally I was responsible for for the clinical development technologies, I'll take it from that perspective, if that's okay. So we would have, in that case, we didn't have any Veeva products, quite frankly.
So what we had was we had, face forwards or oracles product for EDC. We had we did not have an overall clinical trial management system. We had kind of a homegrown system that helped us keep track of key milestones and key dates. And we were reasonably outsourced, from a standpoint, but, and then we had things like statistical analysis. So we had a bunch of different aspects of SaaS, which is kind of the base, but the various visualization tools around that.
And then, from an overall data warehousing perspective, we tried to implement a number of times how to get that panacea of a data warehouse. And we one of the things that we struggled with was cost was 1. And so without getting to name a competitor here. There's a pretty big competitor that Veeva has that, that they've got a model where they're pretty much focused on the big pharma. Aisai was a midsized company.
And so we didn't feel the love, if you will, around what our needs were at a price that that we could afford. One of the things I love about the Veeva model is that it's a consumption based model. Right? And so for a company our size, I get to leverage all of that technology, that the same that across the street, Pfizer gets to use, I get to use all of that. But just for what I consume of it.
Now I don't know that I answered your question fully. So if you want to follow-up then.
I probably have time for 1 or 2 more. All the way in the back?
Just Two questions. One is kind of a slumber 1, which is as you've seen the Veeva kind of portfolio grow itself out, what are the other kind of pain points that or modules that you think that they should address that they're not currently talking about? And then second, as you think about kind of complex data management as just a class of of software or class of offering that you have that you utilize, how
does that
compare to other foundational software platforms you might use, whether it's CRM or ERP. Is that the same conversation? Is it fundamentally different? Where do you rank that kind of relative to the needs, like the dollar amounts, sales cycle? Any thoughts around that?
Okay. Say your very first part again and I'll tackle that one first.
Sure. What other pain points should be the address that they're enacting?
So This one is interesting only because Henry said it wasn't this when he described it. One pain point that I have strangely enough is, is training. So most companies, say that they've got, they can get to a single training instance, across both the R and D and the commercial organizations. And that's fair. We we did at my last company.
The problem as I see it is, is that we had success factors at my last company for the training. And we had to validate it. Success factors doesn't validate software. And they also, because of their model, they're pushing out software every 6 months to 12 months. And you can only be an n-1 or an n-2.
I can't remember exactly which, which effectively that I had to almost every year revalidate my training application because that's a requirement for Gxp compliance. That's a problem. That's $100,000, $150,000 every year for us to do something that really shouldn't be done. And when I look at what Veeva has done on the quality side with their validation services, they do 90% of the heavy lifting. So for me, I would love to see an environment where we take training, which can cover my R and D staff as well as all the way to the commercial staff.
You guys are starting to own both sides. It would just be logical for me to kind of see it go across. And your second question, remind me again.
Was when you think about complex data management or Vault, in general? Like how does that conceptualize in your mind relative to other foundational platforms that you might use on ERP or CRM? Kind of all the vectors that are kind of important?
Yes. I mean, I start to look at it. Again, I said at the beginning around platforms, ERP is a platform, right? CRM is a platform. And what I heard of the several minutes that I heard, Henry talking I can see where that could very easily become a platform.
It's almost like shared allergy, right? It's an ERP of clinical. It's incredibly complex. And you heard some of the stories that there's just a lot of touch points and to be able to to have that all in one platform all talking to each other, where I don't have to do the work, I put a high value on that.
All right. Great. Well, with that, Dan, I'd like to thank you very much for taking the time to spend with us and our investors. I know you guys appreciate it, as well. We can give you a quick round of applause.
Tim. Tim Cabral, our CFO.
Thanks, Matt
and Dan, and good afternoon. As Henry said, I'm I'm happy to be here as well. Let me advance the slide here. So again, thank you for coming this afternoon and listening to us and looking forward to the Q and A here in a few minutes. As you've seen today, Veeva continues to execute very well.
Since early in our evolution as a company, we've delivered a unique and powerful operating model of both strong growth and profitability. And with consistent and disciplined execution, we continue to deliver strong financial results and as importantly, delivering customer success. And looking forward, we expect our focus of innovation to enable us to were delivering materially ahead of the $1,000,000,000 run rate plan we shared with you a few years ago at this venue. So while many SaaS companies that you all know are still in the early stages of proving out the leverage of their model and some are even still burning cash, You can see Q2, in fact, and Peter talked about it earlier, marked Veeva's 36th consecutive quarter or over 9 years of growth and profitability, And over the past 2 years, while we've done that, we've continued to deliver new products addressing large strategic markets which we expect will materially contribute to our Finally, as you know, our profitability has been meaningful with the last roughly 2 years showing operating margins in the low 30s, and our current guidance for the also create healthy cash flow from operations, including fiscal 'nineteen's guidance, our cash position from early 2014 will increase roughly four times, culminating this year in more than $1,000,000,000 in cash and cash equivalents.
So this operating cash flow margin over the last couple of years been into the 30s and really enables us to have optionality from an acquisition perspective and certainly a very strong balance sheet as we partner with some of the largest companies in the life sciences market. Today represents roughly 5 years since we took Veeva public And in that time, we've consistently executed, delivering strong growth across a number of key measures of a successful cloud company. As we've done throughout the history of the company, we've increased our TAM almost twofold with new products that address our customers' key challenges. At the same time, we've increased our customer base more than 3 times, and these customers are using more of our products as you saw in Matt's slides earlier. This obviously leads to very strong financial results, both on the top and bottom line.
So as revenue in this time period has grown four times, The leverage of our operating model has also improved, meaning that our bottom line results in our cash flow has grown six times over that 5 year period. Looking forward, with a healthy pipeline of products to drive future growth. As you see here, these products are in different stages of their maturity curve. Today, as you know, the products that are primarily driving our growth are in the upper half of the slide, while the newer products we've announced and launched in the last couple of years are really going to drive or create potential for healthy growth beyond While we will see some revenue contribution from those newer products as we get to the $1,000,000,000 revenue run rate, I did want to reiterate how we think about new products and our approach to the go to market or their market entry
in each
of these markets, like safety or outside life sciences initiative, we start with the goal of building the best product. We then look to partner with early adopters and really invest in their success and really invest in our learning. Once we've established strong customer success from those early adopters, we move into what we call the reference selling phase, which ultimately drives material revenue growth from that particular product or market. As discussed, This typically is a multi year process going through the early adopter phase and getting into the reference selling phase. And as such, we would expect the material revenue contribution from these newer products to fuel that growth in the years following 2020, but they're among the reasons why we believe we're well positioned to grow Veeva to a multibillion dollar company.
The combination of our strong products portfolio and our disciplined go to market approach gives us confidence in growing with this coupled with this go forward view means that we will hit the $1,000,000,000 revenue run rate, which we define as our first $250,000,000 quarter essentially 1 year earlier than we originally than when we originally set the target. Drilling down further, we've been making great progress against the 3 key measures since we initially rolled out the 2020 revenue target. First, the contribution of non CRM revenue, almost entirely led by Vault, as you've heard today, has now roughly hit 50%. The expanded use of our products by our existing customers and their early adoption of new products has continued to drive the number of eight figure customers to where we are today. And we also, in the last year, saw a very nice increase in overall 7 figure customers going from 85 a year ago to 110 this year.
And lastly, we continue to expand our customer count and in the last 2 years, we've grown that overall number by more than a 100 in each of the years. We've also seen strong operating margin performance over the past year, enabling us to raise our gross margin and operating margin target for calendar 2020. The efficiency of the Vault platform, as you heard from Peter and Henry today, and the higher contribution of revenue from our Vault applications, is driving the improvement in gross margin. The incremental gross margin in part will fall to the bottom line, but for some we'll continue to reinvest in our product and field teams as we continue to invest for customer success and future growth. The net result is an operating margin target of 33 percent to 35 percent for calendar year 'twenty, which continues to be world class relative to our stage of growth.
Let me finish by talking about one of the operating principles we talk about as a management team and as a company. Execution matters most. And you've heard this execution theme throughout the presentations today. What we believe is having the best idea guarantees very little. It's what each individual does every day, every week, every quarter, every year that matters.
It's about incremental progress and being relentless. Executing means we embrace uncertainty in plexity, go fast and iterate and always keep customer success at the forefront. I would personally say this has been one of the strong parts of the blueprint of Veeva's success. So with that, let me turn it back over to Peter for some closing remarks before we move into Q And A.
Thanks, Dan. Alright. Just one summary slide for me before we go into Q And A. So, yeah, Tim said it, we're on a path to become a multi $1,000,000,000 company. I didn't think of that 11 years ago, but now that's where we're at.
And we have a path that we need to do, and it's going to be hard execution, but I believe we can do it. We have to continue our innovation. We're well on track to do that. We have to go into significant new markets. You're seeing that with safety, clinical data management, sites, clinical network, Andy and Nitro.
We have this long term leadership position that we're establishing in our commercial cloud and our development cloud those are our franchises. Those are super important processes for a huge industry. We're the 1st tackle them, we have 1st mover advantage. Our focus there is to be the leader in like. And those systems will last on for 25, 35, 40 years.
That's the type of thing they are. We have a powerful and unique cloud platform. We had the idea to start doing that in 2010. And that was a major thing, and it's taken a long time. Now we're really seeing it pay off.
And we have a business model, the Veeva Way, that works inside of life sciences and it's proving to work well outside of life sciences. So in summary, that's, things are going well for Vida. And now I think we're bringing up for the team for Q And A.
Thanks guys. It's Tom Roderick from Stifel. So, kind of going through the theme of execution matters and the reference selling model has worked tremendously. It's kind of enabled you to kind of keep a focus on what you've done well while still stretching product lines new adjacent territories. Now you're stretching even a little bit more than you historically have and kind of specifically reference ADC as an area that maybe isn't completely adjacent to some of the things that Vault has had a different decision maker perhaps a different part of the organization.
Talk a little bit about what your customers are saying. Going back that reference selling model. Why are they asking you to do this? And from the perspective of what's missing in that solution set on the EDC side, what do you think you can bring to the table or what are you bringing to the table that is not there that, that really changes the game in that front?
You want to hear that, man?
Yes. Thanks for the question, Tom. So I think, and most fundamentally, one of the things that we bring is modern tech and reliable, performance, scalable, in today's world, that maybe seems like it should be easy for a company to claim. But in companies that are serving the life sciences industry, it's not normal to have real multi tenant cloud software that works all the time, from a company that deeply cares. So just bringing cloud technology into some of these spaces, we are the first ones.
Like, EDC, there was some cloud, but not real multi 10 in cloud, safety. There was nothing that resembles cloud in any way in safety management. There was nothing in quality when we entered. There was nothing in regulatory. There was nothing in CRM when we entered.
So we're the only real cloud provider in most of the things that we do. And the only one that spans multiple areas. So just fundamental, all of the advantages of cloud computing, we're able to bring to these areas of a life sciences company of that industry that we're really underserved by modern technology. I think if we look in EDC and now CDMS specifically, One of the things we bring beyond that just technical advantage is the integration with the other parts of the development cloud. Where I'd like to correct your question just slightly, it is connected.
So it is just as connected to CTMS, as the eTMF is, as an example. So, CDMS is an integrated part of an overall development cloud you're right that it's always been separate, but that wasn't good for the industry that it was always treated as a separate thing. And then within that, we're going to have an expanded product offering that is beyond just what people think of as traditional EDC. And as Henry described, it should have never diverted. Clinical data management should have been part of the EDC or vice versa.
And so the solution that we're working on now is broader than what any one vendor is bringing to that market with the advantage that it's integrated with everything else, And with the advantage that it's the latest in cloud technology.
Thanks. Kirk Materne at Evercore ISI. Can you all talk about now that you have the development cloud platform and you can go and have a maybe a bit of a broader discussion about digital transformation with a lot of the key stakeholders. Is that impacting sort of how you can go to market with bigger system integrators? And if that's the case, are your lands going to get bigger?
It's always been a great land and expand myelbits specifically on the clinical side. I'd be curious if there's an opportunity to start seeing a bigger footprint to start? Thanks.
I think that it depends on the market. I think that in small and medium market, definitely. I think that in the, in the bigger markets, I think you're going to see bigger decisions on we're going with Veeva, then the implementations, I think, are still going to be, a little focused because there's so much old technology and a lot of interconnection of those technology where we need to figure out a way of taking each component out, replacing it with Veeva, making sure that everything still works, and then taking the next one, and the next one, and the next one. So I think that we will work with more partners and make of those conversations are about building accelerators. Can they invest in things that will, in essence, accelerate the ability for us to remove the old stuff and replace them with Vito.
Where I've seen the partners getting excited is they're all building businesses in helping companies implement each one of the areas. So quality management practice or a regulatory practice, where I see a lot of our partners getting excited is once companies have evolves in multiple areas, helping them to reimagine and redefine their processes so that they can dramatically prove the way that the place runs. So it's and it doesn't generally, in a large, large company, it doesn't happen the same time because each one of these areas is so large. But that, that process re imagination I think, is not just for Veeva to own, that's something that we'll do with partners of of large and small over time.
Thanks Sandy Draper at SunTrust. A few weeks ago, maybe about a month ago, Amazon, Merck, and Accenture announced a partnership to build a clinical data warehouse, so not on the commercial side, but on the clinical side. 1, just wanted to see if you had any reaction to that. And then relative to your comments around Nitro for going after that market with a with a purpose built technology, does it why would somebody and you could have a lot of failed big data warehouses another attempt at it in more, again, more on the clinical side, but just how should we think about that announcement relative to what we've heard today around Nitro?
So in terms of the Amazon announcement, I'm not very familiar with that one. We'll have to get back to you specifically on that. As why would why would your question is, why would they want to do something with us on Nitro when there's been a history of quite a issues before with other ones?
Well, actually more, you know, another attempt, because there have been a lot of failures, another attempt to get a big integrator get Accenture in there. You get an off the shelf Amazon and you get a customer to try to build their own proprietary data warehouse. That seems that's very different from what you guys are articulating with Nitro. And so just curious. I didn't know if you'd seen that announcement, but just thoughts on why companies would do that?
How do you target this market when you periodically have people say, Hey, we we're Merck, we want to do it ourselves, and we're going to own it ourselves. We don't want to share something to somebody else.
I understand a little more. So I have to say, I don't know the specifics of that Amazon or Mark 1, but in general, this type of building of custom data warehouses has been going on for about 20 years, literally. So it's just a pattern and a habit and it's and it's what people know And in times of stress, people go to what they know. I did that before. I'll do that again.
I used to use Oracle or Teradata. Hey, I'll just I'll use that red shift, and I'll do it again. I can do this. Nobody's come out with a packaged offering yet. Except for Veeva, and we're new and unproven.
We just have 3 early adopters. So it's just a process of change management. I view it as very similar when we brought out cloud based CRM. That took some time. It takes some time or the development cloud.
That takes some time. So it's just time and change management make no mistake. We have to mature our products too. Are we ready to install Nitro and have it go swimmingly for the largest pharma companies, not yet, right? We have to focus on a few early adopters.
Hi,
Carl Carirstead at Deutsche Bank. Maybe 2 for Tim. Tim, on the new fiscal 'twenty one targets, maybe a couple of questions. One is, clearly, what I think stands out to everybody is the 300 basis point increase in your target non GAAP operating margin, super impressive given that it's already at a pretty high level So relative to a year ago, when you put up the 30% to 32% target, what's changed most significantly? Is it that your commercial cloud margins or tracking way above what you thought?
Is it that Vault margins are expanding? What's the delta to cause that shift? And then I've got a follow-up.
Sure.
Yeah. I think you hit it a little bit Carl on the second one. I think what we've seen and you've heard it as we've talked about Vault's contribution to total revenue over the last year and the growth that that's creating, on two fronts, actually. First on subscription gross margin, We're seeing some uptake there, but we're also seeing really strong margin in some of the services project in some of the newer areas like rim and quality, or it seems like the attach rate is a bit higher than what we saw in clinical before. So I think that's what's creating some of the uptick in our gross margin feeling.
And that also drove some of the increase in the operating model you saw me change or saw us change, excuse me, this time around.
Okay. That's helpful. Thanks. And then maybe a follow-up on the, it looks like a reaffirmed target for 20% subscription revenue growth. So, Tim, I think for next fiscal year, you've offered a little bit of color on what the split look like by the commercial cloud business versus Vault.
As you think about getting to that for fiscal 2021. Any color on what the respective growth rates between those 2 major buckets might look like?
Yes. So to be clear though, we haven't given specific guidance for next year in terms of the growth rates of those. That's something we'll typically do in our Q4 call, which
I guess
I meant this year,
my apologies.
So not giving any guidance there. Again, we look at a growth story in the near term, as you know, Carl is being primarily a Vault Growth story. The portfolio that we've built of products and applications that we're delivering to the market and the strength of that growth is really the near term story. What we do see is not a lot of variability in the growth rate Hey, Dave Larson with Leerink Partners. A question for Peter.
10 years from now, what percentage of your revenue would you like see coming from, like, outside of life sciences? And how are you going to balance that growth between life sciences areas? And you know, sectors outside of that space?
10 years from now. That's 2028. I hope to be still riding my mountain bike and things are going well. That's that's a long time. So we really, I I really don't plan that far.
So I really could couldn't answer that. We would have to see how that goes. I find that those types of very long term plans, they can distract you. So I certainly have 3 year, 5 year plans in my mind, but nothing out that far. We just have to see how it goes.
It's huge outside of life sciences, right? It's, life sciences as a term of the economy of the world is this and everything else is very big. Our biggest, thing that we can do is remain focused, right, not try to go everywhere all at once, stay within our reference selling model. Life science is plenty big enough. I mean, and then outside of life sciences, it's huge.
We just have to focus in. So short answer is I don't have any 2028 targets yet.
How about 3 to 5 years?
We do have targets there, but that those are something, since We're in the early phase out there in quality 1. So we don't want to expose those targets now because they're still moving around, you know, in we don't really we need to focus on the success of our early adopters, right? We don't need to do anything other than that. If we get those early adopters very live, very successful, QualityOne will go because we have the 1st mover advantage. Nobody else has tried to do this thing yet.
And we know that it needs to be done. Quality is important. You got to do this stuff. So I feel like we're we got the runway that we can see down the field, we just got to hold on the ball and run down the field, right? And so that's what we're focused on.
I didn't know that 3 years ago. When we got into it, right? I, you know, it was unknown. We didn't have any customers. Now we have 30, 31 customers, 7 figure, with the $10,000,000 plus of revenue.
Now it's just, gosh, you got to focus, got to execute. Oh, Brian Peterson for Raymond James. Kind of on that note, Peter, in your slides, you did reference a 5 year plan for operational excellence, I believe, towards outside of life science So on the outside, what metrics or what how should we look to track that as we look to evaluate that business over a 3 to 5 years? Is it international? Is it potentially different markets?
How should we think about that? Well, we'll go we'll give you updates as we go along. I think the things to look at are early adopter success. At some points, along the time, we'll give you revenue numbers at certain points. And that's very concrete there, right, when you give that.
Those are the things to look for in anecdotes. And I believe you'll start to hear about us from customers. Right, then that's something that happened inside of life sciences with the community that followed us pretty closely, started to hear about that from the customers. So I think that's a very good barometer as well.
Thanks guys. Spreadsales from B. A. Merrill. Another one on the outside life sciences opportunity.
Obviously, the product is very extensible into these other industry verticals Where are you, in terms of addressing that opportunity with the sales force? How different is it, how much domain expertise do you need in these different verticals as you take falls into these other industries? And what's the plan to kind of build that out over time?
So, in terms of QualityOne, that's our first offering. It is actually even different when you look inside of CPG, M chemicals, and cosmetics and industrial products. There are some differences there. We have to have people who know how to do implementations there, who know what to look for, how to talk about it. So it is different.
If we expand QualityOne even further, yeah, there's small things you have to do, right? We're not selling QualityOne into airlines now, right? If we did, there's some certain things we have to do, food manufacturers. If we did, there's asset and a few other things that we have to do. So, yeah, Each one is a set of things, and you need some domain knowledge, you need some product features, you need to start that reference selling.
It's very, very broad, and it and it has a set of specific things. So it's hard, right? But and that's probably why nobody's done it before. That's what's exciting to me. I think we can do it because we have our processes.
I think it's most analogous actually to pharmacy or M in this way. Pharma CRM is very difficult because it has regulatory requirements all around the world that are different. If you introduce a drug in Japan, there's a certain set of things you have to do in your CRM, right? US, you have to handles samples differently than Italy, etcetera. So it's hard to make one set of code do great for around the world.
Same type of thing in quality. How do you make a system that works great for many, many industries? It's hard. But I think we can do it. And so that's, that's why I'm confused about it.
And then there's tremendous leverage because when you think about it, these industries have had very specialized vendors in that area, So their market is only so large. They're not cloud. So the outcome of this is not good software that these customers are kidding, right? Some of the things that I think we're going to automate right now will be, today, are mostly done on spreadsheets emailed around. So it's just sort of a wasteland out there.
And that's why I'm excited about it.
Hi, guys. Ken Wong from Guggenheim. Matt, in your slide, you mentioned the TAM going up from $8,000,000,000 to $9,000,000,000. Not sure if it just went really quickly, but it didn't look like knife was part of the increase in TAM. I'm just wondering, one, why that is?
Is it just longer time to revenue and kind of roughly help us size that? And then I have a follow on.
Yeah. So the way that we always define the commercial cloud was the products that we had today and the products we could build nitro and that whole commercial data warehouse analytics piece was one of those things that we could build. So it's within the original $3,000,000,000 and now we're addressing a larger percentage of that. And we didn't I mean, do I want to size it? We really didn't do a very detailed analysis.
So I'm not comfortable giving you a specific number, but it was within it was within the $3,000,000,000. So it allows us to go after a higher percentage.
So is that, that plus portion of the TAM?
No, no, no, it's within the $3,000,000,000. It's not a plus. So, Yeah. What I'll share though is if you look at the number of dollars spent on CRM software, versus a number of dollars spent on and around a data warehouse. We think the data warehouse piece is at least as much.
And then, and then also on, on Nitro, I think kind of one of the things that's valuable valuable about it mentioned kind of a lot of connectors going in. You guys are going to productize that. Any concern that you might put into an issue like you saw with network where you third party vendors that might deliberately try to block you?
Yes, we could have that. We've had this issue, we've talked about it before with network and open data where IMS has exhibited some anticompetitive behavior, not let their data be put to our software and therefore slowing down network. There's potential we could have that with Nitro as well, but we're early days there. We're working with our early adopters. And that's what's important.
And so we're improving our product. We take a long term view on these things like Nitro and Andy. They're really going to transform the industry And we'll work through any kind of a data access issue like that. Over time, it may take some time. And we don't have enough track record with those data providers yet to predict.
I will say we've had never in our history having we had a problem the data provider, actually, other than IMS, right? And that's why we have the lawsuit going with them, etcetera, but we're confident we can get through it.
I had two questions. The first one is on EDC and just, I guess, understanding either now in the next 12 months your ability to ingest lab data, genomic data, medical images, and health data, are you at that point where you, you have that capability, or are you kind of that still have the roadmap to get there?
So, I'll address actually each of those a little bit the ingestion of those components will be in data workbench, which is targeted for next year. But I want to differentiate between labs, which is completely gonna be ingested. And then things like imaging where the actual images, need to be treated quite a bit differently. And what we will ingest is what needs to be submitted or analyzed, and that's the imaging result, the actual analysis of the image, and what you actually need to learn from that image. And then from an M Health perspective, it's similar.
We're not planning and our in our interest and our customer's interest is not to ingest billions 1,000,000,000 of records, that are not important. What's important is what you find out from that M Health, device. And the actual result of somebody else who looks at that data says that there's something that's important to report, that data will go into our environment. That answer your question?
Yes. And then just one other question. Your discussion of, I guess, the investigator trial site product I was just curious if you'd actually charge the clinical trial site, you know, outside IBioClinic or if it's sort of part of the the sponsor trial. And so I guess the sites would get the software for free, just what the plan is there here?
We'll charge the sites for the, what we call site docs. And that's, I think that's, that's normal, right? These are large in institutions, they need they actually wanna pay for that stuff because what they want to get is something that optimizes their processes. What they don't want to get really is something that they use that helps optimize the farm company's process. So they're used to paying for that.
And and many, many of them custom build these things today. So, certainly we want to charge for that charge a good price for that. That's the way we can make a great product.
This is Sterling Nadi from JP Morgan. So one tech question and one market question. On the tech side, looking at Nitro, when you look at that, I guess, that being that data exchange specifically, you
talk through the complication of
data mapping and and syncing how are you going to accomplish solving that? What's going to be the configuration, especially as I think about the, you know, the many pairs that are going to be created, right, between it, How are you going to manage that complexity? And then one follow-up for Matt?
Yeah. There's really 2 parts to that. One is the the the interaction data that it's created from our CRM system, and then the content and content interaction data, which, okay, that's also from our promo apps. And there, basically, we have some pretty smart software that wakes up every day interrogates our CRM interrogates our promo apps, looks for any deltas that have been made in the system and knows how to then automatically map that into the canonical model the standard model of Nitro. So that's where a lot of the IP is.
That's a serious amount of Java code that we've written that figures that out. You could consider it as sort of an adaptive ETL because we know exactly, our CRM system tracks all the changes that people have made in it, and we know what those are. And so we know how to do that mapping. Now for the industry data sources, like let's say you're buying, claims data. The vendors that provide that data, they don't change their formats very much because when you think about it.
They have to provide that data in pretty standard formats because otherwise, everybody has issues. So once you get that done right, It's pretty stable unless the vendor comes out with some new data. And then we think over time, we'll be in a leadership position. They'll talk to us Hey, you're going to have version 8 of your data spec, what's in there, we'll get it ready ahead of time, and we'll do it. That's what we've done in CRM with our ecosystem of partners right now.
There are small partners that hook onto our CRM ecosystem. We work very well with them We keep up to date what they do. They keep up to date with with what, what we do and vice versa.
Okay. And then one for you, Matt. You put up the slide looking at the number of vaults by cohort. I think the oldest were like 3.4, some of the earlier ones were somewhere around too. I'm kind of curious what you think the logical evolution.
So those older, is that 3.4? How high can that go realistically? And where should that overall average migrate to over time?
Can realistically to 15 because we're gonna have 15 applications. I think you heard it from Dan that He could for those 15 applications, he could deal with 30 companies, or he could deal with 1. And so we are approaching development cloud involving general, that we have to be such a good partner to each and every company and to the industry, that they would not be fearful of going all in and getting all 15. So we are really trying to create the people and the processes and the relationships and the trust in the quality products that someone would actually want to get all 15. Now we don't even have 15 today, but we're on the way.
What is realistic to get? I mean, I think there will be many companies over time that have all of them, particularly small companies that don't even have to replace something. So we've seen companies buy 3, 4, 5, 6. I think 6 might be the record, but 6 volts at once. We're going all in.
And I think that if we continue to stay focused on customer success ahead of our own personal success. And the industry knows and appreciates believes that we really do care, that is not just about us, that we're really trying to help each and every company and their individuals and the industry to improve, then I think there isn't a limit to where that average can go, and it should continue to grow.
Hey, guys. It's Stan Zlotsky. Good morning, Stanley. Two quick questions. One may be either for Peter or Matt.
On the commercial cloud, the you're at 25% penetration now and, growing this 10% to 11% range. Thinking about this product, line over the next 7, 8, 9 years or so. Is this what we should be thinking about that this commercial cloud continues to grow in this high single digit, low double digit range, because you just have this long runway of growth going forward. And then a quick follow-up for Tim The fiscal 'twenty one operating margins, 33% to 35%. Any more thoughts on where your free cash flow margin might be at that point.
Thank you.
In terms of the commercial cloud growth, yes, we're not going to give guidance, specifically for the out years, but it can be a consistent grower, right? We can, it'll have it up and down like all kinds of product lines. We don't know exactly what new products will introduce. We don't know exactly what could be the price that we get for Andy, right, because we haven't made that product yet, we have to explore there. But I think your characteristic is right as a consistent thing that can grow, it's not going to have huge spikes.
I think it's a way to think about it.
On the cash flow margin stand, I think you in the low 30s. And I think it could work a little bit up from there if you include the excess tax benefit that you've heard us talk about around stock based comp, but it it has a 3 handle. It's not that far below our operating margin.
Brent Bracen with KeyBanc. Two questions. I'll start with, with, Tim here. Practical question, but, what's the use of cash? You know, it's approaching a $1,000,000,000.
You did buy a company a few years ago, Zinc, what are the, the, the balance, as you think about uses of proceeds there with the reference selling model? Does it make sense to consider M and A, maybe outside of life sciences. Walk us through the, the logic there from a tactical standpoint around cash. And then I have one follow-up for Matt.
Sure. I think as we think about the use of cash, it hasn't really changed, Brent over the last couple of years. I think we first, what I always talk about is we first start with the fact that we're partnering with some of the largest companies in the industry that we serve, and they're putting a lot of trust in us. So having a very strong balance sheet and a cash balance, a strong cash balance. And as you know, we're debt free is certainly a long way towards having that strong balance sheet.
So they look at us as being a very stable partner over the very long run. So that's 1st and foremost. I think the second thing as you talked about is the cash balance today and the growing cash balance gives us the optionality to do acquisitions in the future where we see the ability to either drive future growth, drive customer success, or maybe catalyze our journey in a market a little bit faster we otherwise would. So I think it gives us the stability of the balance sheet and the optionality of acquisitions is we think about our cash balance today.
And is a priority rent acquisition changed at all? It's a priority? I'm sorry. Has a priority changed at all shifted of acquisitions?
No. I wouldn't say. I mean, Peter and Matt, you may want to chime in here. I don't know if the priority has changed. I think we are we're always looking around for opportunities to, to use the cash in an acquisition way we gotta find the right one, as you know.
All right. Good. And then, Matt, 2 things stood out to me today. 1, the penetration rates, did you think about 25% penetration installed base around, commercial only 10% penetration of Vault, and then Henry's comments, I think, around going all in, with some customers feels like it's something different or you're simply something different. So walk us through the next 2 years, the number of customers, I mean, is this changing relative appetite for your existing installed base customers to go on in, all in, or is this more of a 1, 2 handful of customers that are going on in.
Just any sort of scope over the next 2 years, the number of folks going all in would be helpful. Thanks.
I think it's probably actually similar in commercial and Vault, the way that it feels it's happening. And that is that if you think about CRM and CRM add ons, we had some add ons that were new. You know, a line was new and events was new and engage was new. And so for someone to go all in meant they had to be an early adopter in multiple things. So now on the commercial side, there's basically 1, well, yes, there's one thing, Nitro, and ultimately, Andy, that will be very new, but the other ones work.
Like, we know that they were. Even Engage is new. We know the product works, but there's a lot of business process stuff that still needs to get worked out around it. So you could go all in in commercial and not have to be an early adopter unless you go do a Nitro. And then I think it's similar on on the R and D side in development cloud where to go all in would have meant you're on the bleeding edge for multiple things And in fact, you still could be.
So when we say all in, we're thinking in terms of their strategy. It doesn't necessarily mean they buy everything all at once. But 2 years ago, you couldn't have bought multiple things without being an early adopter and at least one of them. And now we have more mature
Can you provide a little color around how much some of your customers actually save by adopting more and more of your products? Because I'm assuming, I mean, they're obviously using one system now and they convert over to, you know, a Veeva platform. It's not actually costing them a lot of incremental dollars. And in fact, they might be, you know, saving money Can you give any metrics around that?
Yeah. So, refer to the commercial side of the business. Your question wasn't specific to commercial R and D. On the commercial side, we have some saw commercial Vault is a good example, where, companies spend, I mean, large enterprise company may spend $100,000,000 or more on the commercial has to invest differently because the requirements and the messaging needs to be different for, it's for every brand and every country. So in that scenario, we work with customers to create the business case and the business case can be tens of 1,000,000 of dollars that they create.
Now it takes time to realize that savings and realize that cost. So a customer may have to be work at that to change process, because it's not simply about implementing a system. A system is a key part of that. But there's a whole number of things that they have to put in place to do that. So that's just one example where our customers, implement Veeva and they change their process.
And over time, they start to realize and recognize more and more of the savings.
In that case, they're generally replacing multiple systems with Vault Promomax. And that's one of the things that enables that global sharing. More broadly, to your question directly, we're generally replacing multiple things that are either custom or on premise They may be old and just on maintenance. And so the dollar for dollar, what they spend today versus what they spend for Veeva, is sort of all over the place. And CIOs have been able to delay a big on premise upgrade as a way of cutting their budget for the year, where Veeva is an operating expense.
It's a subscription. And so some of our customers try to line up all the dollars and figure out what they're saving. But as people have gotten more mature, terms of their adoption of cloud, it more and more of the work that we do around ROI and value proposition is more on what is the value of the integrated suite versus how many dollars is it versus what we're spending today. That still happens because people have budgets, but it's very different than it was 5 years ago. 5 years ago, 100% of our kind of analysis around what things cost was total cost of ownership?
How many dollars are we spending today? How many dollars will we spend on Veeva? Today, I think probably the majority of it is what's the value of the integrated platform.
Probably have time for a couple more.
Thanks. Saket Kalia from Barclays. Question for Peter or Matt. I think we've talked about Andy as an engine to really enhance Andy to enhance the R and D experience as well. And and if so, would we need to to would we need another sort of data warehouse for that, or does that already exist?
Does that, does that, Krish, make sense?
Yes. That's does? Yes. There are certainly use cases for artificial intelligence across R&D, you know, in quality and regulatory and clinical. I'll give you a very end in safety, certainly in safety.
I'll give you a very easy one in our clinical and our eTMF, somebody can upload a document in there today. Etmf asked you, okay, well, what kind of document is that and classify it? In the future, we can just say, well, it's probably it looks like one of these, are you okay with that? That's a very small one but there are bigger ones like in safety to analyze an incoming safety event an incoming email about safety and automatically categorize it. Oh, this is the same one as the one that came in before.
So there's tremendous amounts of applicability. There's applicability in commercial content as well. One of the things in commercial content is to know there's a new promotional plea piece. Where are all the specific claims made in that promotional piece? Artificial intelligence could examine that promotional piece and pick out those claims and do that work.
So there's a tremendous amount of things that can be done. Now you're And those will get done over time. The key is you have to have the data on that. And yes, for the R and D side, it would need something else other than nitro, right? It would be in it would be some type of nitro equivalent for R and D side, because in Nitro now, that's focused on the commercial use case.
Clinical is a different set of data, but we know where that data lives. And it's interesting actually. There is 3rd party data in the in the R and D side, but it's not as much dependent on the 3rd party data as the commercial side is. It's more about the data that the pharma company generates and the clinical sites generate. Plenty of work to do.
Hey, thanks guys. D. J. Hynes from Canaccord. I wanted to ask about the target model.
It implies a couple of 100 basis points of uplift in sales and marketing. Just any color on how you're thinking allocating some of those resources. Is it product specialists to drive home some of the new efforts? Is it expanding reach to kind of capitalizing that mid market opportunities and outside of life sciences. And then I think part of the margin outperformance you've seen, I think you've said you've lagged a bit on your hiring.
Just talk a little bit broadly around kind of how you're seeing the market for talent and where those folks are coming from.
Yeah. Dijay, I think you answered most of your question. I think it is, as we see some of the products in the slide you saw on both Peter and I show, in terms of where they are in their maturity stages, those newer products that we're bringing to market are going to need resources in the field. They may be, We call them market owners. People think about them as product sales people, primarily are product strategists.
So that's an area of investment rounding out both the commercial and R and D teams on the life sciences side. And that also included our thinking for the near term needs from the outside life sciences, initiative as well. So it's a combination of the new products bringing to market and the field teams around those new products to make sure that we get through early adopter. And as we move into reference selling, we're really ready to get the flywheel going. In terms of hiring, as you know, the sales folks are hired globally.
We have global teams, in the U. S. And Europe and Asia and LatAm, so very different in terms of the market dynamics across the globe. We are, we have a big initiative called Generation Veeva that we're filling both our engineering pipeline with folks that were teaching them about the life sciences industry, as well as our consulting. And one of the things that Peter and Alan and the team have talked about is how can we take some of those new generation Veeva folks out of, out of university, how can we turn those long term into potentially being field folks as well.
So there's a couple of different ways with which we'll grow that team. And that gives you a little color, DJ, on where we're focusing our our investments.
All right. So we're going to wrap up. Thank you to everyone that's still with us on the webcast. I appreciate you all coming, spending the afternoon with us. We, we will have refreshments available on the 3rd floor, ambassador room.
And you can just follow the signs. So, Yeah. Again, thank you for all thank you all for coming. Appreciate it. And please join us for conversation afterward.
Thanks.