The State of Enterprise Software by Jerry Chen | Greyscale

Launching a startup isn't easy. At each stage of scaling, from founding to product market fit, from product market fit to hypergrowth, and from hypergrowth to maturity, entrepreneurs face unique challenges. Greylock Partners hosted an event called Grayscale focused on these challenges at each stage. In the opening keynote, Jerry Chen of Greylock Partners gives an overview of enterprise Software after the first quarter of 2016. He sums up the private and public markets M and A activity and explains how this climate affects the startup environment. For more podcasts, please visit news.greylock.com I'm Jerry Chen.

Welcome to Grayscale. You know, there's not the first idea for the name of this. Grayscale is my first choice. Originally I said 50 shades of greylock, but I thought we run to trademark issues and so they denied 50 Shades of Greylock and and we're calling it Grayscale. And so I want to say, what do we mean by Grayscale? And like what's the theme of today? And thank you very much for coming. So do we mean 50 shades of gray, dark gray, light gray, Very, very, very light gray? Or if you actually Google grayscale, Obviously for the Game of Thrones fans, this is grayscale. But what we mean by grayscale is today's theme is around enterprise companies scaling and growing, both from a product perspective, a go to market perspective, and a culture and team building perspective. And when my partners and I sat down, we thought about doing an event for kind of enterprise founders, enterprise entrepreneurs. We thought that instead of doing a topical event around big data security, AI and you know, things like that, we want to focus on what it means to build and scale a company from start to IPO or beyond. And it speaks volumes to kind of my experience both as an investor and as an operator. My background, those who don't know me, I see a bunch of familiar faces. I started, I think, as Matt Eccleston's intern at VMware, when there's a couple hundred employees and we're there to over 15,000 employees to 5 billion in revenue. And so we were able to see that company scale from very, very small to very, very small deals to very large deals. And so when we think about Grayscale, we kind of break the phases of the life cycle into three areas. The first we think is from founding to product market fit. So when our company is just starting, maybe it's like a founder, two founders, it's PowerPoint, it's just a dream, it's a baby little dragon thinking about taking over the world. But how do you go from the very, very start to understanding product market fit, to understand there's a market out there, there's demand for your product, you, and making sure I have the right solution to fit the right demand. And I always say early in this life cycle, you have to make sure you're in the top tier, top three priorities of your customer. Because the cio, the cfo, the CEO, they only have budget for three or four things. So it doesn't matter if you're number nine, number eight on their wish list. If you're not top three, you're not gonna find that product market fit. So let's say you find this early product market fit. The next phase, obviously, as you're growing, is from product market fit to, to hypergrowth, hyperscale. And this means that you found something, a use case is repeatable, you found a buyer that economically makes sense, that's buying your product. But now you're at a race. How do you bring your product to your customers through the channel, at speed, at scale, that's also going to be profitable. That while you're competing against other startups who are competing in the same space or incumbents in the same space. So really it's a race between your Dragon and the rest of the market. And finally, at hypergrowth to maturity, so all of a sudden you kind of went through this revenue acceleration. When do you launch a second product? When you launch a third product? How do you think about international expansion? How do you think about M and A? How do you upgrade your executive team, your VP of sales, your VP of products, or VP of marketing? How do you think about combining forces with other larger companies out there to actually have a lasting, enduring company that goes multiple generations? So those are the three phases. Founding to product market fit, product market fit to hyperscale, and hyperscale to maturity. And so the theme of today, we're going to have a bunch of speakers, a bunch of conversations that will hopefully be useful to each of your journeys along that path. So first, founding product market fit. This can be anywhere from 0 to 10 million revenue, 1 to 100 employees. Sometimes it's smaller, sometimes it's bigger. Depends upon the vertical, depends upon the market you're in. Second, again, product market fit to hybrid growth. Tend to call it 100 million revenue. So you're seeing this acceleration very quickly, maybe up to 100 or 1,000 employees. And finally, hybrid growth and maturity. But before we go into the details of the day and kind of the mechanics of how do you scale your company, I want to take a pause and kind of say, you know, what's going on in the market in 2016. So first, you know, as they would say, follow the money. So we look at this is the Bessemer Cloud index. We look at the past four or five years of, you know, top SaaS and cloud companies and look at their valuations charted. We obviously hit a peak in 2015. And then in Q1 of 2016, as you guys know, we had a severe dip, a severe correction in a bunch of the SaaS and cloud companies. But in kind of the end of Q1 and Q2, the valuations have come back actually. So actually we've hit this kind of new normal in early Q2. It's not going to return to the levels of 2015 and 2016, but nor are we in the kind of the same the deep trough we saw in Q1 of 2016. So just a few months ago. So if you look at valuations and that's kind of a short term look, this is the Morgan stanley index of SaaS companies and software companies over 15 years from January 1998 to February 2016. So if you see that big spike in the far left, that was kind of the dot com bubble where multiples include measured by enterprise value to next year's revenue were astronomic, right? We're talking 25, 30x next year's revenue. And don't even get started on income because there was no earnings. So after kind of the dot com crash, we went for many years where we had kind of anywhere from 7 to 10x multiples of next year's revenue. And then from 2010 to 2014, you saw this kind of run up in valuations where we actually had the peak. We saw on average companies were being valued 15 to 16 times next year's revenue. And again, what happened in Q1 in early Q2 of 2016 is that number has gone down by roughly half. So from a 15x multiple of next year's revenue to roughly 78x multiple next year's revenue. And you can talk about why. It could be public markets, it could be maturing industries, could be investor sentiment, but it's actually looking more like historical normals in the 2002-2010 timeframe than it is in the two abnormal areas in the dot com peaks in the most recent bubble. So that's in the public market. So the next thing I want to do is show you kind of even a shorter snapshot of what's happened in recent IPOs and the performance of the past year. So we have Pure Storage, Atlassian, New Relic Box and Hortonworks. So each of the recent tech IPOs there have been a bunch. They've all been either below their initial offering price. So pure is actually 10% below the IPO. Atlassian is roughly 15 to 20%. And both those companies actually fairly large, growing momentum and have kind of a path towards profitability. The ones towards the bottom box and Hornet Works obviously went down quite dramatically in early 2016, but are coming back as well in 2016. But that said, the market's not rewarding growth at all costs. So if you're a high burn rate company in the public market burning a lot of cash to get revenue, the the public market no longer has that kind of appetite to reward that P and L, they're really looking for a four to six quarter path towards cash flow. Break even for the public market now to be enthusiastic about your offering. So we take that data around public markets. So A valuations are half what they were kind of, you know, 30, 90 days ago. B IPO returns are down below initial price off rate. How has that translated the past 15 years to the VC investment? So once again, this is the same Morgan Stanley data now with or Morgan stanley timeframe from 1998, 1999 through 2016. So that's Q1 2016 at the far right. And once again you see during the dot com days around 99, 2000, you know, $7 billion plus of VC investments per quarter. Again that dropped dramatically towards 2002, 2004. In the past two, three years it's run up quite dramatically until Q1. It's actually come down pretty dramatically last quarter and this quarter. Now we zoom in in just the most recent quarters. This is from PitchBook's data of both total value of all the deals done in early stage venture by quarter, as well as number of deals done in early stage venture by quarter. And so if you look at this number, we hit, you know, 750, 740 deals in Q1 Q2 2015. And not only are we down dramatically year over year, but also dramatically down quarter over quarter in terms of number of deals done. So the number of actual early stage VC deals being done by the industry is down year over year and quarter after quarter. But interesting enough, the total dollars invested in Q1 in 2016 is slightly up both year over year and quarter over quarter, which means that the round size is going up. So there's still an appetite to do deals in the early stage. But now investors are looking to invest More in good companies and quite frankly own a larger percentage of deals. So that's the early stage market for those in the audience are thinking about series A, Series B. If you're kind of post that, you're looking at late stage VC and the numbers are similar. If you look year over year from Q1 2016 to Q1 2015, we're also down in terms of number of deals from 462 to 388 as well as deal sizes. The total dollars invested was $12 billion in Q1 2015 to about $9.4 billion in Q1 2016. So again you see the public markets coming down both in valuations as well as stock prices. And then that kind of translates a little bit towards the private markets. So let's look Also the other exits besides the public market is Strategic M and A. So this chart's kind of hard to read or hard to grok, but if you look at 2004 through 2009, the number of tech companies went public that were acquired. So that kind of cohort of kind of the mid-2000s, half of the companies that went public during that time frame had been acquired have gone some other outcome. But you look at the 2010-2014 companies, very little had been bought. Right. Which reflects that Strategic M and A from large corporates have been sitting on the sideline for a couple reasons. One, prices were very high and two, there wasn't a lot of appetite for companies to sell at the time. So my expectation is you're going to see a lot of corporate M and A pick up back half of 2016, 2017. Because you know, if you're, if you're a data person, you believe returns, the median returns, the mean that numbers of 20%, 19%, 28% should look more like 40 to 50% if we look back this chart in two or three years. So if you think about the money for the past two, three years, my summary is the following. Look public markets valuations are down 15x multiples at the peak in 2015, looking at 7x multiples now in 2016. But that said, we're stabilizing. So I think we're seeing a new normal. A lot of investors were worried in Q1 in 2016 because they thought you, you know, stock price is going down, how low can this go? Prices have come back up. I think we're seeing a new normal, a new stable level of valuations in stock prices. So I think people feeling good about the market number two. So that's translating towards VC deal volume, I think it's decreasing year over year. Right. It's hard to keep up the pace we saw in 2014, 2015, but there's still an appetite for great companies. That's indicated by the number of deals, but more important the round size of the deals being done. So fewer deals being done, but larger check sizes. And finally, I think M and A from large strategics will pick up over the next two or three years. It's natural. We've talked to a bunch of corporate VPs in biz dev and corp dev of the large companies and they're sniffing around. They're talking to a bunch of VCs, they're talking to a bunch of startups. I think you're going to see a bunch of incumbents buy companies for the next two, three years. So now we have kind of that place setting the context. It's not all doom and gloom, right? And people are kind of looking at me. But it's also not everything's up in the right. I think we're looking at a new reality. So if we think about that, what are the three things that when I talk to my portfolio companies and talk to entrepreneurs that come by Greylock, you know, a focus on our cash position. So if you raise money, you're raising money now. A think about your burn rate. Think about the cash you have today because you don't know how long it will be until the market returns or how hard or how easy it will be to raise your next round. Number two, building for the long haul. Because there's no historic M and A that's at a reasonable or high valuation. Build your companies to last. Right? Make sure that you have a business model A go to market a customer segment that's growing. And third, I always say this. Pick a wave bigger than you. When you're a founder or a CEO, you want to ride a wave bigger than you, bigger than your competitors. So if you're, you know, I always say you're trying to fight Facebook and your photo sharing app like Instagram, you ride the mobile first wave, you're trying to fight Oracle and databases near your Cloudera or hardware works, you ride a big data wave, you're trying to find VMware in the infrastructure space, your Docker, you ride a container wave. So ride a wave bigger than you because at the end of the day, these macro trends will a float your valuation and float the amount of interest in you as a company or you as a startup. So if we think about what waves are out there, what Waves are going to gain ride. I thought I would pick out three or four different focus markets, three or four different themes that I think about as an investor in Greylock. And again, there's no magic answers. The next three or four slides, they're more ideas and questions I'm going to throw out to you guys, either to discuss during the day or during the breaks. For the first space I spent a lot of time is data center and cloud infrastructure, background of VMware and Cloud Foundry, and the board member of Docker and cloudera. I think a lot about infrastructure, but my overall investment theme right now in infrastructure is you're caught between OSS and a cloud place, a rock and a hard place. On one hand you have open source, that is a powerful tool for marketing, for trial, for distribution. But for a whole category of customers, monetizing pure open source is very, very difficult because especially around Soma, no one's going to be paying for your software. On the other hand, I call it the cloud place, where if you have an open source project in storage, security, in management, if you're at scale, all of a sudden, Amazon, Google, Microsoft say hey, thank you very much, let me go run Elastic as a service, I'll run Hadoop as a service, I'll run Containers as a service. So you're kind of caught between open source and a cloud place, rocking a hard place. So when you start a company in this space, be thoughtful about how you can navigate these two spaces. And so when you think about navigating these spaces, there's kind of four things in infrastructure I think about. Number one is Amazon Amazon Web Services. AWS is probably emerging as the biggest threat to infrastructure companies today. And there's folks like Datadog that build their companies around on Amazon. So think about how it can make Amazon not just a competitor, but as a channel, as an ally, as a partner. And later on this afternoon, Mike Clayville, who's the VP of sales for all of Amazon's cloud, will be on stage with me. We'll talk about two things. One, scaling, growing a go to market and sales team, and two, we'll talk a little about Amazon and how Amazon wants to work for the startup ecosystem. But the scary thing about Amazon is because the power default is so easy. They have the credit cards, they have the developers, they have the apps, they have the users. It's really easy for them to sell an additional service to their customers. And so you have to think about how to dislodge that. Number two, it's not just all Amazon So I think Microsoft Azure, what they're now calling the Microsoft cloud, and Google's going to make Google progress in 2016. I think they're distant, number two, number three from Amazon, but we're seeing a lot of enterprise buyers from the Fortune 500, Fortune 1000 talk a lot more about Azure than they did a year or two ago. Number three, this goes to the strategic M and a point I just made. Incumbent vendors will behave irrationally. So they might do things like Dell buying EMC because they're consolidating a market. They're going to basically pull up the stakes, circle the wagons and try to defend their installed base. So they're going to do some things like buy companies, but expect them to do irrational things too, cut price, be very aggressive in their competitive policies. And the fourth thing, especially around infrastructure, I have this theme, I call it ddi, developer defined infrastructure, where you actually have to own the developer. The best way to kind of circumvent or fight Amazon as a competitor is to actually have a direct relationship with the developers, a large footprint. So your Docker, your Hadoop, your, you're ending this great open source projects, you actually have a relationship directly with the developer, with the end user that can kind of circumvent kind of Amazon, Azure and Google and create more power to your franchise. So those are three or four things around infrastructure. I think about second space we spend a lot of time is security and I would say separating signal from the noise. Security is an evergreen hot market because there's always going to be bad guys and there's always going to be good guys that need tools to fight the bad guys. So the good news is there's always going to be a market for security. The bad news is there's always going to be new security companies out there that you have to compete against. Right? So what I mean by that is there are thousands of security companies out there. If you went to RSA this year, there's 40,000 attendees, which is up from like 25 or 30,000 a year beforehand. So a bunch of these security companies all sound the same and quite frankly many are the same. But many of the same. They mean they're attacking the same problem, they're offering the same value. So. So it's really hard to discern if you're a buyer, the signal from the noise. Why should I buy Michael's product versus Varun's or something like that? So customers don't want to buy snake oil because oftentimes with security you're selling fear Right. Like, hey, if you don't buy this, you're going to get hacked from North Korea. If you don't buy this product, insider threat's going to take you down. So part of the first job of being a security entrepreneur is how to make your buyers smarter. So before you even teach them about your product, your value add, teach your audience, teach your buyers how to be a smart buyer, how to be a discerning buyer on a security product, security category. And if you kind of change the game on how you think about go to market around security, around marketing security, I think you can actually have a more clever go to market. I think Michael, who's in the audience, we talked about this in the past, that about 10 years ago, security used to be run like the volunteer fire department, right? There's a fire, a bunch of people came, try to put it out, there's a security breach, a bunch of people came from networking, storage, whatever, to put it out. But now it's actually professional area. So think about how to build a security company that is not a flash in the pan. Okay, the next category I want to talk about is apps. And I can jokingly say this is not your father's Oldsmobile. Then I thought maybe folks in the audience don't remember that commercial theme. So, okay, what I mean by that is apparently apps have an evolution. Went from client server, went to cloud and SaaS. Went from cloud and SaaS to cloud mobile. So what comes next, right? What's beyond mobile? Is it like computer chips in my brain? Is it iot? What does it mean? And what I mean is there are new fundamental primitives of how you build your apps. So we talk about bots and conversational UIs IoT. So extend the reach of your application everywhere to your car, to your phone, to your glasses. And the big data and AI will power these apps. So I think about apps, are we going to see a new CRM or a new category applications like erp, hr? And my answer right now is no, we're not going to see a new app category. But these three primitives will think how you rewrite and rebuild your application category using bots, IoT and AI. And so let's take an example, and this is one that Satya from Microsoft talks about. Let's say you crash a car. If you're Atom, you got rear ended recently 1. So today you crash a car, that's a bad thing. But, but in the future, your cloud enabled Tesla or IoT car will sense when you had a crash, automatically notify Both the paramedics or the fire department in the garage, or quite frankly, your insurance company. Your insurance company would then text you to your smartphone via like a bot or SMS, hey, XYZ is done with the car because it's wired via IoT, we actually know what's wrong with it. And Quite frankly, with GPS, they'll call LyftCar or Uber to come pick you up. Right? So you're not rewriting a customer service app, but your insurance company can extend their reach not only from the phone or mobile phone app, directly to your car. So if your Atom got rendered recently, you get an Uber to pick you up on the street. Again, not your father's Oldsmobile. So the final theme is these apps are being powered by data and IoT. And I kind of lump these things together because IoT just generates a bunch of more data. And my theme here is machine intelligence and other oxymorons, which basically means what does machine intelligence mean? I mean, AI and big data are more marketing terms than anything else. And when I segment this thing, it's like, okay, are we going to have a self driving intelligent car or are we going to have something in between? And one of the things that I think John Lilly and I talk about is are you building Iron man or Terminator, right? Are you building a suit of armor powered by big data, powered by AI to make you better? So you're going to build a security product to make you better? Are you going to build a DevOps product to monitoring or deployment that'll make your IT and Ops feel better are to you going or are you building Terminator? Right. I think Google, their last event talked about how Google Cloud will eliminate ops, become no ops. And that could be threatening, that could be long term end state. But I think in the short term, these AI bots, these AI powered applications are really building things to make your customers better. Right? Think about that. So finally, when we think about AI and big data, there's some things that are real. Vision, speech and text are all real for app deployments. And then on the data side, it's more data trumps better math. And what I mean by that is algorithms are one thing, but if you're going to beat the incumbents, be it a Facebook or Google or a Baiju or a Yahoo, your main advantage isn't better math or better algorithms, is how can you find a source of data, proprietary source of data, or a different set of data that you can apply big data, machine learning on top of and then generate better results if you're just using a common training set of data, you're going to be no better than Google or Facebook. So finally, what I want to do now is kind of talk about the rest of the day. We have a bunch of great speakers and actually you guys are part of it because we're going to have questions after all the speakers. We have roundtables today and then plenty of breaks. So coming up, my partners John Lilly and Reid Hoffman with Chris Yeh will talk about Blitzscaling. So John, Chris and Reid and Alan taught this class at Stanford this past year, last year, this past fall, it's called CS 183 at Stanford called Blitzscaling, where they talked about scaling through these three stages and they'll talk about their version of this framework. But I think John obviously was a founder himself of reactivity, ran Mozilla during this hypergrowth phase. Reid Hoffman obviously started companies twice. Both built PayPal and LinkedIn from founding through hybrid growth, maturity and the Chris. I'll tease out from them their learnings across these three stages later on today, my partner Dan Bertillo and Jeff Markowicz will talk about hiring. So Dan focuses on core talent. Engineers, product designers and people always ask, how do you find good talent? How do you know when you're not hiring correctly? So Dan will talk about how he thinks about debugging your recruiting process. Jeff will talk about executive hiring boards, VPs, how to really augment your team. After that, I'm going to talk about unit of value, a go to market framework that I've talked a lot about and how to think it through. And then we'll have Mike Clayville, who's the VP of sales for all Amazon's cloud on stage, talk about his go to market and his experience scaling sales teams. This afternoon we'll have a CIO panel for the CIOs of Clorox and Workday, as well as a bunch of other CIOs in the audience at these tables for you to meet with and have a conversation with. And then over dinner, Anil Bushri, my partner and CEO and co founder of Workday, he and I will talk about his experience scaling Workday from literally him and Dave Duffield at a diner outside Tahoe where they came up the idea for Workday to billion dollar revenue 15 billion market cap company. So with that, you know, we're going to start with the first panel, which is going to be not necessarily life or death, but please welcome Chris, John and Re.