Live from San Francisco, California, theCUBE, covering MarkLogic World 2015. Brought to you by MarkLogic. Here are your hosts, John Furrier and Jeff Kelly. Okay, welcome back everyone. You are watching theCUBE live in Silicon Valley at MarkLogic World 2015. I'm John Furrier with my co-host Wikibon analyst, Jeff Kelly, our next guest is a customer of MarkLogic, Jeff Career Senior Director, product developed for Mitchell Juan. Welcome to theCUBE. Thank you. Jeff interviewed you on stage. So give us the lowdown. What's happening? What do you guys talk about? What's going on? What does your company do? And why are you here? Sure, Mitchell Juan's a subsidiary of Snap-on. Snap-on is a corporation very, very focused on just two things, right? Help people fix vehicles, help people run their shop better. At Mitchell, we do those things by delivering information to technicians on how to fix the car that's in front of them right then. Tell them what's wrong with it. From a shop management standpoint, we have a shop management software that's been running for 20 years and is now the source for our big data. So on day one, we threw the switch and had 20 years worth. So MarkLogic, CEO, is on earlier talking about the conversations that he's involved in. What are the top conversations that you're involved in with your job in terms of technology, your employees, customers, partners? What are some of the things you're talking about? How to take the information we have and better leverage it to fix cars? And where can we get new information? One of the things we're doing right now is we've got hundreds of millions of repair orders that have tons of information about what's going on in cars out on the road today. And what we're trying to do is figure out how to take that data and turn it into knowledge. To help a guy focus on the problem. He gets a car in his bay that he sees that car once a year maybe. He has no idea how to work on it. So what we do is try to help him by saying here's what we know about the car. We've seen it 170,000 times and here's the things that we know go wrong with it. And how to get that information to those people. We talk about that endlessly. So that's classic harnessing the data that already exists and put it in the hands of the user. Really fast. It sounds easy. I mean. Yeah, not that easy. Well, yeah. Well, you've got so many different sources of data we talked about in the panel. Talk about that a little bit. I mean, you're dealing with data coming from multiple sources in different formats. We have data coming from 27 different OEMs. And although the Society of Automotive Engineers would love to have you believe that there's a standard name for everything. Those 27 OEMs apparently didn't read that memo. So they will call, for example, an oxygen sensor by 27 different things. 27 different names. And a large part of what we have to do is to figure out what they mean in context. Again, to help that guy who doesn't know the 27 different names. But to him, it's an oxygen sensor. When they tell us that they then take that in the context of the vehicle they're actually working on and do it. So we have information coming in from OEMs. We have information coming in from hundreds of mechanics around the world. In North America, in Europe. If they see something unusual under the hood of a car that day that they're working on, they'll feed that information to us and then we incorporate it into our product and feed it to technicians. We're gathering sort of business intelligence, if you will, to the tune of millions of repair orders a month that we sort of pile on top of the 300 and some odd million we already have. And we're constantly chewing through that, looking for new things, looking for trends, looking for ways to help that guy fix the car.  Who's really, sometimes, John, we talk about business applications that are a little esoteric, a little kind of hard to define. But you're talking about a mechanic in a shop who's trying to fix a car and he needs certain data at a certain time. How is Mark Lodge helping you actually deliver on all that? What we've done is we've taken all the information from those 27 OEMs, we've put it into a Mark Lodge repository and basically broken it down into paragraphs. We enrich that with metadata about the context for that paragraph and so when somebody goes back to that oxygen sensor, we can say, well, here's a paragraph over here about how to remove it, here's a paragraph over here how to replace it. We assemble all of that into an article that's very, very focused on just that oxygen sensor and deliver that to their tablet, to their desktop PC, in theory to their phone, although that's a little suspect, right? Because it's a tiny little screen and a big wiring diagram doesn't look good on a screen that big. But very, very focused on getting them the right information at the right time to solve the problem that they have in their bay. It's one of the things I really love about the job is we're helping somebody do something, right? He's got a problem, we're helping him solve it. Yeah, they get faster turnaround on the inventory if they will, not sitting there, they get more churned, which is good for their business again, they make more money and they have happy customers. How hard is it?  To unify all this data is really challenging. They remind the algorithms that need to be applied to the data. So it's a classic case of you have new inbound data coming in.  How real time? How do you unify the data? I mean, I know it must be difficult because I know the complexity of the data. Share with some of the nuances of how you guys unify it together and apply it. We have an editorial staff, total of about 50 people, some dedicated strictly to taxonomy, to ontology, to management of the vocabulary of all those OEMs, if you will. And so they're all touching that, they're all making sure that it's got the right markup, that it has the right metadata attached to it, that we're identifying new things because they're adding new things to cars constantly, right? So we can't kind of define a car and walk away. We've got to redefine that car every year, again, for the 27 different people. For the aftermarket, one of the big challenges we face, particularly with the repair orders, is technicians may be really good at fixing a car, spelling's not necessarily their strong suit, grammar's not necessarily their strong suit. So as we're doing the analytics on those repair orders, we've got to sort of be able to derive, oh wait, when they use this term, what they really meant was, or to look at things in context, and to cut out the noise, because nobody cares that that car got an oil change, right? It's not germane to a problem with the car, typically. And so just sorting the wheat from the chaff, and that's very challenging. That's more of the ontology side, sounds like. So you have developers then, working on this stuff. Yeah, so how does the interface with Mark positive, they get, what's their user experience like, dealing with the Mark logic technology? We've built a very nice front end, that lets them sort of manage the taxonomy, manage the ontology. We're doing some things now with what we call the knowledge graph, which is relationships across types of data. You know, when I talk about the 27 OEMs, they don't all use the same term for something.  The guy in engineering who wrote the service manual called it some third thing. And so stitching all of those together into a seamless experience for our users, it's very challenging and very demanding. We invest a lot in that. How about predictive analytics? Anything on prescriptive and predictive analytics you guys working on? Like, you must see things early and have to blast out notifications. We are, we're trending in that direction. I don't want to give away too much by way of private knowledge. The analogy I used earlier today, I don't know if you know the car talk on NPR, and a guy called up in the middle of winter from Maine and he gets one of the guys and he describes, he goes, yeah, I'm driving a 2008 Ford F-150 and one of the brothers goes thermostat. And the guy says, well, I didn't tell you the problem. And he goes, all right, tell me the problem. The guy describes this problem and he goes thermostat. And it turns out that, you know, what happens is a technician will be on one or two automotive forms. Well, the car talk guys have all day to do that, right? So they're looking across 40 or 50 of them. And what they had seen was this trend in sub-zero temperatures for Ford F-150 thermostats to go bad. And so as soon as the guy said, Ford wouldn't have 50 thermostat. So we want to do that same thing, right? We're from Maine, it's called record winter, Ford 150 connect the dots. Exactly. So we want to do that for our customers and it's a ways off here but we're heading that direction. And I think we've got a good start and we, you know, certainly competitive advantage just having 300 million repair workers because you're not running down to 7-11 and buying those when you decide you want to do a big data project. So walk us through kind of how you came to work with our project and one of the things that I'm interested in and you talked about it briefly in our panel discussion but maybe you could expand a little bit on some of the challenges of adopting a new technology and a new mindset. Not necessarily a technology challenge but a mindset challenge, you know, kind of giving, putting that relational model aside and adopting kind of a new mindset in this new world of big data. Talk a little bit about that and how that happened at your organization. Yeah, the mindset can be very challenging. You know, as I related earlier, when I came from Snap on Diagnostics which is where I had been and the Snap on Culture was very much we cut metal with fire, right, right. And so I get transferred to Mitchell and I think, all right, fantastic. I'm going to the information group and I get to the information group and they put ink on paper. It was like, no, fellas, really, there's no more paper. And getting people's head around stop thinking about relational technology just think about the problem you want to solve. Focus on the problem. Let the technology help you.  Mark logic will help us with that. You know, it lets us connect all of the dots so you don't have to manually do that anymore and we're still driving that change through. The technology side of the business, everybody gets it. The rest of the business is coming around but it's an interesting cultural transformation. And does that require investment in training, you know, existing workers so that they can adopt this or is it more of an informal kind of thing where employees help each other?  A bit of both. We encourage everybody very actively to take training. The Mark logic folks have done a great job of making the training accessible, making it affordable. So there's a lot of that but there's also a lot of helping each other. Part of it, no small part of it is shedding old bad habits because people think relationally and I've been around sadly long enough to remember pre-relational database, I remember relational database was the big new thing and everybody became very invested in it and getting people to sort of look past that can be an interesting challenge. We're getting there though and it's a lot of just talking people along, helping them understand, you know, stuff. Don't worry about the how, worry about the what, you know, and in my team I'll worry about the how in the background. So I got to ask you, what's the coolest thing that you're working on right now that you could share? I mean, you're involved in a lot of cool tech. Actually got a platform behind it in Mark logic and other technology. What is the, what gets you excited right now? What are the coolest, what's the coolest thing that you're doing and working on? Well, we just introduced a feature in one of our products that will show you the relationship between a symptom, all the parts of the car that might cause that symptom, all of the diagnostics codes, you know, the check engine light comes on so there's codes in between and we're showing a graphic relationship so that a technician can, you know, if the code comes up and he'll click on the code and we'll say, well, okay, here's a list of symptoms that we know are associated with that code because we did the analytics on the 300 million repair orders. And then if they pick one of those symptoms we'll go, aha, you know, it's that part right there is where you should start.  That is probably the coolest thing we're doing and I think we're just scratching the surface really with analytics. So talk about the enablement that you get from the Markologic and the Internet these days because the data you just liberate and you get to do more things, you get some creative licenses, great for developers. What kind of hiring challenge is out there? Obviously we hear all the time, it's really, really hard to hire full stack developers. So what are you looking for in the technology and what has helped you guys if you can share your experiences and getting good people, keeping good people? Because sometimes if people walk out the door that's homegrown, you're holding a bag. Two things is we look for learners, right?  We insist you come to us with a willingness to learn. And then we try to keep the job interesting, keep the job fun, make sure that our developers are connected with their customer. I mean, one of the luxuries that we're afforded because there's aftermarket shops everywhere. And so all of our developers actually, I make sure that they get at least once a year and I try for twice to actually go out for a day and visit shops. We're a business that hires a lot of former technicians, a lot of guys that spent 10, 15, 20 years in shops. And so we'll send a developer out with them and they'll just go on shop visits and see how people are using the technology or using the application, you know. And we just ask them, what are you missing? What do you need? What are we not providing you that we could help you with? And that just keeps it interesting for everybody. Well, really appreciate you coming on theCUBE. Congratulations on being on the panel with Jeff Kelly, the people on Analyst, Big Data House, which his reports have been circulating around. He predicted this years ago, Jeff. Congratulations. Thank you so much. Great to have you on theCUBE. Thank you so much for coming on theCUBE. This is theCUBE, we'll be right back after this short break. To hear more from practitioners, industry leaders here on theCUBE in Silicon Valley from MarkLogic World 2015, we'll be right back.


From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. UI Path has had a long, strange trip to IPO. How so, you ask? Well, the company was started in 2005, but its culture is akin to a frenetic startup. The firm shunned conventions and instead of focusing on a narrow geographic area to prove its product market fit before it started to grow, it aggressively launched international operations prior to reaching unicorn status. Well prior, like when I had very little revenue around like a million dollars. Today, more than 60% of UI Path's business is outside of the United States, despite its headquarters being in New York City. There's more. According to recent SEC filings, UI Path's total revenue grew 81% last year, but its free cash flow is actually positive, modestly. Wait, there's more. The company raised $750 million in a series F in early February at a whopping $35 billion valuation. Yet, the implied back of napkin valuation based on the number of shares outstanding after the offering multiplied by the proposed maximum offering price per share yields a valuation of just under 26 billion. Okay. And there's even more to this crazy story. Hello everyone and welcome to this week's Wikibon Cube Insights powered by ETR. And this breaking analysis will share our learnings from sifting through hundreds of pages of UI Path's red herring. So you didn't have to. And we'll share our thoughts on its market, its competitive position and its outlook. Let's start with a question. Mark Roe Baers is a venture capitalist. He's a managing director at stage two capital and he's also a teacher, professor at the B school at Harvard. One of his favorite questions that he asks his students and others is what's the best way to grow a company? And he uses this chart to answer that question. On the vertical axis is customer retention and the horizontal axis is growth, growth rate. And you can see he's got modest and awesome and so forth. Now, so I'll let you look at it for a second. What's the best path to growth? Of course you want to be in that green circle. Awesome retention of more than 90% and awesome growth. But what's the best way to get there?  What do you think? What do you think most VCs would say? What would you say? I mean, wouldn't you want to maybe run the table, capture the flag before your competitors could get there or would you want to take a more conservative approach? What would Daniel Dinez say? The CEO of UiPath. Again, I'll let you think about that for a second. Let's talk about UiPath. What did they do? Well, I shared at the top that the company shunned conventions and expanded internationally very rapidly, well before it hit escape velocity and they grew like crazy and it got out of control and he had to rein it in, plug some holes. But the growth didn't stop, go, go, go. So very clearly based on its performance and reading through the S1, the company has great retention. It uses a metric called gross retention rate which is at like 96 or 97% very high. It says customers are sticking with it. So maybe that's the right formula. Go for growth and grow like crazy. Let chaos rain, then rain in the chaos as Andy Grove would say.  Let me tell you what I think Mark Robers would say. He told me you can do that, but churn is the silent killer of SaaS companies. And perhaps the better path is to nail product market fit and then your retention metrics before you go into hyperbolic growth mode. There's all science behind this, which may be antithetical to the way many investors want to roll the dice and go for super growth, like go fast or die. Well, it worked for UiPath, you might say, right? Well, no, this is where the story gets even more interesting and long and strange for UiPath. As we shared earlier, UiPath was founded in 2005 out of Bucharest, Romania. The company actually started as a software outsourcing startup. It called the company Desk Over and it built automation libraries and SDKs for companies like Microsoft, IBM and Google and others. It also built automation scripts and developed importantly, computer vision technology which became part of its secret sauce. In December, 2015, Desk Over changed its name to UiPath and became a Delaware Corp and moved its headquarters to New York City a couple of years later. So our belief is that UiPath actually took the preferred path of Mark Roberge, five ticks north, then five more east. They slow cooked for the better part of 10 years, trying to figure out what market to serve and they spent that decade figuring out their product market fit and then they threw gas in the fire. Pretty crazy. All right, let's take a peek at the takeaways from the UiPath S1. The numbers are impressive. 580 million ARR with 65% growth. That asterisk is there because like you, we thought ARR stood for annual recurring revenue. It really stands for annualized renewal run rate. Annualized renewal run rate is a metric that is one of UiPath's internal KPIs and will likely communicate that publicly over time. We'll explain that further in a moment. UiPath is a very solid customer base, nearly 8,000 interviewed many of them. They're extremely happy. They have very, very high retention. They get great penetration into the Fortune 500. Around 63% of the Fortune 500 has UiPath. Most of UiPath's business around 70% comes from existing customers, I would say. You're going to get more money out of existing customers than new customers, but everybody's trying to go out and get new customers. But UiPath I think is taking a really interesting approach. It's their land that expanded. I didn't invent that term, but I'll come back to that. It kind of reminds me of the early days of Tableau. Actually, I think Tableau is an interesting example. Like UiPath, Tableau started out as pretty much a point tool but it had very passionate customers. It was solving problems. It was simplifying things. And it would have bed into a company and grow and grow and grow. Now the market fundamentals for UiPath are very good. Automation is super hot right now and the pandemic has created an automation mandate date and I'll share some data there as well. UiPath is a leader. I'm going to show you the Gartner Magic Quadrant for RPA that's kind of a good little snapshot. UiPath pegs its TAM at $60 billion based on some bottoms up calculations and some data from Bain. Pre-pandemic we pegged it at over 30 billion and we felt that was conservative. Post-pandemic we think the TAM is definitely higher because of that automation mandate that's been accelerated. Now according to the S1, UiPath is going to raise around 1.2 billion and as we said that's an implied valuation that is lower than the Series F so we suspect the Series F investors have some kind of ratchet in there. UiPath needed the cash from its Series F investors so it took in 750 million in February and its balance sheet in the S1 shows about 474 million in cash and equivalent. So as I say it needed that cash. UiPath has had significant expense reductions that we'll show you in some detail. And it's brought in some fresh talent to provide some adult supervision. Around 70% of its executive leadership team and outside directors came to the company after 2019. In the company's S1 it disclosed that its independent accounting firm identified last year what it called a, quote, material weakness in our internal controls over financial reporting related to revenue recognition for the fiscal year ending 2018 caused by a lack of oversight and technical competence within the finance department, unquote. Now the company outlined the steps it took to remediate the problem, including hiring new talent. However, we said last year we felt UiPath wasn't quite ready to go public so it really had to get its act together. It was not as we said at the time the well-oiled machine that we said was Snowflake under Mike Scarpelli's firm operating guidance. You guys are operational guru but we suspect the company wants to take advantage of this market, it's a good time to go public. It needs the cash to bolster its balance sheet and the public offering is going to give it cachet in a stronger competitive posture relative to its main new competitor, newbie competitor, automation anywhere and the big whales like Microsoft and others that aspire in a watching what UiPath is doing and saying, hey, we want a piece of that action. Now one other note, UiPath CEO Daniel Danez owns 100% of the Class B shares of the company and has a 35 to one voting power. So he controls the company subject of course to his fiduciary responsibilities. But if UiPath, you know, let's say it gets in trouble financially he has more latitude to do secondary offerings at the same time is insulated from activist shareholders taking over his company. So lots of detail in the S1 and we just wanted to give you some of those highlights. Here are the pretty graphs. Whoever wrote this F1 was a genius. I mean, it's just beautiful. As we said, ARR annualized renewal run rate, just all it does is annualizes the invoice amount from subscriptions and the maintenance portion of the revenue. In other words, the parts that are recurring revenue, it excludes revenue from support and perpetual license like one time licenses and services. So it's just kind of the UiPath and maybe that's sort of a legacy there as future is that recurring revenue. So it's pretty similar to what we think of as ARR but it's not exact. Lots of customers with a growing number of six and seven figure accounts and a dollar based net retention of 145%. This figure represents the rate of net expansion of the UiPath ARR from existing customers over a 12 month period. Translation, this says UiPath's existing customers are spending more with the company to land and expand and we'll share some data from ETR on that. As you can see, the growth of 86% cagger over the past nine quarters, very, very impressive. Let's talk about some of the fundamentals of UiPath's business. Here's some data from the Brookings Institute and the OECD that shows productivity statistics for the US, the smaller charts in the writer for Germany and Japan. And I've shared some similar data before the US showed in the middle there showed productivity improvements with the personal productivity boom in the mid to late 90s and it spilled into the early 2000s. But since then you can see it's dropped off quite significantly. Germany and Japan are also under pressure as are most developed countries. China's labor productivity might show declines but it's level is at level significantly higher than these countries April 16th, the headline of the Wall Street Journal says that China's GDP grew 18% this quarter. So, we've talked about the snapback in post COVID in the post isolation economy but these are kind of one time bounces. But anyway, the point is we're reaching the limits of what humans can do alone to solve some of the world's most pressing challenges. And automation is one key to shifting labor away from these more mundane tasks toward more productive and more important activities that can deliver lasting benefits. This according to UiPath is its stated purpose to accelerate human achievement big. And the market is ready to be automated for the most part. Now, the post isolation economy is increasingly going to focus on automation to drive productivity as we've discussed extensively. I got to share the RPA magic quadrant where nearly everyone's a winner. Many people are of course happy. Many companies are happy just to get in to the magic quadrant. You can't just, you have to have certain criteria. So that's good. That's what I mean by everybody wins. We've reported extensively on UiPath and automation anywhere. We think we might shuffle the deck a little bit on this picture, maybe creating more separation between UiPath and automation anywhere and the rest. And from our vantage point, UiPath's IPO is going to either force automation anywhere to respond. And I don't know what its numbers are. I don't know if it's ready. I suspect it's not, we see that already. But I bet you it's trying to get there. Or if they don't, UiPath is going to extend its lead even further. That would be our prediction. But personally, I would have Pega systems higher on the vertical. Of course they're not an IPO, an RPA specialist. So I kind of get what Gartner's doing there. But I think they're executing well. And I'd probably, in a broader context, I'd probably maybe drop blue prism down a little bit even though last year was a pretty good year for the company. And I would definitely have Microsoft looming larger up in the upper left as a challenger more than a visionary, in my opinion. But look, Gartner does good work and its analysts are very deep into this stuff, deeper than I am. So I don't want to discount that. It's just how I see it. Let's bring in the ETR data and show some of the backup here. This is a candlestick chart that shows the components of net score, which is spending momentum. Remember, ETR goes out every quarter and says you're spending more, you're spending less, they subtract the lesses from the mores and that's net score. It's more complicated than that. But that's that blue line that you see in the top. And yes, it's trending downward, but it's still highly elevated. I'll talk about that. The market share is in the yellow line at the bottom there. And that green represents the percentage of customers that are spending more and the reds are spending less or replacing. That gray is flat. And again, even though UI pass net score is declining, it's that 61%. That's a very elevated score. Anything over 40% in our view is impressive. So UI pass has been holding in the 60s and 70% over the past several years. That's very, very good. Now that yellow line, market share, yes, it dips a bit, but again, it's nuanced. And this is because of Microsoft is so pervasive in the data set. It's got so many mentioned mentions that it tends to somewhat overwhelm and skew these curves. So let's break down net score a little bit. Here's another way to look at this data. This is a wheel chart. We show this often. It shows the components of net score. And what's happening here is the bright red is defections. So look at it. It's very, very small. That wouldn't be churn. It's tiny. Remember, churn is the killer for software companies. And so that forest green is existing customers spending more at 49%. That's big. That line green is new customers. So again, it's from the S1 70% of UI pass revenue comes from existing customers. And this really kind of underscores that. Now here's more evidence in the ETR data in terms of land and expand. This is a snapshot from the January survey and it lines up UI path next to its competitors and it cuts the data just on those companies that are increasing spending. And so that forest green that we saw earlier. So what we saw in Q1 was the pace of new customer acquisition for UI path was decelerating from previous highs. But UI path, it shows here is outpacing its competition in terms of increasing spend from existing customers. So we think that's really, really important. UI path gets very high scores in terms of customer satisfaction. I mean, I've talked to many in theCUBE. There's places on the web where we have customer ratings. And so you want to check that out, but it'll confirm that the churn is low, satisfaction is high. Yeah, they get dinged sometimes on pricing. They get dinged sometimes lately on service because they're growing so fast. So maybe they've taken the eye off the ball on a couple of accounts, but generally speaking, clients are leaning in, they're investing heavily. They're creating centers of excellence around RPA and automation and UI path is very focused on that. Again, land and expand. Now here's further evidence that UI path has a strong account presence, even in accounts where its competitors are present. In the 149 shared accounts from the Q1 survey where UI path, automation anywhere and Microsoft have a presence, UI pass net score or spending velocity is not only highly elevated, its relative momentum is accelerating compared to last year. Okay, so there's some really good news in the numbers, but some other things stood out in the S1 that are concerning or at least worth paying attention to. So we want to talk about that. Here's the income statement and look at the growth. The company was doing like a million dollars in 2015, like I said before, and when it started to expand internationally, it surpassed 600 million last year. It's insane growth. And look at the gross profit. Gross margin is almost 90% because revenue grew so rapidly. And last year its costs went down in some areas like services, less travel was part of that. Now jump down to the net loss line. And normally you would expect the company growing at this rate to show a loss. The street wants growth. And UI path is losing money, but its net loss went from 519 million, half a billion down to only 92 million. And that's because the operating expenses went way down. Now again, typically a company growing at this rate would show corresponding increases in sales and marketing expense, R and D and even G and A, but all three declined in the past 12 months. Now, reading the notes, there was definitely some meaningful savings from no travel and canceled events. UI path has great events around the world. In fact, the cube, knock wood is going to be at its event in October in Las Vegas at the Blasio. So we're stoked for that. But to draw expenses that precipitously with such high growth is kind of strange. Go look at Snowflake's income statement. They're in hyper growth as well. We like to compare it to Snowflake as a very well run company. And it's in hyper growth mode, but its sales and marketing and R and D and G and A, G and A expense lines, they're all growing along with that revenue. Now, perhaps they're growing at a slower rate. Perhaps the percent of revenue is declining as it should as they achieve operating leverage, but they're not shrinking in absolute dollar terms as shown in the UI path S1. So either UI path has applied some magic automation mojo to its business.  And maybe it has found the holy grail of operating leverage. I mean, it's a company that's all about automation or the company was running way too hot on the expense side and had to cut and clean up its income statement for the IPO and conserve some cash. Our guess is the latter, but maybe there's a combination there. We'll give them the benefit of the doubt and just to add a bit more to this long strange trip. When have you seen an explosive growth company just about to go public show positive cash flow? You know, maybe it's happened, but it's rare in the tech and software business these days. Again, go look at companies like Snowflake. They're not showing positive cash flow, not yet anyway. They're growing and trying to run the table. So you have to ask, why is UI path operating this way? And we think it's because they were running so hot and burning cash that they had to reel things in a little bit and get ready to IPO. It's going to be really interesting to see how this stock reacts when it does IPO. So here's some things that we want you to pay attention to. We have to ask, is this IPO is a window dressing or did UI path again uncover some new productivity and operating leverage model? I doubt there's anything radically new here. This company doesn't want to miss the window. So I think it said, okay, let's do this. Let's get ready for IPO. We got to cut expenses. We had a lot of good advisors. It surrounded itself with a new board, extended that board, new management and really want to take advantage of this because it needs the cash. In addition, it really does want to maintain its lead. It's got automation anywhere competing with it. It's got Microsoft looming large. And so it wants to continue to lead. It's made some really interesting acquisitions. It's got very strong vision as you saw in the Gartner Magic Quadrant and obviously it's executing well but it's really had to tighten things up. So we think it's used the IPO as a forcing function to really get its house in order. Now, will the automation mandate sustain? We think it will. The forced march to digital worked. It was effective. It wasn't pleasant, but even in a downturn, we think it will confer advantage to automation players and particularly companies like UiPath that have simplified automation in a big way and have done a great job of putting in training, great freemium model and has a culture that is really committed to the future of humankind. I mean, it sounds ambitious and crazy but talk to these people, you'll see it's true. Pricing, UiPath had to dramatically expand or did dramatically expand its portfolio and had to reprice everything. Now I'm not so worried about that. I think it'll figure that pricing out for that portfolio expansion. My bigger concern is for SaaS companies in general. I don't like SaaS pricing that has been popularized by Workday and ServiceNow and Salesforce and DocuSign and all these companies that essentially lock you in for a year or two and basically charge you upfront. It really is a one-way street. You can't dial down, you can only dial up. It's not true cloud pricing. You look at companies like Stripe and Datadog and Snowflake. It is true cloud pricing. It's consumption pricing. I think the traditional SaaS pricing model is flawed and it's very unfairly weighted toward the vendors and I think it's going to change. Now, the reason we put cloud on the chart is because we think cloud pricing is the right way to price. Let people dial up and dial down. Let them cancel anytime and compete on the basis of your product excellence. And yeah, give them a price concession if they do lock in. But the starting point we think should be that flexibility, pay by the drink, cancel anytime. I mentioned some companies that are doing that as well. If you look at the modern SaaS startups and the forward-thinking VCs, they're really pushing their startups to this model. So we think over time that the term lock-in model is going to give way to true consumption-based pricing and at the client's option allow them to lock in for a better price, way better model. And UiPASS cloud revenue today is minimal but over time we think it's going to continue to grow that cloud and we think it'll force a rethink in pricing and in revenue recognition. So watch for that. How is the street going to react to Daniel Dinez having basically full control of the company? Generally, we feel that solid execution, if UiPASS can execute, is going to outweigh those concerns. In fact, I'm very confident that it will. We'll see. Kind of like when a CEO has enough mojo to say, you know what? I'm not going to let what happened to, for instance, EMC happened to me. You saw Michael Dell do that. You saw just this week, they're spinning out VMware. He's maintaining his control. VMware Dell shareholders get 40.44 shares for every Dell share they're holding and who's the biggest shareholder? Michael Dell. So he's, you got two companies, one chairman. He's controlling the table. Michael Dell beat the great icon. Who beats Carl Icon? Well, Michael Dell beats Carl Icon. So Daniel Dinez has looked at that and says, you know what? I'm not just going to give up my company. And the reason I like that with an if, is that that we think will allow the company to focus more on the longterm. The if is it's got to execute. Otherwise it gets so much pressure and look, the bottom line is that UiPath has really favorable market momentum and fundamentals, but it is signing up for the 90 day shot clock. The fact that the CEO has control again, means they can look more longterm and invest accordingly. Oftentimes that's easier said than done. It does come down to execution. So it's going to be fun to watch. Okay. That's it for now. Thanks to the community for your, your comments and insights and really always appreciate your feedback. Remember I publish each week on wikibon.com and siliconango.com. And these episodes are all available as podcasts. All you can do is search for the breaking analysis podcast. You can always connect with me on Twitter at dvolante or email me at david.volante at siliconango.com or comment on my LinkedIn posts. And we'll see you in clubhouse. Follow me and get notified when we start a room which we've been doing with John Furrier and Sargeecho Hall and others. And we love to riff on these topics. And don't forget, please check out ETR.plus for all the survey action. This is Dave Vellante for theCUBE Insights powered by ETR. Be well everybody and we'll see you next time.