Category Archives: Startups

The Venture Capital Inversion

There used to a be time in Silicon Valley when a startup created a strategy, made a business plan to go execute it, and then raised the amount of money required to execute the business plan.

That seems pretty  quaint these days.  Because today, many companies have this upside-down.  Instead of making a plan and raising funds to execute it, they raise a pile of money and then go figure out how to spend it.

This is happening largely because of the frothy, particularly mid- to late-stage financing environment that exists today.  More and more money is going into later-stage VC and PE growth funds, funds get bigger, minimum check sizes get bigger, and all of sudden you have a bunch of investors who each need to write checks of $50M to $100m to make their funds work and those check sizes start dominating round sizes in Silicon Valley.

But it’s all upside down.  Companies shouldn’t raise more money because investors want to write bigger checks.  Companies should only raise more money if they need it to fund their plan.

A key part of building a startup is focus.  Flooding companies with money works against focus.  Remember the startup epitaph:

Capture

When startups “just do both” they fail to choose — in so doing, often choose to fail.  When you flood a startup with money, it tends not just to do both, but perhaps all 4 or 5, of the ideas that were in discussion.

When a company gets caught in the VC inversion bad things happen.  For details, see this post I wrote entitled Curse of the Megaround, but the short summary is that startups with too much cash make too many questionable investments that defocus the company and don’t provide returns, ultimately resulting in the termination of the CEO and usually a chunk of the executive team along with him/her.  In short, turmoil.

Remember this tweet from Marc Andreessen:

Capture1

So the next time you hear a company celebrating a $100M round ask yourself these questions:

  • Can they actually put the money to productive use?
  • What distractions will they start or continue to invest in?
  • How much longer will the CEO and executive team last given the new, heavy pressure put on the valuation?

Startups should be about entrepreneurs driving a vision for customers that benefits the founders and employees, with the VCs along for the ride.  Let’s not get that inverted and end up with startups being run for the late-stage investors with the customers, employees, and founders along for the ride.

Are Your Managers Good Enough? A Simple Test

When I listen to senior executives talk about their first- and second-line managers, I sometimes get pretty concerned.  That happens when I hear what I call “good enough” thinking.

“Yeah, he’s not great, but he’s good enough.”

“She’s doing a solid job, but nothing too inspirational.”

“He’s not a great manager, but he can stay on top of the business.”

The purpose of this post is a to provide a brief inspirational reminder:  good enough isn’t.

I know why executives and managers fall victim to “good enough” thinking:

  • Hiring is hard
  • Management is hard
  • Hiring managers is therefore hard^2

So while most executives demand excellence from their front-line employees, they seem to dial back their expectations when it comes to management.  The only thing scarier than hiring new salesreps or product managers is hiring sales managers or product management directors.  Scary though it may be, it’s their job to do so.

In mulling this, I have come up with a simple test to determine if you managers are good enough:

EVERY EMPLOYEE SHOULD HAVE A MANAGER TO WHOM THEY LOOK UP AND FROM WHOM THEY CAN LEARN.

If your managers don’t pass that test, then maybe they shouldn’t be managing.

More Turmoil at Adaptive Insights

I always have mixed feelings about competitive blog posts and to keep my life simple and the blog pure, I generally try to avoid doing them.  However, for a bevy of reasons related primarily to how Adaptive Insights chooses to compete with Host Analytics, I have made and will continue to make a few exceptions.

From the day I joined Host Analytics, Adaptive made a deliberate FUD campaign against Host Analytics and aimed very much at the company.

  • They’d point out I was a new CEO and that new was scary.  They’d forget to say experienced CEO who already grew a company to $80M, knew the BI/EPM category, and was running a $500M division at Salesforce.
  • They’d say we had scary management turnover.  They’d forget to say that I was building a new team to take the company to the next level and rather than examining the simple fact of change, you should evaluate whether the change was good or bad.  The real question was whether the team I was building was well suited to moving the company forward.  Did the people have the right experience?  Had they built startups before?  Did they know the category?
  • They’d talk about their funding and tell customers (crossing the defamation line in my humble opinion) that we were risky to buy from due to financing issues.  Anaplan shut that down pretty fast after raising a $100M round and to date Crunchbase reports that Host Analytics has raised $86M and Adaptive $101M — no big difference there.
  • They’d boast that they hired our former people.  They’d forget the part about “that we didn’t want.”  In my tenure we’ve never hired someone in the reverse direction, and I don’t expect we will.  Our aim is to be “the Hyperion of the cloud” and you don’t get there with low-end people pumping low-end product.

Adaptive’s argument was simple:  customers should (1) buy from the company who’s raised the most money in the space and (2) not buy from a company if they have had senior management changes.  Thus, I am pleased to report by Adaptive’s own “insights” (i.e., reasoning), that customers should not buy from them.

Why?

If you want the company whose raised the most capital, it’s not Adaptive, it’s Anaplan at $144M.

Note that I never made the argument that most money is best.  Business Objects was grown to $1B+ in revenues on something like $4M in VC.  Tableau is worth $8B today and was built on $15M in (as I hear it, unneeded) VC.  In my opinion, when it comes to startups and VC, the Goldilocks rule applies:  neither too much nor too little — but just right.

If you want to avoid companies with management turmoil, consider the following:

  • By my count, Adaptive Insights is on its fourth CEO since 2011.  Count:  (1) the interim guy whose name I can’t remember, (2) Rob Hull who I believe acted as interim at some point, (3) John Herr who was exited in July 2014, and now (4) retired East Coast venture capitalist Tom Bogan.
  • Long-time SVP of Sales Neil Thomas left the company this past November after 8 years.

Quick: what’s the #1 reason people with quotas suddenly leave companies?

I will try to avoid the tendency to editorialize about the subjective question of whether the new team is the right one, with the right experience, in the right categories, et cetera and simply observe this fact:  if you believe Adaptive’s argument that you should not buy from companies with management changes, then you shouldn’t buy from Adaptive.

#QED.

karma.domino

Bottom-Fishing Acquisitions and Catching Falling Knives

As mentioned in my recent Curse of the Megaround post, some companies that find themselves flush with cash and under heavy pressure to grow, decide to embark on dubious acquisitions to help shore up the growth story.

As one reader it put it, you can summarize your megaround post with the simple phrase “much money makes you stupid.”  And it can.  Thus, as the old saw goes, fools and their money are soon parted.

What separates good from bad acquisitions in this context?  As a general rule, I’d say that when high-growth venture-backed companies acquire firms that would otherwise best be acquired by private equity, it’s a bad thing.  Why?

Firms destined to be acquired by private equity follow a typical pattern.

  • They are old, typically 10+ years
  • They have tried multiple iterations on a strategy and none has worked
  • They have a deep stack of technology built over the years but most of which could be quickly replaced with modern, often open source, standard components
  • They tend to get strategically inverted — starting out with “what we have” as opposed to “what the market wants”
  • They have gone through several generations of management teams
  • Basically, they’re turnarounds

So private equity funds bottom-fish these opportunities, buy companies for a fraction of the total invested venture capital, scrap most of the original dream and either [1] double down on one core piece that’s working or [2] roll the company up with N adjacent companies all selling to the same buyer.

This is hard work.  This is dirty work.  This is “wet work” involving lots of headcount changes.  And private equity is good at it.   In one sense (and excluding private equity growth funds), it’s what they do.

High-flying VC backed startups are simply the wrong types of buyers to contemplate these acquisitions.  In the core business, it’s all about grow, grow, and grow.  In the acquired business, it’s all about cut, cut, cut and focus, focus, focus.  These are two very different mentalities to hold in your head at one time and the typical fail pattern is apply the grow-grow-grow mentality to the broken startup that repeatedly hasn’t-hasn’t-hasn’t.

The other failure pattern is what I call the worst-of-breed suite.  This happens when a player in space X acquires a two-bit player in space Y, hoping to “get a deal” on a cheap technology they can then sell to their customers.   The vendor is thinking “I can sell more stuff through my existing channel.”  However, the customer is thinking “I don’t want to use a worst-of-breed product just because you decided to acquire one on the cheap.”  Moreover, with easy of integration of cloud services, there is typically no real integration advantage between the cheaply acquired product and a third-party best-of-breed one.

On Wall Street, they say that bottom-fishing falling stocks is like catching falling knives.  For high-growth startups, trying to bottom-fish failed startups is pretty much the same thing.

The Curse of the Megaround

With what everyone seems reluctant to call a bubble in late-stage, private financing in full swing, I thought I’d do a quick post to drill into a concept I presented in my 2015 predictions post, something I call the curse of the megaround.

We will do that by examining the forces, and the winners and losers, surrounding a megaround.  Let’s start with a hypothetical example. Company X raises $200M at $1B pre-money, giving them a $1.2B post-money valuation.

Champagne is popped, the financing is celebrated, the tech press bows, and the company is added to many unicorn trackers.

Now what happens?

  • The CEO is under immediate pressure to invest the additional capital.  If you take the rule of thumb that most venture rounds are designed to last 18-24 months, then a $200M raise implies a cash burn rate of $8 to $10M/month or $25 to $30M/quarter.  That is an enormous burn rate and in many cases it is difficult or impossible to spend that much money wisely.
  • The CEO is under heavy pressure to triple the value of the company in 2-3 years.  The investors who do these rounds are typically looking for a 3x return in 2-3 years.  So the CEO is under huge pressure to make the company worth $3.6B in 2-3 years.
  • This, in turn, means the CEO will start investing the money not only in promising growth initiatives, but also dubious ones.   Product lines are over-extended.  Geographic over-expansion occurs.  Hiring quality drops — in an attempt to not fall behind the hiring plan and lose all hope of achieving the numbers.
  • In cases, money is waste en masse in the form of dubious acquisitions, in the hope of accelerating product, employee, and customer growth.  However, the worst time to take on tricky acquisitions is when a company is already falling behind its own hypergrowth plans.
  • All of this actions were done in the name of “well, we had no hope of making the plan if we didn’t open in 12 countries, hire 200 people, add 3 product lines, and buy those 2 companies.”  So we may as well have tried as we would have been fired anyway.  At least we gave it our best shot, right?
  • This often comes to a head in a Lone Ranger moment when the board turns on the CEO.  “Didn’t we agree to that hiring plan?  Didn’t we agree to those product line extensions?  Didn’t we agree to that acquisition?” the CEO thinks.  But the board thinks differently.  “Yes, we agreed to them, but you were accountable for their success.”

Yes, being CEO can be a lonely job.  This is why I call it the curse of the megaround — because it’s certainly a curse for the CEO.  But the situation isn’t necessarily a curse for everyone.  Let’s examine the winners and losers in these situations.

Winners

  • The founders.  They get the benefit of a large investment in their company at low dilution without the downside of increased expectations and the accountability for delivering against them.
  • The private equity fund managers.  Provided the turmoil itself doesn’t kill the company and new, more realistic plans are achieved, the PE fund managers still get their 2+20 type fee structure, earning 2% a year baseline and 20% of the eventual upside as carry.  In a “more normal” world where companies went public at $300M in market cap, there would be no way to earn such heavy fees in these investments.

Losers

  • The CEO who is typically taken out back and shot along with any of the operating managers also blamed for the situation.
  • The company’s customers who are typically ignored and under-served during the years of turmoil where the company’s focus is on chasing an unreachable growth plan and not on customer service.
  • In the event the company is sold at a flat or down valuation, the common stock holders (including founders and employees) who can see their effective ownership either slashed or wiped-out by the multiple liquidation preferences often attached to the megaround.  (People love to talk about the megaround valuation, but they never seem to talk about the terms that go with it!)
  • The private equity limited partners whose returns are diminished by the very turmoil their investment created and who are stuck paying a high 2+20 fee structure with decade-ly liquidity as opposed to the 1% fee structure and daily liquidity they’d have with mutual funds if the companies were all public (as they would have been pre-Sarbox.)
  • The private equity limited partners who ultimately might well end up with a down-round as IPO.

In some situations — e.g., huge greenfield markets which can adopt a new solution quickly and easily — a megaround may well be the right answer.  But for most companies these days, I believe they are more curse than blessing.

Survivor Bias in Churn Calculations: Say It’s Not So!

I was chatting with a fellow SaaS executive the other day and the conversation turned to churn and renewal rates.  I asked how he calculated them and he said:

Well, we take every customer who was also a customer 12 months ago and then add up their ARR 12 months ago and add up their ARR today, and then divide today’s ARR by year-ago ARR to get an overall retention or expansion rate.

Well, that sounds dandy until you think for a minute about survivor bias, the often inadvertent logical error in analyzing data from only the survivors of a given experiment or situation.  Survivor bias is subtle, but here are some common examples:

  • I first encountered survivor bias in mutual funds when I realized that look-back studies of prior 5- or 10-year performance include only the funds still in existence today.  If you eliminate my bogeys I’m actually an below-par golfer.
  • My favorite example is during World War II, analysts examined the pattern of anti-aircraft fire on returning bombers and argued to strengthen them  in the places that were most often hit.  This was exactly wrong — the places where returning bombers were hit were already strong enough.  You needed to reinforce them in the places that the downed bombers were hit.

So let’s turn back to churn rates.  If you’re going to calculate an overall expansion or retention rate, which way should you approach it?

  1. Start with a list of customers today, look at their total ARR, and then go compare that to their ARR one year ago, or
  2. Start with a list of customers from one year ago and look at their ARR today.

Number 2 is the obvious answer.  You should include the ARR from customers who choose to stop being customers in calculating an overall churn or expansion rate.  Calculating it the first way can be misleading because you are looking at the ARR expansion only from customers who chose to continue being customers.

Let’s make this real via an example.

survivor bias

The ARR today is contained in the boxed area.  The survivor bias question comes down to whether you include or exclude the orange rows from year-ago ARR.  The difference can be profound.  In this simple example, the survivor-biased expansion rate is a nice 111%.  However, the non-biased rate is only 71% which will get you a quick “don’t let the door hit your ass on the way out” at most VCs.  And while the example is contrived, the difference is simply one of calculation off identical data.

Do companies use survivor-biased calculations in real life?  Let’s look at my post on the Hortonworks S-1 where I quote how they calculate their net expansion rate:

We calculate dollar-based net expansion rate as of a given date as the aggregate annualized subscription contract value as of that date from those customers that were also customers as of the date 12 months prior, divided by the aggregate annualized subscription contract value from all customers as of the date 12 months prior.

When I did my original post on this, I didn’t even catch it.  But therein lies the subtle head of survivor bias.

# # #

Disclaimers:

  • I have not tracked the Hortonworks in the meantime so I don’t know if they still report this metric, at what frequency, how they currently calculate it, etc.
  • To the extent that “everyone calculates it this way” is true, then companies might report it this way for comparability, but people should be aware of the bias.  One approach is to create a present back-looking and a past forward-looking metric and show both.
  • See my FAQ for additional disclaimers, including that I am not a financial analyst and do not make recommendations on stocks.

Joining the Granular Board of Directors

I’m very happy to say that I’ve joined the Board of Directors of Granular.  In this post, I’ll provide some commentary that goes beyond the formal announcement.

I think all CEOs should sit on boards because it makes you a better CEO.  You get take remove the blinders that come from your own (generally all-consuming) company, you build the network of people you can rely upon for answering typical CEO questions, and most importantly, you get to turn the tables and better understand how things might look when seen from the board perspective of your own company.

Let’s share a bit about Granular.

  • Granular is a cloud computing company, specifically a vertical SaaS company, aimed at improving the efficiency of farms.
  • They have a world-class team with the usual assortment of highly intelligent overachievers and with an unusual number of physicists on the executive team, which is always a good thing in a big data company.  (While you might think data scientists are computer science or stats majors, a large number of them seem to come from physics.)

To get a sense of the team’s DNA, here’s a word cloud of the leadership page.

wordle 2

Finally, let’s share a bit about why I decided to join the board.

  • As mentioned, they have a world-class team and I love working with supersmart people.
  • I like vertical strategies.  At MarkLogic, we built the company using a highly vertical strategy.  At Versant, a decade earlier, we turned the company around with a vertical strategy.  At BusinessObjects, while we grew to $1B largely horizontally, as we began to hit scale we used verticals as “+1” kickers to sustain growth.  As a marketeer by trade, I love getting into the mind of and focusing on the needs of the customer, and verticals are a great way to do that.
  • I love the transformational power of the cloud. (Wait, do I sound like too much like @Benioff?)  While cloud computing has many benefits, one of my favorites is that the cloud can bring software to markets and businesses where the technology was previously inaccessible.  This is particularly true with farming, which is a remote, fragmented, and “non-sexy” industry by Silicon Valley standards.
  • I like their angle.  While a lot of farming technology thus far has been focused on precision ag, Granular is taking more of financial and operations platform approach that is a layer up the stack.  Granular helps farmers make better operational decisions (e.g., which field to harvest when), tracks those decisions, and then as a by-product produces a bevy of data that can be used for big data analysis.
  • I love their opportunity.  Not only is this a huge, untapped market, but there is a two-fer opportunity:  [1] a software service that helps automate operations and [2] an information service opportunity derived from the collected big data.
  • Social good.  The best part is that all these amazing people and great technology comes packaged with a built-in social good.  Helping farmers be more productive not only helps feed the world but helps us maximize planetary resource efficiency in so doing.

I thank the Granular team for taking me on the board, and look forward to a bright, transformational future.