Category Archives: Silicon Valley

Lost and Founder: A Painful Yet Valuable Read

Some books are almost too honest.  Some books give you too much information (TMI).  Some books can be hard to read at times.  Lost and Founder is all three.  But it’s one of the best books I’ve seen when it comes to giving the reader a realistic look at the inside of Silicon Valley startups.NeueHouse_Programming_LostandFound

In an industry obsessed with the 1 in 10,000 decacorns and the stories of high-flying startups and their larger-than-life founders, Lost and Founder takes a real look at what it’s like to found, fund, work at, and build a quite successful but not media- and Sand-Hill-Road-worshiped startup.

Rand Fishkin, the founder of Moz, tells the story of his company from its founding as a mother/son website consultancy in 2001 until his handing over the reins, in the midst of battling depression, to a new CEO in February 2014.  But you don’t read Lost and Founder to learn about Moz.  You read it to learn about Rand and the lessons he learned along the way.

Excerpt:

In 2001, I started working with my mom, Gillian, designing websites for small businesses in the shadow of Microsoft’s suburban Seattle-area campus. […] The dot-com bust and my sorely lacking business acumen meant we struggled for years, but eventually, after trial and error, missteps and heartache, tragedy and triumph, I found myself CEO of a burgeoning software company, complete with investors, employees, customers, and write-ups in TechCrunch.

By 2017, my company, Moz, was a $45 million/ year venture-backed B2B software provider, creating products for professionals who help their clients or teams with search engine optimization (SEO). In layman’s terms, we make software for marketers. They use our tools to help websites rank well in Google’s search engine, and as Google became one of the world’s richest, most influential companies, our software rose to high demand.

Moz is neither an overnight, billion-dollar success story nor a tragic tale of failure. The technology and business press tend to cover companies on one side or the other of this pendulum, but it’s my belief that, for the majority of entrepreneurs and teams, there’s a great deal to be learned from the highs and lows of a more middle-of-the-road startup life cycle.

Fishkin’s style is transparent and humble.  While the book tells a personal tale, it is laden with important lessons.  In particular, I love his views on:

  • Pivots (chapter 4).  While it’s a hip word, the reality is that pivoting — while sometimes required and which sometimes results in an amazing second efforts — means that you have failed at your primary strategy.  While I’m a big believer in emergent strategy, few people discuss pivots as honestly as Fishkin.
  • Fund-raising (chapters 6 and 7).  He does a great job explaining venture capital from the VC perspective which then makes his conclusions both logical and clear.  His advice here is invaluable.  Every founder who’s unfamiliar with VC 101 should read this section.
  • Making money (chapter 8) and the economics of founding or working at a startup.
  • His somewhat contrarian thoughts on the Minimum Viable Product (MVP) concept (chapter 12).  I think in brand new markets MVPs are fine — if you’ve never seen a car then you’re not going to look for windows, leather seats, or cup-holders.  But in more established markets, Fishkin has a point — the Exceptional Viable Product (EVP) is probably a better concept.
  • His very honest thoughts on when to sell a startup (chapter 13) which reveal the inherent interest conflicts between founders, VCs, and employees.
  • His cheat codes for next itme (Afterword).

Finally, in a Silicon Valley where failure is supposedly a red badge of courage, but one only worn after your next big success, Fishkin has an unique take on vulnerability (chapter 15) and his battles with depression, detailed in this long, painful blog post which he wrote the night before this story from the book about a Foundry CEO summit:

Near the start of the session, Brad asked all the CEOs in the room to raise their hand if they had experienced severe anxiety, depression, or other emotional or mental disorders during their tenure as CEO. Every hand in the room went up, save two. At that moment, a sense of relief washed over me, so powerful I almost cried in my chair. I thought I was alone, a frail, former CEO who’d lost his job because he couldn’t handle the stress and pressure and caved in to depression. But those hands in the air made me realize I was far from alone— I was, in fact, part of an overwhelming majority, at least among this group. That mental transition from loneliness and shame to a peer among equals forever changed the way I thought about depression and the stigma around mental disorders.

Overall, in a world of business books that are often pretty much the same, Lost and Founder is both quite different and worth reading.  TMI?  At times, yes.  TLDR?  No way.

Thanks, Rand, for sharing.

Video of my SaaStr 2018 Presentation: Ten Non-Obvious Things About Scaling SaaS

While I’ve blogged about this presentation before, I only recently stumbled into this full-length video of this very popular session — a 30-minute blaze through some subtle SaaS basics.  Enjoy!

I look forward to seeing everyone again at SaaStr Annual 2019.

The Domo S-1: Does the Emperor Have Clothes?

I preferred Silicon Valley [1] back in the day when companies raised modest amounts of capital (e.g., $30M) prior to an IPO that took 4-6 years from inception, where burn rates of $10M/year looked high, and where $100M raise was the IPO, not one or more rounds prior to it.  When cap tables had 1x, non-participating preferred and that all converted to a single class of common stock in the IPO. [2]

How quaint!

These days, companies increasingly raise $200M to $300M prior to an IPO that takes 10-12 years from inception, the burn might look more like $10M/quarter than $10M/year, the cap table loaded up with “structure” (e.g., ratcheting, multiple liquidation preferences).  And at IPO time you might end up with two classes common stock, one for the founder with super-voting rights, and one for everybody else.

I think these changes are in general bad:

  • Employees get more diluted, can end up alternative minimum tax (AMT) prisoners unable to leave jobs they may be unhappy doing, have options they are restricted from selling entirely or are sold into opaque secondary markets with high legal and transaction fees, and/or even face option expiration at 10 years. (I paid a $2,500 “administrative fee” plus thousands in legal fees to sell shares in one startup in a private transaction.)
  • John Q. Public is unable to buy technology companies at $30M in revenue and with a commission of $20/trade. Instead they either have to wait until $100 to $200M in revenue or buy in opaque secondary markets with limited information and high fees.
  • Governance can be weak, particularly in cases where a founder exercises directly (or via a nuclear option) total control over a company.

Moreover, the Silicon Valley game changes from “who’s smartest and does the best job serving customers” on relatively equivalent funding to “who can raise the most capital, generate the most hype, and buy the most customers.”  In the old game, the customers decide the winners; in the new one, Sand Hill Road tries to, picking them in a somewhat self-fulfilling prophecy.

The Hype Factor
In terms of hype, one metric I use is what I call the hype ratio = VC / ARR.  On the theory that SaaS startups input venture capital (VC) and output two things — annual recurring revenue (ARR) and hype — by analogy, heat and light, this is a good way to measure how efficiently they generate ARR.

The higher the ratio, the more light and the less heat.  For example, Adaptive Insights raised $175M and did $106M in revenue [3] in the most recent fiscal year, for a ratio of 1.6.  Zuora raised $250M to get $138M in ARR, for a ratio of 1.8.  Avalara raised $340M to $213M in revenue, for a ratio of 1.6.

By comparison, Domo’s hype ratio is 6.4.  Put the other way, Domo converts VC into ARR at a 15% rate.  The other 85% is, per my theory, hype.  You give them $1 and you get $0.15 of heat, and $0.85 of light.  It’s one of the most hyped companies I’ve ever seen.

As I often say, behind every “marketing genius” is a giant budget, and Domo is no exception [4].

Sometimes things go awry despite the most blue-blooded of investors and the greenest of venture money.  Even with funding from the likes of NEA and Lightspeed, Tintri ended up a down-round IPO of last resort and now appears to be singing its swan song.  In the EPM space, Tidemark was the poster child for more light than heat and was sold in what was rumored to be fire sale [5] after raising over $100M in venture capital and having turned that into what was supposedly less than $10M in ARR, an implied hype ratio of over 10.

The Top-Level View on Domo
Let’s come back and look at the company.  Roughly speaking [6], Domo:

  • Has nearly $700M in VC invested (plus nearly $100M in long-term debt).
  • Created a circa $100M business, growing at 45% (and decelerating).
  • Burns about $150M per year in operating cash flow.
  • Will have a two-class common stock system where class A shares have 40x the voting rights of class B, with class A totally controlled by the founder. That is, weak governance.

Oh, and we’ve got a highly unprofitable, venture-backed startup using a private jet for a bit less than $1M year [7].  Did I mention that it’s leased back from the founder?  Or the $300K in catering from a company owned by the founder and his brother.  (Can’t you order lunch from a non-related party?)

As one friend put it, “the Domo S-1 is everything that’s wrong with Silicon Valley in one place:  huge losses, weak governance, and now modest growth.”

Personally, I view Domo as the Kardashians of business intelligence – famous for being famous.  While the S-1 says they have 85 issued patents (and 45 applications in process), does anyone know what they actually do or what their technology advantage is?  I’ve worked in and around BI for nearly two decades – and I have no idea.

Maybe this picture will help.

domosolutionupdated

Uh, not so much.

The company itself admits the current financial situation is unsustainable.

If other equity or debt financing is not available by August 2018, management will then begin to implement plans to significantly reduce operating expenses. These plans primarily consist of significant reductions to marketing costs, including reducing the size and scope of our annual user conference, lowering hiring goals and reducing or eliminating certain discretionary spending as necessary

A Top-to-Bottom Skim of the S-1
So, with that as an introduction, let’s do a quick dig through the S-1, starting with the income statement:

domo income

Of note:

  • 45% YoY revenue growth, slow for the burn rate.
  • 58% blended gross margins, 63% subscription gross margins, low.
  • S&M expense of 121% of revenue, massive.
  • R&D expense of 72% of revenue, huge.
  • G&A expense of 29% of revenue, not even efficient there.
  • Operating margin of -162%, huge.

Other highlights:

  • $803M accumulated deficit.  Stop, read that number again and then continue.
  • Decelerating revenue growth, 45% year over year, but only 32% Q1 over Q1.
  • Cashflow from operations around -$150M/year for the past two years.  Stunning.
  • 38% of customers did multi-year contracts during FY18.  Up from prior year.
  • Don’t see any classical SaaS unit economics, though they do a 2016 cohort analysis arguing contribution margin from that cohort of -196%, 52%, 56% over the past 3 years.  Seems to imply a CAC ratio of nearly 4, twice what is normally considered on the high side.
  • Cumulative R&D investment from inception of $333.9M in the platform.
  • 82% revenues from USA in FY18.
  • 1,500 customers, with 385 having revenues of $1B+.
  • Believe they are <4% penetrated into existing customers, based on Domo users / total headcount of top 20 penetrated customers.
  • 14% of revenue from top 20 customers.
  • Three-year retention rate of 186% in enterprise customers (see below).  Very good.
  • Three-year retention rate of 59% in non-enterprise customers.  Horrific.  Pay a huge CAC to buy a melting ice cube.  (Only the 1-year cohort is more than 100%.)

As of January 31, 2018, for the cohort of enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV is 186% of the original license value, compared to 129% and 160% for the cohorts of enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively. For the cohort of non-enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV as of January 31, 2018 was 59% of the original license value, compared to 86% and 111% for the cohorts of non-enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively.

  • $12.4M in churn ARR in FY18 which strikes me as quite high coming off subscription revenues of $58.6M in the prior year (21%).  See below.

Our gross subscription dollars churned is equal to the amount of subscription revenue we lost in the current period from the cohort of customers who generated subscription revenue in the prior year period. In the fiscal year ended January 31, 2018, we lost $12.4 million of subscription revenue generated by the cohort in the prior year period, $5.0 million of which was lost from our cohort of enterprise customers and $7.4 million of which was lost from our cohort of non-enterprise customers.

  • What appears to be reasonable revenue retention rates in the 105% to 110% range overall.  Doesn’t seem to foot to the churn figure about.  See below:

For our enterprise customers, our quarterly subscription net revenue retention rate was 108%, 122%, 116%, 122% and 115% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For our non-enterprise customers, our quarterly subscription net revenue retention rate was 95%, 95%, 99%, 102% and 98% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For all customers, our quarterly subscription net revenue retention rate was 101%, 107%, 107%, 111% and 105% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively.

  • Another fun quote and, well, they did take about the cash it takes to build seven startups.

Historically, given building Domo was like building seven start-ups in one, we had to make significant investments in research and development to build a platform that powers a business and provides enterprises with features and functionality that they require.

  • Most customers invoiced on annual basis.
  • Quarterly income statements, below.

domo qtr

  • $72M in cash as of 4/30/18, about 6 months worth at current burn.
  • $71M in “backlog,” multi-year contractual commitments, not prepaid and ergo not in deferred revenue.  Of that $41M not expected to be invoiced in FY19.
  • Business description, below.  Everything a VC could want in one paragraph.

Domo is an operating system that powers a business, enabling all employees to access real-time data and insights and take action from their smartphone. We believe digitally connected companies will increasingly be best positioned to manage their business by leveraging artificial intelligence, machine learning, correlations, alerts and indices. We bring massive amounts of data from all departments of a business together to empower employees with real-time data insights, accessible on any device, that invite action. Accordingly, Domo enables CEOs to manage their entire company from their phone, including one Fortune 50 CEO who logs into Domo almost every day and over 10 times on some days.

  • Let’s see if a computer could read it any better than I could.  Not really.

readability

  • They even have Mr. Roboto to help with data analysis.

Through Mr. Roboto, which leverages machine learning algorithms, artificial intelligence and predictive analytics, Domo creates alerts, detects anomalies, optimizes queries, and suggests areas of interest to help people focus on what matters most. We are also developing additional artificial intelligence capabilities to enable users to develop benchmarks and indexes based on data in the Domo platform, as well as automatic write back to other systems.

  • 796 employees as of 4/30/18, of which 698 are in the USA.
  • Cash comp of $525K for CEO, $450K for CFO, and $800K for chief product officer
  • Pre-offering it looks like founder Josh James owns 48.9M shares of class A and 8.9M shares of class B, or about 30% of the shares.  With the 40x voting rights, he has 91.7% of the voting power.

Does the Emperor Have Any Clothes?
One thing is clear.  Domo is not “hot” because they have some huge business blossoming out from underneath them.  They are “hot” because they have raised and spent an enormous amount of money to get on your radar.

Will they pull off they IPO?  There’s a lot not to like:  the huge losses, the relatively slow growth, the non-enterprise retention rates, the presumably high CAC, the $12M in FY18 churn, and the 40x voting rights, just for starters.

However, on the flip side, they’ve got a proven charismatic entrepreneur / founder in Josh James, an argument about their enterprise customer success, growth, and penetration (which I’ve not had time to crunch the numbers on), and an overall story that has worked very well with investors thus far.

While the Emperor’s definitely not fully dressed, he’s not quite naked either.  I’d say the Domo Emperor’s donning a Speedo — and will somehow probably pull off the IPO parade.

###

Notes

[1] Yes, I know they’re in Utah, but this is still about Silicon Valley culture and investors.

[2] For definitions and frequency of use of various VC terms, go to the Fenwick and West VC survey.

[3] I’ll use revenue rather than trying to get implied ARR to keep the math simple.  In a more perfect world, I’d use ARR itself and/or impute it.  I’d also correct for debt and a cash, but I don’t have any MBAs working for me to do that, so we’ll keep it back of the envelope.

[4] You can argue that part of the “genius” is allocating the budget, and it probably is.  Sometimes that money is well spent cultivating a great image of a company people want to buy from and work at (e.g., Salesforce).  Sometimes, it all goes up in smoke.

[5] Always somewhat truth-challenged, Tidemark couldn’t admit they were sold.  Instead, they announced funding from a control-oriented private equity firm, Marlin Equity Partners, as a growth investment only a year later be merged into existing Marlin platform investment Longview Solutions.

[6] I am not a financial analyst, I do not give buy/sell guidance, and I do not have a staff working with me to ensure I don’t make transcription or other errors in quickly analyzing a long and complex document.  Readers are encouraged to go the S-1 directly.  Like my wife, I assume that my conclusions are not always correct; readers are encouraged to draw their own conclusions.  See my FAQ for complete disclaimer.

[7] $900K, $700K, and $800K run-rate for FY17, FY18, and 1Q19 respectively.

The Question that CEOs Too Often Don’t Discuss with the Board

Startup boards are complex.  While all board members own stock in the company their interests are not necessarily aligned.

  • Founders may be motivated by a vision to change the world, to hit a certain net worth target, to see their name in an S-1, to make the Forbes 500, or — and I’ve seen crazier things — to make more than their Stanford roommate.  First-time founders with little net worth can be open to selling at relatively low prices.  Conversely, serial successful founders may need a large exit simply to move the needle on their net worth.  Founders can also be religious zealots and take positions like “I wouldn’t sell to Microsoft or Oracle at any price.”
  • Independent board members typically have significant net worth (i.e., they’ve been successful at something which is why want them on your board) and relatively small stakes which, by default, financially incents them to seek large exits.  While they notionally represent the common stock, they are often aligned with either the founders or one of the investors in the company — they got on the board for a reason, often existing relationships —  and thus their views may be shaped by the real or perceived interest of those parties.  Or, they can simply drive an agenda that they believe is best for the company — whatever they happen to think “best” means.
  • Venture capitalists (VCs) are motivated by generating returns for their funds.  Simple, right?  Not so fast.  VC is increasingly a “hits business” where a few large outcomes can mean the difference between at 10% and 35% IRR over a fund’s ten-year life.  Thus, VCs have a general tendency to seek huge exits (“better to sell too late than too early”), but they are also motivated by other factors such as the expectations they set when they raised their fund, the performance of other investments in the fund (e.g., do they need a big hit to bail out a few bad bets), and their relationships with members of other funds represented on the company’s board.

In this light, it’s clearly simplistic to say that everyone is aligned around a single goal:  to maximize the value of the stock.  Yes, surely that is true at one level.  But it gets a bit more complicated than that.

That’s why it’s so important that CEOs ask the board one question that, somewhat amazingly, they all too often don’t:  what does success look like?  And it doesn’t hurt to re-ask it every few years as any given board member’s position may change over time.

I’m always shocked how the simplest of questions can generate the most debate.

Aside:  back in the day at Business Objects (~1998), I suggested bringing in the Chasm Group to help us with a three-day, strategic planning offsite.  I figured we’d spend a morning reviewing the key concepts in Crossing the Chasm, at most one afternoon generating consensus on where we sat on their technology adoption lifecycle curve, and then two days working on strategic goals and operational plans after that.

Tech-Adoption-Lifecycle-01

With about 12 people who had worked together closely for years, after three full days we never agreed where we sat on the curve.  We spent literally the entire time arguing, often intensely, and never even got to the rest of the agenda.  Fortunately, that didn’t end up impeding our success, but it was a big lesson for me.  End aside.

So be ready for that simple question to generate a long answer.  Most probably, several long answers.  In fact, in order to get the best answer, I’d suggest asking board members about it first individually (to avoid any group decision-making biases) and then discuss it as a group.

But before examining the answers you can expect to this question, let’s take a minute to consider why this conversation doesn’t occur more often and more naturally.  I think there are three generic reasons:

  • Conflict aversion.  Perhaps sensing real misalignment, like in a bad marriage the CEO and board tacitly agree to not discuss the problem until they must.  You may hear or make excuses like “let’s cross that bridge when we come to it,”  “let’s execute this year’s plan and then discuss that,” or “if there’s no offer on the table then there’s nothing to discuss.”  Or, in a more Machiavellian situation, a board member may be thinking, “let’s ride Joe like a rented mule to $5M and then shoot him,” continuallying defer the conversation on that logic.  Pleasant or unpleasant, it’s usually better to address conflicts early rather than letting them fester.
  • Rationalization of unrealistic expectations.  If some board members constantly refrain “this can be a billion-dollar company,” perhaps the CEO rationalizes it, thinking “they don’t really believe that; they’re just saying it because they think they’re supposed to.”  But what if they do believe it?
  • The gauche factor.  Some people seem to think it’s a gauche topic of conversation.  “Hey, our company vision statement says we’re making the world a better place through elegant hierarchies for maximum code reuse and extensibility, we shouldn’t be focusing on something so crass as the exit, we should be talking about making the world better.”  VCs invest money for a reason, they measure results by the IRR, and they can typically cite their IRRs (and those of their partners) from memory.  It’s not gauche to discuss expectations and exits.

When you ask your board members what success looks like these are the kinds of things you might hear:

  • Disrupting the leader in a given market.
  • Building a $1B revenue company.
  • Becoming a unicorn ($1B valuation).
  • Changing the way people work.
  • Getting a 10x in 5-7 years for an early stage fund, or getting a 3x in 3-5 years for a later stage fund.
  • Showing my Mother my name in an S-1 (a sub-case of “going public”).
  • Getting our software into the hands of over 1M people.
  • Realizing the potential of the company.
  • Selling the company for more than I think it’s worth.
  • Getting acquired by Google or Cisco for a price above a given threshold.
  • Building a true market leader.
  • Creating a Silicon Valley icon, a household name.
  • Selling the company for {a base-hit, double, triple, home-run, or grand-slam} outcome.

Given the possibility of a list as heterogeneous as this, doesn’t it make sense to get this question on the table as opposed to in the closet?

I learned my favorite definition of strategy from a Stanford professor who defined strategy as “the plan to win.”  The beauty of this definition is that it instantly begs the question “what is winning?”  Just as that conversation can be long, contentious, and colorful, so is the answer to the other, even more critical question:  what does success look like?

Kellblog Predictions for 2018

In continuing my tradition of offering predictions every year, let’s start with a review of my hits and misses on my 2017 predictions.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s.  HIT.
  2. Social media companies finally step up and do something about fake news. MISS, but ethical issues are starting to catch up with them.
  3. Gut feel makes a comeback. HIT, while I didn’t articulate it as such, I see this as the war on facts and expertise (e.g., it’s cold today ergo global warming isn’t real despite what “experts” say).
  4. Under a volatile leader, 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.  HIT.
  5. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. MISS, turns out this program was never classical government investment in infrastructure, but a massive privatization plan that never happened.
  6. Huge emphasis on security and privacy. PARTIAL HIT, security remained a hot topic and despite numerous major breaches it’s still not really hit center stage.
  7. In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  HIT.
  8. Artificial intelligence hits the peak of inflated expectations. HIT.
  9. The IPO market comes back. MISS, though according to some it “sucked less.”
  10. Megavendors mix up EPM and ERP or BI. PARTIAL HIT.  This prediction was really about Workday and was correct to the extent that they’ve seemingly not made much progress in EPM.

Kellblog’s Predictions for 2018

1.  We will again continue to see a level of divisiveness and social discord not seen since the 1960s. We have evolved from a state of having different opinions about policies based on common facts to a dangerous state based on different facts, even on easily disprovable claims, e.g., the White House nativity scene.  The media is advancing, not reducing, this divide.

2.  The war on facts and expertise will continue to escalate. Read The Death of Expertise for more.   This will extend to a war on college. While an attempted opening salvo on graduate student tuition waivers didn’t fire, in an environment where the President’s son says, “we’ll take $200,000 of your money; in exchange we’ll train your children to hate our country,” you can expect ongoing attacks on post-secondary education.  This spells trouble for Silicon Valley, where a large number of founders and entrepreneurs are former grad students as well as immigrants (which is a whole different area of potential trouble).

3.  Leading technology and social media companies finally step up to face ethical challenges. This means paying more attention to their own culture (e.g., sexual harassment, brogrammers).  This means taking responsibility for policing trolls, spreading fake news, building addictive content, and enabling foreign intelligence operations.  Thus far, they have tended to argue they are simply keepers of the town square, and not responsible for the content shared there.  This abdication of responsibility should start to stop in 2018, if only because people start to tune-out the services.  This leads to one of my favorite tweets of the year:

Capture

4.  AI will move from hype to action, meaning bigger budgets, more projects, and some high visibility failures. It will also mean more emphasis on voice and more conversational chatbots.  For finance departments, this means more of what Ventana’s Rob Kugel calls the age of robotic finance, which unites AI and machine learning, robotic process automation (RPA), natural language bots, and blockchain-based distributed ledgers.

5. AI will continue to generate lots of controversy about job displacement. While some remain optimistic, the consensus viewpoint seems to be that AI will suppress employment, most likely widening the wealth inequality gap.  A collapsing educational system combined with AI-driven pressure on low-skilled work seems a recipe for trouble.

6.  The bitcoin bubble bursts. As a reminder, at one point during the peak of tulip mania, the Dutch East India Company was worth more, on an inflated-adjusted basis, than twenty of today’s technology giants combined.

tulips

7.  The Internet of Things (IoT) will continue to build momentum.  IoT won’t hit in a massive horizontal way, instead B2B adoption will be lead by certain verticals such as healthcare, retail, and supply chain.

8.  The freelance / gig economy continues to gain momentum with freelance workers poised to pass traditional employees by 2027. While the gig economy brings advantages to high-skilled knowledge workers (e.g., freedom of location, freedom of work projects), this same trend threatens low-skilled workers via the continual decomposition of full-time jobs in a series of temp shifts.  This means someone working 60 hours a week across three 20-hour shifts wouldn’t be considered to be a full-time employee and thus not eligible for full-time benefits, further increasing wealth inequality.

freelancers

9.  M&A heats up due to repatriation of overseas cash. Apple alone, for example, has $252B in overseas cash.  With the new tax rate dropping from 35% to 15.5%, it will now be ~$50B less expensive for Apple to repatriate that cash.  Overall, US companies hold trillions of dollars overseas and making it cheaper for them to repatriate that cash suggests that they will be flush with dollars to invest in many areas, including M&A

10.  2018 will be a good year for cloud EPM vendors. The dynamic macro environment, the opportunities posed by cash repatriation, and the strong fundamentals in the economy will increase demand for EPM software that helps companies explore how to best exploit the right set of opportunities facing them.  Oracle will fail in pushing PBCS into the NetSuite base, creating a nice third-party opportunity.  SAP, Microsoft, and IBM will continue to put resources into other strategic investment areas (e.g., IBM and Watson, SAP and Hana) leaving fallow the EPM market adjacent to ERP.  And the greenfield opportunity to replace Excel for financial planning, budgeting, and even consolidations will continue drive strong growth.

Let me wish everyone, particularly the customers, partners, and employees of Host Analytics, a Happy New Year in 2018.

# # #

Disclaimer:  these predictions are offered in the spirit of fun.  See my FAQ for more on this and other usage terms.

The SaaS Rule of 40

After the SaaSacre of early 2016, investors generally backed off a growth-at-all-costs mindset and started to value SaaS companies using an “appropriate” balance of growth and profitability.  The question then became, what’s appropriate?  The answer was:  the rule of 40 [1].

What’s the rule of 40?  Growth rate + profit should be greater than or equal to 40%.

There are a number of options for deciding what to use to represent growth (e.g., ARR) and profit (e.g., EBITDA, operating margin). For public companies it usually translates to revenue growth rate and free cash flow margin.

It’s important to understand that such “rules” are not black and white.  As we’ll see in a minute, lots of companies deviate from the rule of 40.  The right way to think about these rules of thumb is as predictors.  Back in the day, what best predicted the value of a SaaS company?  Revenue growth — without regard for margin.  (In fact, often inversely correlated to margin.)  When that started to break down, people started looking for a better independent variable.  The answer to that search was the rule of 40 score.

Let’s examine a few charts courtesy of the folks at Pacific Crest and as presented at the recent, stellar Zuora CFO Forum, a CFO gathering run alongside their Subscribed conference.

rule-of-40

This scatter chart plots the two drivers of the rule of 40 score against each other, colors each dot with the company’s rule of 40 score, and adds a line that indicates the rule of 40 boundary.  42% of public SaaS companies, and 77% of public SaaS market cap, is above the rule of 40 line.

As a quick demonstration of the exception-to-every-rule principle, Tintri recently went public off 45% growth with -81% operating margins, [2] reflecting a rule of 40 score of -36%, and a placement that would be off the chart (in the underneath sense) even if corrected for non-cash expenses.

For those interested in company valuations, the more interesting chart is this one.

rule of 40 valuation.PNG

This chart plots rule of 40 score on the X axis, valuation multiple on the Y axis, and produces a pretty good regression line the shows the relationship between the two.  In short, the rule of 40 alone explains nearly 50% of SaaS company valuation.  I believe that outliers fall into one of two categories:

  • Companies in a strategic situation that explains the premium or discount relative to the model — e.g., the premium for Cloudera’s strong market position in the Hadoop space.
  • Companies whose valuations go non-linear at the high end due to scarcity — e.g., Veeva.

Executives and employees at startups should understand [3] the rule of 40 as it explains the general tendency of SaaS companies to focus on a balance of growth and profitability as opposed to a growth at all costs strategy that was more popular several years back.  Ignore the rule of 40 at your peril.

Notes

[1] While the Rule of 40 concept preceded the SaaSacre, I do believe that the SaaSacre was the wake-up call that made more investors and companies pay attention to.

[2] Using operating margin here somewhat lazily as I don’t want to go find unlevered free cash flow margin, but I don’t think it materially changes the point.

[3] Other good rule of 40 posts are available from:  Tomasz Tungaz, Sundeep Peechu, and Jeff Epstein and Josh Harder.

Detecting and Eliminating the Rolling Hairballs in your Sales Pipeline

Quick:  what’s the biggest deal in this quarter’s sales pipeline?  Was that the biggest deal in last quarter’s pipeline?  How about the quarter before?  Do you have deals in your pipeline older than your children?

If you’re answering yes to these questions, then you’re probably dealing with “rolling hairballs” in your pipeline.  Rolling hairballs are bad:

  • They exaggerate the size of the pipeline.
  • They distort coverage and conversion ratios.
  • They mess up expected-value forecasts, like a forecast-category or stage-weighted sales forecast.

Maybe they’re real deals; maybe they’re figments of a rep’s imagination.  But, if you’re not careful, they pollute your pipeline and your metrics.

Let’s define a rolling hairball

A rolling hairball is a typically large opportunity that sits in your current-quarter pipeline every quarter, with a close date that slips every quarter.  At 2 quarters it’s a suspected rolling hairball; at 3 or more quarters it’s a confirmed one.

Rolling Hairball Detection

The first thing you need to do is find rolling hairballs.  They’re tricky because salesreps always swear they’re real deals that are supposed to finally close this quarter.  What makes rolling hairballs obvious is their ever-sliding close dates.  What makes them dangerous is their size (including an accumulation of them that aggregate to a material fraction of the pipeline).

If you want to find rolling hairballs, look for opportunities in the current-quarter pipeline that were also in last-quarter’s pipeline.  That will find numerous bona fide slipped deals, but it will also light-up potential rolling hairballs.  To determine if an opportunity is  a rolling hairball, for sure, you can do one of two things:

  • See if it also appeared in the current-quarter pipeline in any quarters prior to the previous one.
  • Look at its stage or forecast category.  If either of those suggest it won’t be closing this quarter, it’s another big hairball indicator.

The more sophisticated way to find them is to examine “stuck opportunity” reports that light-up deals that are moving through pipeline stages too slowly compared to your norms.

But typically, the hairball is a big opportunity hiding in plain sight.  You know it was in last quarter’s pipeline and the quarter before that.  You’ve just been deluded into believing it’s not a hairball.

Fixing Rolling Hairballs

There are two ways to fix rolling hairballs:

  • Fix the close date.  Reps are subtly incented to put deals in the current quarter (e.g., to show they’re working on something, to show they might bring in some big sales this quarter). The manager needs to get on the phone with the customer and, after having verified it’s a real opportunity, get the real timeframe in which it might close.  Assigning a realistic close date to the opportunity makes your pipeline more real and reminds the rep that they need to be working on other shorter-term opportunities as well.  (There is no mid-term if you fail enough in the short term.)  The deal will still remain in the all-quarters pipeline, but it won’t always be in the current-quarter pipeline, ever-sliding, and distorting metrics and ratios.

 

  • Fix the size. While a realistic close date is the best solution, what makes rolling hairballs dangerous is their size.  So, if the salesrep really believes it’s a current-quarter opportunity, you can either reduce its size or split it into two opportunities (particularly if that’s a possible outcome), a small one in the current quarter along with an upsell in the future.  Note that this approach can be dangerous, with lots of little hairball-lets flying below radar, so you should only try if it you’re sure your salesops team can produce the reports to find them and if you believe it reflects real customer buying patterns.

Don’t let rolling hairballs pollute your pipeline metrics and ratios.  Admit they exist, find them, and fix them.  Your sales and sales forecasting will be more consistent as a result.