Kellblog covers topics related to starting, managing, leading, and scaling enterprise software startups. My favorite topics include strategy, marketing, sales, SaaS metrics, and management. I also provide commentary on Silicon Valley, venture capital, and the business of software.
Harry’s interview was broad-ranging, covering a number of topics including:
Financing lessons I’ve learned during prior bubble periods and, perhaps more importantly, bubble bursts.
The three basic types of exits available today: strategic acquirer, old-school private equity (PE) squeeze play, and new-school PE growth and/or platform play.
A process view of exiting a company via a PE-led sales process, including discussion of the confidential information memorandum (CIM), indications of interest (IOIs), management meetings, overlaying strategic acquirers into the process, and the somewhat non-obvious final selection criteria.
The Soundcloud version, available via any browser is here. The iTunes version is here. Regardless of whether you are interested in the topics featured in this episode, I highly recommend Harry’s podcast and listen to it myself during my walking and/or driving time.
How would you like your startup to win deals not only when you win a customer evaluation, but when you tie — and even sometimes when you lose?
That sounds great. But is it even possible? Amazingly, yes — but you need have a halo effect working to your advantage. What is a halo effect? Per Wikipedia,
The halo effect is a cognitive bias in which an observer’s overall impression of a person, company, brand, or product influences the observer’s feelings and thoughts about that entity’s character or properties
There’s a great, must-read book (The Halo Effect) on the how this and eight other related effects apply in business. The book is primarily about how the business community makes incorrect attributions about “best practices” in culture, leadership, values, and process that are subsequent to — but were not necessarily drivers of — past performance.
I know two great soundbites that summarize the phenomenon of pseudo-science in business:
“All great companies have buildings.” Which comes from the (partly discredited) Good To Great that begins with the observation that in their study cohort of top-performing companies that all of them had buildings — and thus that simply looking for commonalities among top-performing companies was not enough; you’d have to look for distinguishing factors between top and average performers.
“If Marc Benioff carried a rabbit’s foot, would you?” Which comes from a this Kellblog post where I make the point that blindly copying the habits of successful people will not replicate their outcome and, with a little help from Theodore Levitt, that while successful practitioners are intimately familiar with their own beliefs and behaviors, that they are almost definitionally ignorant of which ones helped, hindered, or were irrelevant to their own success.
Now that’s all good stuff and if you stop reading right here, you’ll hopefully avoid falling for pseudo-science in business. That’s important. But it misses an even bigger point.
Has your company ever won (or lost) a deal because of:
Analyst placement on a quadrant or other market map?
Perceived market leadership?
Word of mouth as the “everyone’s using it” or “next thing” choice?
Vibe at your events or online?
A certain feeling or je ne sais quoi that you were more (or less) preferred?
If yes, you’re seeing halo effects at work.
Halo effects are real. Halo effects are human nature. Halo effects are cognitive biases that tip the scales in your favor. So the smart entrepreneur should be thinking: how do I get one for my company? (And the smart customer, how can I avoid being over-influenced by them? See bottom of post.)
In Silicon Valley, a number of factors drive the creation of halo effects around a company. Some of these are more controllable than others. But overall, you should be thinking about how you can best combine these factors into an advantage.
Lineage, typically in the form of previous success at a hot company (e.g., Reid Hoffman of PayPal into LinkedIn, Dave Duffield of PeopleSoft into Workday). The implication here (and a key part of halo effects) is that past success will lead to future success, as it sometimes does. This one’s hard to control, but ceteris paribus, co-founding (even somewhat ex post facto) a company with an established entrepreneur will definitely help in many ways, including halo effects.
Investors, in one of many forms: (1) VC’s with a strong brand name (e.g., Andreessen Horowitz), (2) specific well known venture capitalists (e.g., Doug Leone), (3) well known individual investors (e.g., Peter Thiel), and to a somewhat lesser extent (4) visible and/or famous angels (e.g., Ashton Kutcher). The implication here is obvious, that the investor’s past success is an indication of your future success. There’s no doubt that strong investors help build halo effects indirectly through reputation; in cases they can do so directly as well via staff marketing partners designed to promote portfolio companies.
Investment. In recent years, simply raising a huge amount of money has been enough to build a significant halo effect around a company, the implication being that “if they can raise that much money, then there’s got to be a pony in there somewhere.” Think Domo’s $690M or Palantir’s $2.1B. The media loves these “go big or go home” stories and both media and customers seem to overlook the increased risk associated with staggering burn rates, the waste that having too much capital can lead to, the possibility that the investors represent “dumb money,” and the simple fact that “at scale” these businesses are supposed to be profitable. Nevertheless, if you have the stomach, the story, and the connections to raise a dumbfounding amount of capital, it can definitely build a halo around your company. For now, at least.
Valuation. Even as the age of the unicorn starts to wane, it’s undeniable that in recent years, valuation has been a key tool to generate halos around a company. In days of yore, valuation was a private matter, but as companies discovered they could generate hype around valuation, they started to disclose it, and thus the unicorn phenomenon was born. As unicorn status became increasingly de rigeur, things got upside-down and companies started trading bad terms (e.g., multiple liquidation preferences, redemption rights) in order to get $1B+ (unicorn) post-money valuations. That multiplying the price of a preferred share with superior rights by a share count that includes the number of lesser preferred and common shares is a fallacious way to arrive at a company valuation didn’t matter. While I think valuation as a hype driver may lose some luster as many unicorns are revealed as horses in party hats (e.g., down-round IPOs), it can still be a useful tool. Just be careful about what you trade to get it. Don’t sell $100M worth of preferred with a ratcheted 2 moving to 3x liquidation preference — but what if someone would buy just $5M worth on those terms. Yes, that’s a total hack, but so is the whole idea of multiplying a preferred share price times the number of common shares. And it’s far less harmful to the company and the common stock. Find your own middle ground / peace on this issue.
Growth and vision. You’d think that industry watchers would look at a strategy and independently evaluate its merits in terms of driving future growth. But that’s not how it works. A key part of halo effects is misattribution of practices and performance. So if you’ve performed poorly and have an awesome strategy, it will overlooked — and conversely. Sadly, go-forward strategy is almost always viewed through the lens of past performance, even if that performance were driven by a different strategy or affected positively or negatively by execution issues unrelated to strategy. A great story isn’t enough if you want to generate a vision halo effect. You’re going to need to talk about growth numbers to prove it. (That this leads to a pattern of private companies reporting inflated or misleading numbers is sadly no surprise.) But don’t show up expecting to wow folks with vision. Ultimately, you’ll need to wow them with growth — which then provokes interest in vision.
Network. Some companies do a nice and often quiet job of cultivating friends of the company who are thought leaders in their areas. Many do this through inviting specific people to invest as angels. Some do this simply through communications. For example, one day I received an email update from Vik Singh clearly written for friends of Infer. I wasn’t sure how I got on the list, but found the company interesting and over time I got to know Vik (who is quite impressive) and ended up, well, a friend of Infer. Some do this through advisory boards, both formal and informal. For example, I did a little bit of advising for Tableau early on and later discovered a number of folks in my network who’d done the same thing. The company benefitted by getting broad input on various topics and each of us felt like we were friends of Tableau. While sort of thing doesn’t generate the same mainstream media buzz as a $1B valuation, it is a smart influencer strategy that can generate fans and buzz among the cognoscenti who, in theory at least, are opinion leaders in their chosen areas.
Before finishing the first part of this post, I need to provide a warning that halo effects are both powerful and addictive. I seem to have a knack for competing against companies pursuing halo-driven strategies and the pattern I see typically runs like this.
Company starts getting some hype off good results.
Company starts saying increasingly aggressive things to build off the hype.
Analysts and press reward the hype with strong quadrant placements and great stories and blogs.
Company puts itself under increasing pressure to produce numbers that support the hype.
And then one of three things happens:
The company continues delivering strong results and all is good, though the rhetoric and vision gets more unrelated to the business with each cycle.
The company stops delivering results and is downgraded from hot-list to shit-list in the minds of the industry.
The company cuts the cord with reality and starts inflating results in order to sustain the hype cycle and avoid outcome #2 above. The vision inflates as aggressively as the numbers.
I have repeatedly had to compete against companies where claims/results were inflated to “prove” the value of bad/ordinary strategies to impress industry analysts to get strong quadrant positions to support broader claims of vision and leadership to drive more sales to inflate to even greater claimed results. Surprisingly, I think this is usually done more in the name of ego than financial gain, but either way the story ends the same way — in terminations, lawsuits and, in one case, a jail sentence for the CEO.
Look, there are valid halo-driven strategies out there and I encourage you to try and use them to your company’s advantage — just be very careful you don’t end up addicted to halo heroin. If you find yourself wanting to do almost anything to sustain the hype bubble, then you’ll know you’re addicted and headed for trouble.
The Customer View
Thus far, I’ve written this post entirely from the vendor viewpoint, but wanted to conclude by switching sides and offering customers some advice on how to think about halo effects in choosing vendors. Customers should:
Be aware of halo effects. The first step in dealing with any problem is understanding it exists. While supposedly technical, rational, and left-brained, technology can be as arbitrary as apparel when it comes to fashion. If you’re evaluating vendors with halos, realize that they exist for a reason and then go understand why. Are those drivers relevant — e.g., buying HR from Dave Duffield seems a reasonable idea. Or are they spurious — e.g., does it really matter that one board member invested in Facebook? Or are they actually negative — e.g., if the company has raised $300M how crazy is their burn rate, what risk does that put on the business, and how focused will they stay on you as a customer and your problem as a market?
Stay focused on your problem. I encourage anyone buying technology to write down their business problems and high-level technology requirements before reaching out to vendors. Hyped vendors are skilled at “changing the playing field” and trained to turn their vision into your (new) requirements. While there certainly are cases where vendors can point out valid new requirements, you should periodically step back and do a sanity check: are you still focused on your problem or have you been incrementally moved to a different, or greatly expanded one. Vision is nice, but you won’t be around solve tomorrow’s problems if you can’t solve today’s.
Understand that industry analysts are often followers, not leaders. If a vendor is showing you analyst support for their strategy, you need to figure out if the analyst is endorsing the strategy because of the strategy’s merits or because of the vendor’s claimed prior performance. The latter is the definition of a halo effect and in a world full of private startups where high-quality analysts are in short supply, it’s easy to find “research” that effectively says nothing more than “this vendor is a leader because they say they’re performing really well and/or they’ve raised a lot of money.” That doesn’t tell you anything you didn’t know already and isn’t actually an independent source of information. They are often simply amplifiers of the hype you’re already hearing.
Enjoy the sizzle; buy the steak. Hype king Domo paid Alec Baldwin to make some (pretty pathetic) would-be viral videos and had Billy Beane, Flo Rida, Ludacris, and Marshawn Lynch at their user conference. As I often say, behind any “marketing genius” is an enormous marketing budget, and that’s all you’re seeing — venture capital being directly converted into hype. Heck, let them buy you a ticket to the show and have a great time. Just don’t buy the software because of it — or because of the ability to invest more money in hand-grooming a handful of big-name references. Look to meet customers like you, who have spent what you want to spend, and see if they’re happy and successful. Don’t get handled into meeting other customers only at pre-arranged meetings. Walk the floor and talk to regular people. Find out how many are there for the show, or because they’re actual successful users of the software.
Dive into detail on the proposed solution. Hyped vendors will often try to gloss over solutions and sell you the hype (e.g., “of course we can solve your problem, we’ve got the most logos, Gartner says we’re the leader, there’s an app for that.”) What you need is a vendor who will listen to your problem, discuss it with you intelligently, and provide realistic estimates on what it takes to solve it. The more willing they are to do that, the better off you are. The more they keep talking about the founder’s escape from communism, the pedigree of their investors, their recent press coverage, or the amount of capital they’ve raised, the more likely you are to end up high and dry. People interested in solving your problem will want to talk about your problem.
Beware the second-worst outcome: the backwater. Because hyped vendors are actually serving Sand Hill Road and/or Wall Street more than their customers, they pitch broad visions and huge markets in order to sustain the halo. For a customer, that can be disastrous because the vendor may view the customer’s problems as simply another lily pad to jump off on the path to success. The second-worst outcome is when you buy a solution and then vendor takes your money and invests it in solving other problems. As a customer, you don’t want to marry your vendor’s fling. You want to marry their core. For startups, the pattern is typically over-expansion into too many things, getting in trouble, and then retracting hard back into the core, abandoning customers of the new, broader initiatives. The second-worst outcome is when you get this alignment wrong and end up in a backwater or formerly-strategic area of your supplier’s strategy.
Avoid the worst outcome: no there there. Once in awhile, there is no “there there” behind some very hyped companies despite great individual investors, great VCs, strategic alliances, and a previously experienced team. Perhaps the technology vision doesn’t pan out, or the company switches strategies (“pivots”) too often. Perhaps the company just got too focused on its hype and not on it customers. But the worst outcome, while somewhat rare, is when a company doesn’t solve its advertised problem. They may have a great story, a sexy demo, and some smart people — but what they lack is a core of satisfied customers solving the problem the company talks about. In EPM, with due respect and in my humble opinion, Tidemark fell into this category, prior to what it called a “growth investment” and what sure seemed to me like a (fire) sale, to Marlin Equity Partners. Customers need to watch out for these no-there-there situations and the best way to do that is taking strong dose of caveat emptor with a nose for “if it sounds too good to be true, then it might well possibly be.”
The great reckoning begins. Correct/nailed. As predicted, since most of the bubble was tied up in private companies owned by private funds, the unwind would happen in slow motion. But it’s happening.
Silicon Valley cools off a bit. Partial. While IPOs were down, you couldn’t see the cooling in anecdotal data, like my favorite metric, traffic on highway101.
Porter’s five forces analysis makes a comeback. Partial. So-called “momentum investing” did cool off, implying more rational situation analysis, but you didn’t hear people talking about Porter per se.
Cyber-cash makes a rise. Correct. Bitcoin more doubled on the year (and Ethereum was up 8x) which perversely reinforced my view that these crypto-currencies are too volatile — people want the anonymity of cash without a highly variable exchange rate. The underlying technology for Bitcoin, blockchain, took off big time.
SAP realizes they are a complex enterprise application company. Incorrect. They’re still “running simple” and talking too much about enabling technology. The stock was up 9% on the year in line with revenues up around 8% thus far.
Oracle’s cloud strategy gets revealed – “we’ll sell you any deployment model you want as long as your annual bill goes up.” Partial. I should have said “we’ll sell you any deployment model you want as long as we can call it cloud to Wall St.”
Accounting irregularities discovered at one or more unicorns. Correct/nailed. During these bubbles the pattern always repeats itself – some people always start breaking the rules in order to stand out, get famous, or get rich. Fortune just ran an amazing story that talks about the “fake it till you make it” culture of some diseased startups.
Startup workers get disappointed on exits. Partial. I’m not aware of any lawsuits here but workers at many high flyers have been disappointed and there is a new awareness that the “unicorn party” may be a good thing for founders and VCs, but maybe not such a good thing for rank-and-file employees (and executive management).
The first cloud EPM S-1 gets filed. Incorrect. Not yet, at least. While it’s always possible someone did the private filing process with the SEC, I’m guessing that didn’t happen either.
2016 will be a great year for Host Analytics. Correct. We had a strong finish to the year and emerged stronger than we started with over 600 great customers, great partners, and a great team.
Now, let’s move on to my predictions for 2017 which – as a sign of the times – will include more macro and political content than usual.
Social media companies finally step up and do something about fake news. While per a former Facebook designer, “it turns out that bullshit is highly engaging,” these sites will need to do something to filter, rate, or classify fake news (let alone stopping to recommend it). Otherwise they will both lose credibility and readership – as well as fail to act in a responsible way commensurate with their information dissemination power.
Gut feel makes a comeback. After a decade of Google-inspired heavily data-driven and A/B-tested management, the new US administration will increasingly be less data-driven and more gut-feel-driven in making decisions. Riding against both common sense and the big data / analytics / data science trends, people will be increasingly skeptical of purely data-driven decisions and anti-data people will publicize data-driven failures to popularize their arguments. This “war on data” will build during the year, fueled by Trump, and some of it will spill over into business. Morale in the Intelligence Community will plummet.
Under a volatile leader, who seems to exhibit all nine of the symptoms of narcissistic personality disorder, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media. Whether you like his policies or not, Trump will bring a high level of volatility the country, to business, and to the markets.
With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. Providing such a stimulus to already strong economy might well overheat it. One smart move could be buying a house to lock in historic low interest rates for the next 30 years. (See my FAQ for disclaimers, including that I am not a financial advisor.)
Huge emphasis on security and privacy. Election-related hacking, including the spearfishing attack on John Podesta’s email, will serve as a major wake-up call to both government and the private sector to get their security act together. Leaks will fuel major concerns about privacy. Two-factor authentication using verification codes (e.g., Google Authenticator) will continue to take off as will encrypted communications. Fear of leaks will also change how people use email and other written electronic communications; more people will follow the sage advice in this quip:
Dance like no one’s watching; E-mail like it will be read in a deposition
In 2015, if you were flirting on Ashley Madison you were more likely talking to a fembot than a person. In 2016, the same could be said of troll bots. Bots are now capable of passing the Turing Test. In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media). Left unchecked by the social media powerhouses, bots could damage social media usage.
Artificial intelligence hits the peak of inflated expectations. If you view Salesforce as the bellwether for hyped enterprise technology (e.g., cloud, social), then the next few years are going to be dominated by artificial intelligence. I’ve always believed that advanced analytics is not a standalone category, but instead fodder that vendors will build into smart applications. They key is typically not the technology, but the problem to which to apply it. As Infer founder Vik Singh said of Jim Gray, “he was really good at finding great problems,” the key is figuring out the best problems to solve with a given technology or modeling engine. Application by application we will see people searching for the best problems to solve using AI technology.
Megavendors mix up EPM and ERP or BI. Workday, which has had a confused history when it comes to planning, acquired struggling big data analytics vendor Platfora in July 2016, and seems to have combined analytics and EPM/planning into a single unit. This is a mistake for several reasons: (1) EPM and BI are sold to different buyers with different value propositions, (2) EPM is an applications sale, BI is a platform sale, and (3) Platfora’s technology stack, while appropriate for big data applications is not ideal for EPM/planning (ask Tidemark). Combining the two together puts planning at risk. Oracle combined their EPM and ERP go-to-market organizations and lost focus on EPM as a result. While they will argue that they now have more EPM feet on the street, those feet know much less about EPM, leaving them exposed to specialist vendors who maintain a focus on EPM. ERP is sold to the backward-looking part of finance; EPM is sold to the forward-looking part. EPM is about 1/10th the market size of ERP. ERP and EPM have different buyers and use different technologies. In combining them, expect EPM to lose out.
And, as usual, I must add the bonus prediction that 2017 proves to be a strong year for Host Analytics. We are entering the year with positive momentum, the category is strong, cloud adoption in finance continues to increase, and the megavendors generally lack sufficient focus on the category. We continue to be the most customer-focused vendor in EPM, our new Modeling product gained strong momentum in 2016, and our strategy has worked very well for both our company and the customers who have chosen to put their faith in us.
I thank our customers, our partners, and our team and wish everyone a great 2017.
Calling Palantir a $20B company suggests they are doing $20B in revenues, which is certainly not the case. (They say they did $1B in 2015 and that’s bookings, not revenue.) So we’re not talking a small difference here. Depending on the hype factor surrounding a company, we might be talking 20x.
Domo is another company the media loves to size by its market cap.
I’ve heard revenue estimates of $50M to $100M for Domo, so here again, we’re not talking about a small difference. Maybe 20x.
I love Max. I love MongoDB. While I don’t know what their revenues were when he left (I’d guess $50M to $100M), they certainly were not a “billion-dollar database company.” But, hey, the article got 4,000 shares. Inflation-wise, I’m again guessing 10-20x.
So why does the media do this? Why do they want to mislead readers by a factor of 20?
Because if makes the numbers bigger
And makes the headlines cooler
And increases drama
In the end, because it (metaphorically) sells more newspapers. “Wow, some guy just quit as CEO of a billion-dollar company to actually spend more time with his family” just sounds a whole lot better than the same line with a comparatively paltry $50M instead. Man Bites Dog beats Dog Bites Man every time.
But it’s wrong, and the media should stop doing it. Why?
It’s misleading, and not just a little. Up to 20x as the above examples demonstrate.
It’s not verifiable. For private companies, you can’t really know or verify the valuation. It’s not in any public filing. (While private companies don’t disclose revenue either, it’s much more easily triangulated.)
Private company valuations are misleading because VCs buy preferred stock and employees/founders have common stock. So you take a preferred share price and multiply it by the total number of outstanding shares, both preferred and common. (This ignores the fact that the common is definitionally worth less than the preferred and basically assumes an IPO scenario, which happens only for the fortunate few, where the preferred converts into common.)
In the past few years, companies are increasingly taking late-stage money that often comes with “structure” that makes it non-comparable in rights to both the regular preferred and the common. So just compound the prior problem with a new class of essentially super-preferred stock. The valuation gets even more misleading.
Finally, compound the prior problem with a hyped environment where everyone wants to be a unicorn so they might deliberately take unfavorable terms/structure in order get a higher valuation and hopefully cross into unicorn-dom. The valuation gets even-more-misleading squared. See the following Tweet as my favorite example of this phenom. (OH means overheard.)
When was the last time I saw the media consistently size companies by valuation instead of revenue? 1997 to 2001. Bubble 1.0.
Maybe we’ll soon be talking about eyeballs again. Or, if you like Stance, the company that has raised $116in VC and has “ignited a movement of art and self-expression,” in socks (yes, socks) then maybe we’ll be talking about feet.
While I credited Domo with creating a huge hype bubble through secrecy and mystery, big events, and raising tremendous amounts of money (yet again today) at unicorn valuations — I also questioned how much (as Gertrude Stein said of Oakland) “there there” Domo has when it comes to the company and its products.
Specifically, I began to wonder how to quantify the hype around a company. Let’s say that, as organisms, SaaS companies convert venture capital into two things: annual recurring revenue (ARR) and hype. ARR has direct value as every year it turns into GAAP revenue. Hype has value to the extent it creates halo effects that drive interest in the company that ultimately increase ARR. 
Hype Factor = Capital Raised / Annual Recurring Revenue
Now, unlike some bloggers, I don’t have any freshly minted MBAs doing my legwork, so I’m going to need to do some very back of the envelop analysis here.
Looking at some recent JMP research, I can see that the average SaaS company goes public at around $25M/quarter in revenue, a $100M annual run-rate, and which also suggests an ARR base of around $100M.
Looking at this post by Tomasz Tunguz, I can see that the average SaaS company has raised about $100M if you include everyone or $68M if you exclude companies that I don’t really consider enterprise software.
So, back of the envelope, this suggests that 1.5 (=100/68) is a typical capital-to-ARR ratio on the eve of an IPO. Let’s look at some specific companies for more (all figures are approx as I’m eye-balling off charts in some cases and looking at S-1s in others) :
NetSuite: raised $125M, run-rate at IPO $92M –> 1.3
Cornerstone: raised $41M, run-rate $44M –> 1.0
Box: raised $430M, run-rate $228M –> 1.8
Xactly: raised $83M, run-rate $50M –> 1.7
Workday: raised $200M, run-rate $168M –> 1.2
There are numerous limitations to this analysis.
I do not make any effort to take into account either how much VC was left over on the eve of the IPO or how much debt the company had raised.
Capital consumption per category may vary as a function of the category as a CFO friend of mine reminded me today.
Some companies don’t break out subscription and services revenue and the ARR run-rate calculations should only apply to subscription.
Since private companies raise capital and burn it down until an IPO, you should expect that the above values represent minima from a lifecycle perspective. (In theory, you’d arrive on IPO day broke, having raised no more cash than you needed to get there.)
So I’m going to rather subjectively assign some buckets based on this data and my own estimates about earlier stages.
A hype factor of 1-2 is target
A hype factor of 2-3 is good, particularly well before an IPO
A hype factor of 3-5 is not good, too much hype and too little ARR
A hype factor of 5+ suggests there is very little “there there” at all.
I know of at least one analytics company where I suspect the hype factor is around 10. If I had to take a swag at Domo’s hype factor based on the comments in this interview:
Quote from the article: “contracted revenue is $100M.” Hopefully this means ARR and not TCV.
Capital raised: $613M per Crunchbase, including today’s round.
This suggests Domo’s hype factor is 6.1 including today’s capital and 4.8 excluding it. So if you’ve heard of Domo, think they are cool, are wowed by the speakers and rappers at Domopalooza, you should be. As I like to say: behind every marketing genius, there is usually a massive budget. 
Domo’s spending heavily, that’s for sure. How efficient they are at converting that spending to ARR remains to be seen. My instinct, and this rough math, says they are more efficient at generating hype than revenue. 
Time will tell. Gosh, life was simpler (if less interesting) when companies went public at $30M.
# # #
 In a sense, I’m arguing that hype takes two forms: good hype that drives ARR and wasted hype that simply makes the company, like the Kardashians, famous for being famous.
 And having some trouble making the different data sources foot. For example, the SFSF S-1 indicates $45M in convertible preferred stock, but the Tunguz post suggests $70M. Where’s my freshly minted MBA to help?
 You can argue that the first step in marketing genius is committing to spend large amounts of money and I won’t debate you. But I do think many people completely overlook the massive spend behind many marketing geniuses and, from a hype factor perspective, forget that the purpose of all that genius is not to impress TechCrunch and turn B2B brands into household words, but to win customers and drive ARR.
 Note that Domo says they have $200M in the bank unspent which, if true, both skews this analysis and prompts the question: why raise more money at a flat valuation in smaller quantity when you don’t need it? While my formula deliberately does not take cash or debt into account (because it’s hard enough to just triangulate on ARR at private companies), if you want to factor that claim into the math, I think you’d end up with a hype factor of 3-4. (You can’t exclude all the cash because every startup keeps cash on hand to fund them through to their next round.)
There are two sayings I like when it comes to the unicorn bubble:
“Too much money makes you stupid”
“Any idea’s a good one when you’ve got $100M burning a hole in your pocket.”
Startups are supposed to be focused. Startups are supposed to need to prioritize ideas and opportunities. Just as startups weren’t supposed to buy Superbowl ads, startups aren’t supposed to have hundreds of millions of dollars to plow through in the name of creating brand mystique either via huge-budget events like Domo’sDomopalooza or would-be viral videos, like the one below.
But wait, you protest, didn’t Salesforce always do aggressive marketing and wasn’t that risk-taking part of their greatness? Well, yes and no. A good part of their early marketing was guerrilla PR done on the cheap. Yes, they also ran big events, but they mostly found a way to pay for them — Salesforce raised $53M in VC before going public. Domo has raised nearly 10x that.
Now, I have no particular beef with Domo. Other than being next-generation BI, I must admit to always having had some trouble figuring out what they do — in part due to the abnormal secrecy they had in their early days. I know they don’t compete with Host Analytics so I have no beef there. I also know they have sexed-up the BI category a bit, and they’ve certainly done a great job of positioning themselves as a cool company and have created a lot of buzz in the market.
But at what cost?
Domo has raised $483M. It does cause one to wonder about their capital-to-ARR ratio, which is a great overall capital efficiency metric and one that no ever seems to talk about.
While I don’t know in Domo’s case, I’d guess for many unicorns that this ratio is 10 to 20x — where the company is running a kind of perpetual motion machine strategy where you generate the Halo Effects hoping to drive the sales that justify the valuation that you got on your last financing. This strategy, as many will discover, works well until it doesn’t. If the epitaph of Bubble 1.0 was about Network Effects, that of Bubble 2.0 will be about Halo Effects. Remember Warren Buffet’s famous quote: “only when the tide goes out can you see who’s swimming naked.”
I know for a reasonably capital-efficient SaaS business the capital-to-ARR ratio might be 2-3x. Perhaps an order of magnitude difference.
Back to our core topic — what’s an example of something that looks like a good idea when you have $483M burning a hole in your pocket that, well, might not look like such a good idea if you were forced to lead a more frugal marketing existence?
How about a YouTube mini-series with Alec Baldwin? That’s exactly what Domo did.
As the new year approaches, it’s time for another set of predictions, but before diving into my list for 2016, let’s review and assess the predictions I made for 2015.
Kellblog’s 2015 Predictions Review
The good times will continue to roll in Silicon Valley. I asserted that even if you felt a bubble, that it was more 1999 than 2001. While IPOs slowed on the year, private financing remained strong — traffic is up, rents are up and unemployment is down. Correct.
The IPO as down-round continues. Correct.
The curse of the mega-round strikes many companies and CEOs. While I can definitely name some companies where this has occurred, I can think of many more where I still think it’s coming but yet to happen. Partial / too early.
Cloud disruption continues. From startups to megavendors, the cloud and big data are almost all everyone talks about these days. Correct.
Privacy becomes a huge issue. While I think privacy continues to move to center stage, it hasn’t become as big as I thought it would, yet. Partial / too early.
Next-generation apps like Slack and Zenefits continue to explode. I’d say that despite some unicorn distortion that this call was right (and we’re happy to have signed on Slack as a Host Analytics customer in 2015 to boot). Correct.
IBM software rebounds. At the time I made this prediction IBM was in the middle of a large reorganization and I was speculating (and kinda hoping) that the result would be a more dynamic IBM software business. That was not to be. Incorrect.
The data scientist shortage continues. This one’s pretty easy. Correct.
The unification of planning becomes the top meme in EPM. This was a correct call and supported, in part, through our own launch of Modeling Cloud, a cloud-based, multi-dimensional modeling engine that helps tie enterprise models both to each other and the corporate plan. Correct.
So, let’s it call it 7.5 out of 10. Not bad, when you recall my favorite quote from Yogi Berra: “predictions are hard, especially about the future.”
Kellblog’s Top Predictions for 2016
Before diving into these predictions, please see the footnote for a reminder of the spirit in which they are offered.
1. The great reckoning begins. I view this as more good than bad because it will bring a return to commonsense business practices and values. The irrationality that came will bubble 2.0 will disperse. It took 7 years to get into this situation so expect it to take a few years to get out. Moreover, since most of the bubble is in illiquid securities held by illiquid partnerships, there’s not going to be any flash crash — it’s all going to proceed in slow motion, expect for those companies addicted to huge burn rates that will need to shape up quickly. Quality, well run businesses will continue attract funding and capital will be available for them. Overall, while there will be some turbulence, I think this will be more good than bad.
2. Silicon Valley cools off a bit. As a result of the previous prediction, Silicon Valley will calm a bit in 2016: it will get a bit easier to hire, traffic will modestly improve, and average burn rates will drop. You’ll see fewer corporate buses on 101. Rents will come down a bit, so I’d wait before signing a five-year lease on your next building.
3. Porter’s Five Forces comes back in style. I always feel that during bubbles the first thing to go is Porter five force analysis. What are there barriers to entry on a daily deal or on a check-in feature? What are the switching costs of going from Feedly to Flipboard? What are the substitutes for home-delivered meal service? In saner times, people take a hard look at these questions and don’t simply assume that every market is a greenfield market share grab and that market share itself constitutes a switching cost (as it does only in companies with real network effects).
4. Cyber-cash makes a rise. As the world becomes increasingly cashless (e.g., Sweden), governments will prosper as law enforcement and taxation bodies benefit, but citizens will increasingly start to sometimes want the anonymity of cash. (Recall with irony that anonymity helped make pornography the first “killer app” of the Internet. I suspect today’s closet porn fans would prefer the anonymity of cash in a bookshop to the permanent history they’d leave behind on Netflix or other sites — and this is not to mention the blackmailing that followed the data release in the Ashley Madison hack.) For these reasons and others, I think people will increasingly realize that in a world where everything is tracked by default, that the anonymity of some form of cyber-cash will sometimes be desired. Bitcoin currently fails the grade because people don’t want a floating (highly volatile) currency; they simply want an anonymous, digital form of cash.
5. The Internet of Things (IoT) starts its descent into what Gartner calls the Trough of Disillusionment. This is not to say that IoT is a bad thing in any way — it will transform many industries including agriculture, manufacturing, energy, healthcare, and transportation. It is simply to say that Silicon Valley follows a predictable hype cycle and that IoT hit the peak in 2015 and will move from the over-hyped yet very real phase and slide down to the trough of disillusionment. Drones are following along right behind.
6. Data science continues to rise as a profession. 23 schools now offer a master’s program in data science. As a hot new field, a formal degree won’t be required as long as you have the requisite chops, so many people will enter data science they way I entered computer science — with skills, but not a formal degree. See this post about a UC Berkeley data science drop-out who describes why he dropped the program and how he’s acquiring requisite knowledge through alternative means, including the Khan Academy. Galvanize (which acquired data-science bootcamp provider Zipfian Academy) has now graduated over 200 students. Apologies for covering this trend literally every year, but I continue to believe that “data science” is the new “plastics” for those who recall the scene from The Graduate.
7. SAP realizes it’s an complex, enterprise applications company. Over the past half decade, SAP has put a lot of energy into what I consider strategic distractions, like (1) entering the DBMS market via the Sybase acquisition, (2) putting a huge emphasis on their column-oriented, in-memory database, Hana, (3) running a product branding strategy that conflates Hana with cloud, and (4) running a corporate branding strategy that attempts to synonymize SAP with simple.
Some of these initiatives are interesting and featured advanced technology (e.g., Hana). Some of them are confusing (e.g., having Hana mean in-memory, column-oriented database and cloud platform at the same time). Some of them are downright silly. SAP. Simple. Really?
While I admire SAP for their execution commitment — SAP is clearly a company that knows how to put wood behind an arrow — I think their choice of strategies has been weak, in cases backwards looking (e.g., Hana as opposed to just using a NoSQL store), and out of touch with the reality of their products and their customers.
The world’s leader in enterprise software applications that deal with immense complexity should focus on building upon that strength. SAP’s customers bought enterprise applications to handle very complex problems. SAP should embrace this. The message should be: We Master the Complex, not Run Simple. I believe SAP will wake up to this in 2016.
Aside: see the Oracle ad below for the backfire potential inherent in messaging too far afield from your reality.
8. Oracle’s cloud strategy gets revealed: we’ll sell you any deployment model you like (regardless of whether we have it) as long as your yearly bill goes up. I saw a cartoon recently circulated on Twitter which depicted the org charts of various tech megavendors and, quite tellingly, depicted Oracle’s as this:
Oracle is increasingly becoming a compliance company more than anything else. What’s more, despite their size and power, Oracle is not doing particularly well financially. Per a 12/17/15 research note from JMP,
Oracle has missed revenue estimates for four quarters in a row.
Oracle provided weak, below-expectations guidance on its most recent earnings call for EPS, cloud revenue, and total revenue.
“While the bull case is that the cloud business is accelerating dramatically, we remain concerned because the cloud represented only 7% of total revenue in F2Q16 and we worry the core database
and middleware business (which represents about half of Oracle’s revenue) will face increasing competition from Amazon Web Services.”
While Oracle’s cloud marketing has been strong, the reality is that cloud represents only 7% of Oracle’s total revenue and that is after Oracle has presumably done everything they can to “juice” it, for example, by bundling cloud into deals where, I’ve heard, customers don’t even necessarily know they’ve purchased it.
So while Oracle does a good job of bluffing cloud, the reality is that Oracle is very much trapped in the Innovator’s Dilemma, addicted to a huge stream of maintenance revenue which they are afraid to cannibalize, and denying customers one of the key benefits of cloud computing: lower total cost of ownership. That’s not to mention they are stuck with a bad hardware business (which again missed revenues) and are under attack by cloud application and platform vendors, new competitors like Amazon, and at their very core by next-generation NoSQL database systems. It almost makes you feel bad for Larry Ellison. Almost.
8. Accounting irregularities are discovered at one or more unicorns. In 2015 many people started to think of late-stage megarounds as “private IPOs.” In one sense that was the correct: the size of the rounds and the valuations were very much in line with previous IPO norms. However, there was one big difference: they were like private IPOs — but without all the scrutiny. Put differently, they were like an IPO, but without a few million dollars in extra accounting work and without more people pouring over the numbers. Bill Gurley did a great post on this: Investors Beware: Today’s $100M+ Late-Stage Private Rounds are Very Different from an IPO. I believe this lack of scrutiny, combined with some people’s hubris and an overall frothy environment, will lead to the discovery of one or more major accounting irregularity episodes at unicorn companies in 2016. Turns out the world was better off with a lower IPO bar after all.
9. Startup workers get disappointed on exits, resulting in lawsuits. Many startup employees work long hours predicated on making big money from a possible downstream IPO. This has been the model in Silicon Valley for a long time: give up the paycheck and the perks of a big company in exchange for sleeves-up work and a chance to make big money on stock options at a startup. However, two things have changed: (1) dilution has increased because companies are raising more capital than ever and (2) “vanity rounds” are being done that maximize valuation at the expense of terms that are bad for the common shareholder (e.g., ratchets, multiple liquidation preferences).
In extreme cases this can wipe out the value of the common stock. In other cases it can turn “house money” into “car money” upon what appears to be a successful exit. Bloomberg recently covered this in a story called Big IPO, Tiny Payout about Box and the New York Times in a story about Good Technology’s sale to BlackBerry, where the preferred stock ended up 7x more valuable than the common. When such large disparities occur between the common and the preferred, lawsuits are a likely result.
Many employees will find themselves wondering why they celebrated those unicorn rounds in the first place.
10. The first cloud EPM S-1 gets filed. I won’t say here who I think will file first, why they might do so, and what the pros and cons of filing first may be, but I will predict that in 2016 the first S-1 gets filed for a cloud EPM vendor. I have always believed that cloud EPM is a great category and one that will result in multiple IPOs — so I don’t believe the first filing will be the last. It will be fun to watch this trend and get a look at real numbers, as opposed to some of the hype that gets circulated.
11. Bonus: 2016 proves to be a great year for Host Analytics. Finally, I feel great about the future for Host Analytics and believe that 2016 will be a wonderful year for the company. We have strong products. We have amazing customers. We have built the best team in EPM. We have built a strong partner network. We have great core applications and exciting, powerful new capabilities in modeling. I believe we have, overall, the best, most complete offering in cloud EPM.
Thanks for your support in 2015 and I look forward to delivering a great 2016 for our customers, our partners, our investors, and our team.
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 These predictions are offered in the spirit of fun and I have no liability to anyone acting or not acting on the content herein. I am not an oracle, soothsayer, or prophet and make no claim to be. Please enjoy these predictions, please let them provoke your thoughts, but do not use them as investing or business consulting advice. See my FAQ for additional disclaimers.
I’m Dave Kellogg, consultant, independent director, advisor, and blogger focused on enterprise software startups.
I bring a unique perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud enterprise performance management vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of Service Cloud at Salesforce and CEO at NoSQL database provider MarkLogic, which we grew from zero to $80M in run-rate revenues during my tenure. Before that, I was CMO at Business Objects for nearly a decade as we grew from $30M to over $1B. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Cyral, FloQast, GainSight, Kelda, MongoDB, Plannuh, Recorded Future, and Tableau. I currently sit on the boards of Alation (data catalogs), Nuxeo (content management) and Profisee (master data management). I previously sat on the boards of agtech leader Granular (acquired by DuPont for $300M) and big data leader Aster Data (acquired by Teradata for $325M).
I periodically speak to strategy and entrepreneurship classes at the Haas School of Business (UC Berkeley) and Hautes Études Commerciales de Paris (HEC).