Category Archives: Bubble

Kellblog’s 2017 Predictions  

New Year’s means three things in my world:  (1) time to thank our customers and team at Host Analytics for another great year, (2) time to finish up all the 2017 planning items and approvals that we need to get done before the sales kickoff (including the one most important thing to do before kickoff), and time to make some predictions for the coming year.

Before looking at 2017, let’s see how I did with my 2016 predictions.

2016 Predictions Review

  1. 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.
  2. 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.
  3. 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.
  4. Cyber-cash makes a rise. CorrectBitcoin 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.
  5. Internet of Things goes into trough of disillusionment. Partial.  I think I may have been a little early on this one.  Seems like it’s still hovering at the peak of inflated expectations.
  6. Data science rises as profession. Correct/easy.  This continues inexorably.
  7. 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.
  8. 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.”
  9. 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.
  10. 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).
  11. 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.
  12. 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.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s. Social media echo chambers will reinforce divisions.  To combat this, I encourage everyone to sign up for two publications/blogs they agree with and two they don’t lest they never again hear both sides of an issue. (See map below, coutesy of Ninja Economics, for help in choosing.)  On an optimistic note, per UCSD professor Lane Kenworthy people aren’t getting more polarized, political parties are.

news

  1. 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.
  1. 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.
  1. 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.
  1. 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.)
  1. 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

  1. 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.
  1. 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.
  1. The IPO market comes back. After a year in which we saw only 13 VC-backed technology IPOs, I believe the window will open and 2017 will be a strong year for technology IPOs.  The usual big-name suspects include firms like Snap, Uber, AirBnB, and SpotifyCB Insights has identified 369 companies as strong 2017 IPO prospects.
  1. 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.

# # #

 

Can the Media Please Stop Referring to Company Size by Valuation?

The following tweet is the umpteenth time I’ve seen the media size a company by valuation, not revenue, in the past few years:

mktcap

Call me old school, but I was taught to size companies by revenue, not market capitalization (aka, valuation).

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.

domo

I’ve heard revenue estimates of $50M to $100M for Domo, so here again, we’re not talking about a small difference.  Maybe 20x.

When my friend Max Schireson stepped down from MongoDB to spend more time with his family, the media did it again (see the first line of text below the picture)

mongodb

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.)

ego

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.

# # #

(And while I’m not sure about the $116M, I do love the socks.)

 

Introducing a New SaaS Metric: The Hype Factor

I said in yesterday’s post, entitled Too Much Money Makes You Stupid, that while I don’t have much of a beef with Domo, that I did want to observe in today’s fund-to-excess environment that any idea — including making a series of Alec Baldwin would-be viral videos — can sound like a good one.

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. [1]

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) [2]:

  • 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. [3]

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. [4]

Time will tell.  Gosh, life was simpler (if less interesting) when companies went public at $30M.

# # #

Notes

[1] 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 Kardashiansfamous for being famous.

[2] 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?

[3] 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.

[4] 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.)

Too Much Money Makes You Stupid — Let’s Make an Alec Baldwin Viral Video

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’s Domopalooza 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.

Here’s episode 1 about “rancid data” which, among several issues, breaks the fundamental rules about how to make a successful viral video.

Kellblog Predictions for 2016

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

  1. 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.
  2. The IPO as down-round continues.  Correct.
  3. 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.
  4. Cloud disruption continues.  From startups to megavendors, the cloud and big data are almost all everyone talks about these days.  Correct.
  5. 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.
  6. 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.
  7. 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.
  8. Angel investing slows.  I couldn’t find any hard figures here, but did find a great article on why Tucker Max quit angel investing.  I’m going to give myself a partial here because I believe the bloom is coming off the angel investing rose.  Partial.
  9. The data scientist shortage continues. This one’s pretty easy.   Correct.
  10. 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).

porters-five-forces

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.

the-graduate-plastics
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.
SAP_logo

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.

 

powered by oracle

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-org-chart-300x195

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.

good

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.

# # #

Footnotes

[1]  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.

The Great Reckoning: Thoughts on the Deflation of Technology Bubble 2.0

This post shares a collection of thoughts on what I’ve variously heard referred to as “the tightening,” “the unwinding,” “the unraveling,” or “the great reckoning” — the already-in-process but largely still-coming deflation of technology-oriented stock valuations, particularly in consumer-oriented companies and particularly in those that took large, late-stage private financings.

The Four Horsemen

Here are four key signs that trouble has already arrived:

  • The IPO as last resort.  Box is the best example of this, and while I can’t find any articles, I have heard numerous stories of companies deciding to go public because they are unable to raise high-valuation, late-stage private money.
  • The markdowns.  Fortune ran a series of articles on Fidelity and other mutual funds marking down companies like Snapchat (25%), Zenefits (48%), MongoDB (54%), or Dataminr (35%).  A unique feature of Bubble 2.0 is publicly-traded mutual funds investing in private, VC-backed companies resulting in some CEOs feeling, “it’s like we went public without even knowing it.”
  • The denial.  No bubble would be complete without strong community leaders arguing there is no bubble.  Marc Andreessen seems to have taken point in this regard, and has argued repeatedly that we’re not in a technology bubble and his firm has built a great data-rich deck to support that argument.

The Unicorn Phenom

If those aren’t sufficient signs of bubbledom, consider that mainstream media like Vanity Fair were writing about unicorns  and describing San Francisco as the “city by the froth” back in September.

It’s hard to talk about Bubble 2.0 without mentioning the public fascination with unicorns — private tech companies with valuations at $1B+.  The Google search “technology unicorn” returns 1.6M hits, complete with two unicorn trackers, one from Fortune and the other from CBInsights.  The inherent oxymoron that unicorns were so named because they were supposed to be exceptionally rare can only be lost in Silicon Valley.  (“Look, there’s something rare but we’re so special, we’ve got 130 of them.”)  My favorite post on the unicorn phenom comes from Mark Suster and is entitled:  Why I Effing Hate Unicorns and the Culture They Breed.

As the bubble has started to deflate, we now hear terms like formercorns, onceacorns, unicorpses, or just plain old ponies (with birthday hats on) to describe the downfallen.  Rumors of Gilt Groupe, once valued at $1.1B, possibly selling to The Hudson’s Bay Company for $250M stokes the fire.

What Lies Ahead?

While this time it’s different is often said and rarely true, I do believe we are in case when the unwinding will happen differently for two reasons:  (1) the bubble is in illiquid assets (private company preferred shares) that don’t trade freely on any market and (2) the owners of these illiquid shares are themselves illiquid, typically structured as ten-year limited partnerships like most hedge, private equity growth/equity, or venture capital funds.

All this illiquidity suggests not a bubble bursting overnight but a steady deflation when it comes to asset prices.  As one Wall Street analyst friend put it, “if it took 7 years to get into this situation, expect it to take at least 3.5 years to get out.”

Within companies, particularly those addicted to cheap cash and high burn, change will be more dramatic as management teams will quickly shift gears from maximizing growth to preserving cash, once and when they realize that the supply of cheap fuel is finite.

So what’s coming?

  • Management changes.  As I wrote in The Curse of the Megaround, big rounds at $1B+ valuations come wrapped in high expectations (e.g., typically a 3x valuation increase in 3 years).  Executives will be expected to deliver against those expectations, and those who do not may develop sudden urges to “spend more time with the family.”  Some CEOs will discover that they are not in the same protected class as founders when these expectations go unmet.
  • Layoffs.  Many unicorns are burning $10M or more each quarter.  At a $10M quarterly burn, a company will need to layoff somewhere between 200 and 400 people to get to cashflow breakeven.  Layoffs of this size can be highly destabilizing, particularly when the team was putting in long hours, predicated on the company’s unprecedented success and hypergrowth, all of which presumably lead to a great exit.  Now that the exit looks less probable — and maybe not so great — enthusiasm for 70-hour weeks may vanish.
  • Lawsuits from common stockholders.  Only recently has the valuation-obsessed media noticed that many of those super valuations were achieved via the use of special terms, such as ratchets or multiple liquidation preferences.   For example, if a $100M company has a $300M preference stack and the last $100M went in with a 3x preference, then the common stock would be be worthless in a $500M sale of the company.  In this case, an executive with a 0.5% nominal ownership stake discovers his effective ownership is 0.0% because the first $500M of the sale price (i.e., all of it) goes to the preferred shareholders.  When people find they’re making either “no money” or “car money” when they expected “house money,” disappointment, anger, and lawsuits can result.  This New York Times story about the sale of formercorn Good Technology provides a real example of what I’m talking about, complete with the lawsuits.
  • Focus will be the new fashion.  Newly-hired replacement executive teams will credit the core technology of their businesses, but trash their predecessors for their lack of focus on core markets and products.  Customers unlucky enough to be outside the new core business will be abandoned — so they should be careful to ask themselves and their vendors whether their application is central to the company’s business, even in a downturn or refocus scenario.
  • Attention to customer success.  Investors are going to focus back on customer success in assessing the real lifetime value of a customer or contract.  People will remember that the operative word in SaaS is not software, but service, and that customers don’t pay for services that aren’t delivering.  Companies that emphasized TCV over ARR will be shown to have been swimming naked when the tide goes out, and much of that TCV is proven theoretical as opposed to collectible.
  • Attention to switching costs.  There is a tendency in Silicon Valley to assume all markets have high switching costs.  While this is certainly true in many categories (e.g., DBMS, ERP), investors are going to start to question just how hard it is to move from one service to another when companies are investing heavily in customer acquisition on potentially invalid assumptions about long-term relationships and high pricing power.

Despite considerable turmoil some great companies will be born from the wreckage.  And overall, it will be a great period for Silicon Valley with a convergence to the mean around basics like focus, customer success, and sustainable business models.  The real beauty of the system is not that it never goes out of kilter, but that it always returns to it, and that great companies continue to be produced both by, and in cases despite, the ever-evolving Silicon Valley process.

# # #

Footnotes

This post was inadvertently published on 12/23/15 with an incomplete ending and various notes-to-self at the bottom.  While I realized my mistake immediately (hitting PUBLISH instead of SAVE) and did my best to pull back the post (e.g., deleted the post and the auto-generated tweet to it, created a draft with a new name/URL), as the movie Sex Tape portrays, once something gets out in the cloud, it can be hard to get it back.

Unicorn Tears, Beyond Ultimate, and the Silicon Valley Hype Mentality,

Back in the day we working on a press release and I was a CMO.

Me:  “Somebody, get Randy (the PR director) in here.”

Me:  “Randy, what is this press release calling our new offering the ultimate in business intelligence?”

Randy:  “Yes and the problem is?”

Me:  “The problem is it’s not the ultimate, it’s better than ultimate, it’s beyond ultimate … there must be a word for that … I don’t know, maybe penultimate.”

Randy:  “Chief,” he said sheepishly after waiting a minute, “penultimate means one less than ultimate.  Ultimate means ultimate.  There is no word for one more than ultimate.”

Me:  “Oh.  Well, God damn it, go make one up.”

It was at that moment that I realized I’d been fully sucked into the Silicon Valley hype machine.  Just as unique means unique and requires no modifier like “amazingly,” so does ultimate means ultimate.

Speaking of “amazing,” during my tenure at Salesforce, I used to count the number of amazing’s Marc Benioff would say during a speech.  You’d run out of fingers in minutes.  But somehow it worked.  He was a great — no, amazing — speaker and I never got tired of listening to him.

This is Silicon Valley.   The land where one of my competitors can still peddle a cock-and-bull story about how he, as an immigrant limo driver with $26 (and a master’s in computer science), sold a company (where he was neither founder nor CEO), worked as (a member in the office of the) CTO at SAP, and is growing stunningly — no, amazingly — fast (despite a rumored recent down-round and rough layoffs).  Fact-checking, smact-checking.  If it’s a Man Bites Dog story, people will eat it up.  Blog it, hit publish, and move onto the next one.

Maybe I should pitch the equivalent story about me:

Lifeguard and Self-Taught Programmer Who Arrived in California with Only $30, a Red Bandana, and a Box of Bootlegged Grateful Dead Tapes Becomes CEO of Host Analytics

“Dude, I was guarding by the pool one day and this wicked thunderstorm hit and, flash, like totally suddenly I realized the world needed cloud-based, enterprise planning, budgeting, modeling, consolidation, and analytics.”

And we could discuss how I “hacked” on paper tape back in high school:  “the greatest part about hacking on paper tape was you could roll bones with it when you were done and literally, like, smoke your program.”

It would be a roughly equivalent story.  I’m sure they’d eat it up.

Silicon Valley is a place, after all, where we can create a metaphor for something that doesn’t exist — a unicorn  — and then discover 133 of them.

Is our reaction “bad metaphor?”  No, of course not.  It’s “wow, we’re special, we’ve got 133 things that don’t exist.”

Unicorns (generally defined as startups with a $1B+ valuation) are mostly of a result of three things:

  • The cost and hassle of being a public company, post Sox.  Why go public if you don’t have to?
  • The ability to raise formerly IPO-sized rounds (e.g., $100M) in the private markets.
  • A general bubble in late-stage financing where valuations are high enough to create the IPO-as-down-round phenomena

As the late-stage financing bubble appears to be near popping, you increasingly hear new terms for unicorns.  For example, Good Technology, a “onceacorn,” sold earlier this month for $400M.  Since I love words, I’ve been tracking these new terms closely with some amusement:  formercorns, “just horses with birthday hats on,” usta-corns, dying unicorns, and unicorpses.

So, hopefully, as the financing fuel that’s stoking the fire starts to die down, the hype bubble will go with it.  Until then, enjoy this tweet, which captures the spirit of Silicon Valley today just perfectly:

vape