Open Source Business Models, Revisited

Posted on June 19, 2011 | 7 comments

I had breakfast the other day with Mike Olson, CEO of Hadoop ecosystem leader, Cloudera.  We met because we run in similar circles in data management land and because Mike had some quibbles with my post, The Open Source Software Paradox.

My premise was that open source presents a fundamental paradox:   the larger the community, the better the software, and the less people need to buy support for it.  Thus, that open source market opportunities were inherently flawed / paradoxical because you could only sell services for projects  that were not terribly successful.  Simply put,

You can have a large community who doesn’t need to buy from you or a small community who does.

I think Mike’s overall take on my post was “1990s thinking” because things have evolved over the past decade and businesses now try to monetize open source opportunities in more sophisticated ways.  This approach doesn’t actually contradict the paradox I observed, but instead looks  for more creative ways around it.

Another key point Mike made was that open source is not a business model.  I agree.  Open source is a way of developing software.  There are many different possible business models for monetizing open source projects.

Rather than attempt to replay the back-and-forth of our discussion, I will simply list my revised take on the 4 basic open source business models.

  • Professional services.  The most basic way to make money around an open source project is to offer related consulting (and training) services.  For example, ThinkBigAnalytics, seems to  building a consulting business around Hadoop and NoSQL databases (most of which are also open source).
  • Dual licensing.  A vendor offers (1) a free version under the GPL license which freely enables internal use but contaminates on redistribution and (2) a paid version under a different license that doesn’t include GPL’s copyleft provisions.  This model reeks of the vig as you force people under threat (of open sourcing their system) if they don’t move to the non-GPL version.  In addition, since SaaS or cloud services use but don’t redistribute software, this approach loses its teeth in the SaaS / cloud world.
  • Open core.  A vendor promotes an open source version of a system and makes money by extending it with proprietary additions.  In this model, the vendor “has some IP” and is not totally dependent on support subscriptions which may or may not be renewed.  Cloudera is executing this strategy by offering both (1) the Cloudera Distribution on an Apache license as well as (2) Cloudera Enterprise which is built on the Cloudera Distribution but also includes production support and management applications.

The open core model clearly sidesteps the paradox I’d outlined because open core vendors offer more than support.  Open core is a freemium business model and possesses all the strengths and suffers from all the weaknesses of other freemium models.

  • First, can you build a large community on the free version or service?
  • Second, through what mechanism and at what cost you monetize members of that community to a higher-level service?
  • Third, once monetized at what rate can you keep premium members renewing the premium service or moving them up to an even higher service level?

LinkedIn has done freemium spectacularly well.  I’ve never paid them a dime (as a free service user) but somebody paid them the ~$250M they made in the first 9 months of the year.  (Turns out it’s about 33% each of premium subscriptions, hiring solutions, and marketing solutions.)

The newspapers still haven’t figured out freemium though FT and The New York Times are making headway.

How will open core play out for open source vendors?  I don’t know.  I do know the freemium code is hard to crack.  I do know that freemium models are constantly evolving.  I do believe that freemium is a better business model than simply offering support or services.  And with the  IPO window opening, I do believe we may get a chance to see the financials of a few open core companies in the coming years.

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Posted in Open Source

Interest Misalignments in Silicon Valley Startups

Posted on June 8, 2011 | 19 comments

Everyone’s aligned in a Silicon Valley startup, right?  Give everyone some options so everyone has skin in the game and then everyone wants what’s best for the share price:  one for all and all for one!

Not so fast.

In this post, inspired by a chat with longtime serial entrepreneur Ken Ross, I’ll delve into what I see as the common alignment issues in Silicon Valley startups.  While I am a big believer in broad employee share ownership, one shouldn’t make the mistake of believing that simply because everyone has shares that they are automatically and permanently aligned.

In my estimation, there are four drivers of potential misalignment.

  • Portfolio theory
  • Shareholdings and net worth
  • The “exit” concept
  • Irrational considerations

Portfolio Theory

The most common cause of misalignment is driven by portfolio theory.  VCs typically invest in 10-15 companies and work in partnerships of 5-10 partners.  Thus a VC might get “carry” (i.e., a slice of the investment profits) on 50-80 companies.  A friend once calculated that a VC gets the equivalent of a VP-level (or better) equity stake in each of the portfolio’s companies.

Entrepreneurs and executives, however, have but one life to give and must work at one company at a time.

Divergence can result when VCs want to take more risk than founders and executives because they have placed 80 bets while the executives have placed one.  This can manifest itself in pushing for overly aggressive operating plans or declining “base hit” acquisition offers in favor of “swinging for the fences” each time.   Time can compound this divergence as accumulated sweat equity tends to make the founders and executives more conservative over time.  (Think:  “I have 8 years of my life in this thing, we can’t take that risk.”)

In addition, VC is increasingly a “hits business” – i.e., a fund that delivered an IRR of 35% might deliver only 15% excluding its top two investments.  Thus, VCs are generally more afraid of selling too early than too late.  While founders often tell tales of VCs declining early acquisition offers that could have earned them a quick $20M, VCs might tell the tale of VMware, which sold for $625M in 2004 and is now worth $41B.

Portfolio theory has other effects that are more subtle.  You might think of a given venture-backed company as in one portfolio.  In reality, the company is in numerous “portfolios” at different levels:

  • The fund level.  The expectations for a company become a function of the performance of the other companies in the fund.  If they are performing poorly, pressure may increase to deliver a big result.  Alternatively, if the fund is old, has lackluster performance, and the VC firm has subsequently launched several high-performing funds, a lack of interest may develop.
  • The partnership level.  Different VC firms set have different investment objectives and reputations.  Some want to quietly deliver great returns.  Some favor operating guys as partners, other favor financial types.  Some like seeing their name in the press; some don’t.    As a general rule, the more early-stage and the more big-name the partnership, the more they will want portfolio companies to swing for the fences across the entire portfolio.
  • The partner level.  Each partner in a fund has his own set of companies.  VC partners track each other’s performance closely and a partner’s fate over time is, in large part, determined by his investment performance.  In addition, since most VC firms are fairly stove-piped, expectations for a given company are probably more shaped by its partner’s portfolio than any other.  Factors that influence the partner’s motivations include the performance his portfolio, his existing status in the firm (e.g., venture partner looking for a big-hit to make general partner, or established leader in the firm, or in-trouble and need of a big-hit to stay in the game), and his future plans (e.g., retirement).
  • The partnership-partnership level.  Suppose early-stage VC firm 1 does a lot of business with late-stage VC firm 3, as is often the case.  You can then think of your company in the “intersection” portfolio between these two partnerships.   Why does this matter?  To the extent that VC3 is dependent on VC1, they may make decisions that optimize the VC1/VC3 relationship over those that they might think best for a given portfolio company.  (Think:  “if Bob ever wants to work with us again, he’d better go along with us on this decision.”)

Shareholdings and Net Worth

The size of someone’s position, particularly relative to net worth, can cause a divergence of interests.  Consider a hypothetical company with 25M shares:

  • The founder owns 5M shares.
  • The total employee option pool is 5M shares.  (Of which Joe Engineer has 20K shares.)
  • VC1 owns 10M shares, having paid an average of $1.60/share across two rounds.
  • VC2 owns 5M shares, having paid $3.00/share in leading the second round.

Let’s consider a proposed $6.00/share offer for this company, for a total exit of $150M.

  • The founder would make $30M and be set for life.  He votes yes.
  • VC1 would receive $60M which does not move the needle relative to the size of his $600M fund.  On a return basis, he makes 3.75x, a poor result for an early-stage VC.  He votes no.
  • VC2 would receive $30M which moves his needle even less.  He makes a 2.0x return, low for a late-stage investor.  He votes no.
  • Neither VC partner will gain any bragging rights because the exit is small in an absolute sense.   This confirms their no votes.
  • Joe Engineer would get $120K pretax or about $60K post-tax.  He can buy nice car, but he still can’t touch a Silicon Valley house.  Joe doesn’t get a vote, but if he did, he’d vote no, too.

The interesting thing here is that Joe Engineer is much more aligned with Winston the VC than he is with the company’s founders and executives.  Joe would vote no for two reasons:  first, $60K after tax doesn’t move the needle for him and odds are (since he chose to work at the startup), Joe is a true believer in the technology and thus thinks of this deal as sell-out.  Amazingly, Winston votes no for the same reason:  $60M doesn’t do much for his fund and he also sees the deal as a sell-out.

Now, the founder would have made $30M and, using typical ratios, the CEO would have made $7.5M, and the key VPs somewhere between $1.5M and $3.0M.   In most cases, they would all vote yes.  (But in reality only the founder and CEO are on the board and actually get a vote.)

The scenario changes dramatically if the founder is already rich.  Imagine the founder made $100M on his previous startup.  Now, a $30M exit is uninteresting because it results in neither a lifestyle upgrade nor a status change.  Now, the founder aligns with Winston and Joe in voting against the deal.  You can analyze the CEO’s vote in a similar fashion.

The “Exit” Concept

Managers want to build great companies; VCs want great exits.

Unfortunately, building a great company is neither a necessary nor sufficient condition to enable a great exit.  At only 3 years old, Bebo sold to AOL for $850M.  A spectacular exit, no doubt, but a little more than 2 years later AOL sold it for less than $10M.  A great company?  Certainly not.  YouTube, while infinitely more ubiquitous, barely makes money but was sold to Google at 18 months old for $1.65B.  A great exit?  Yes — goosebumps quality even.  Did they even have the time to build a great company?  Not really.

The best managers tend not to focus on great exits.  They focus on building great companies.  In fact, the “IPO as exit” is almost purely a VC notion.  In reality, an IPO is almost certainly not an exit for the CEO; he or she is de facto bound to the company for at least the next several years and his/her ability to sell shares is highly restricted.

I have always believed that IPOs are like high-school graduations – they are a beginning, not an end.  Godfrey Sullivan, CEO of the red-hot company Splunk, seems to feel similarly, saying “we consider an IPO the 3rd mile of a marathon. The IPO is an early milepost, not the destination.”

In the best-case scenarios, building a great company will indeed lead to an IPO which will be yet another milestone in a long journey of success.  But this is not always the case.  I’ve seen companies (e.g., Versant back in the day) twist into pretzels to make it through the IPO window and provide a reasonable exit for the investors only to end up living-dead zombies thereafter.

Now, I have not found the particular VCs with whom I have worked over the past 20 years particularly exit-focused.  Most are surprisingly patient and indeed want to focus on building great companies.  But, you cannot ignore the possibility of divergence when some of the passengers can exit the bus reasonably quickly post-IPO while others cannot.

The terminology “exit” reflects this pretty clearly.  For employees, customers, staff, and executives, the IPO is not an exit.  Nor, for that matter, are most acquisitions.  Founders, key executives, and key staff are often locked in (through various mechanisms) for 1-3 years after a deal closes.

Irrational Considerations

As humans, we must recognize that we do not always act rationally.  Behavioral economics reminds us that we are subject to a bevy of rules and heuristics that can cause us to make sub-optimal decisions.

Some decisions that appear irrational are rationally motivated  — but by either an unknown personal or non-shared goal.  Others actually are just plain irrational.  For example:

  • Anchoring:  I need to make $50M.  (Because I decided that I need to make $50M.)
  • Benchmarking:  I need to make $50M.  (Because my roommate at Stanford made $50M and I’m smarter than he is.)
  • Fame-seeking:   I need to be famous and will take increasingly risky bets in order to achieve that.  (Arguably this is a rational decision derived from a non-shared goal, but if you are on the board of a company you have a duty to its shareholders so I’d argue it’s irrational from that perspective.)
  • Dreaming:   This technology is going to change the world, despite much evidence to support that contention.  (Because I made it and it’s really cool.)
  • One-more go:  I will take increasingly risky bets because I’m retiring soon and this is my last chance to get one more for my legacy.  Shoot the moon.

The trick here is most founders are, by definition, a little crazy.  The confidence and zeal it takes to quit one’s job, develop a product idea, start a company, and raise venture capital is well beyond that of the average “reasonable” person.  Thus, it can be hard for founders to know when to stop pressing bets.  The same traits that enabled them to be successful as founders present a risk they overplay their hands, and destroy shareholder value in the process, in the long term.

Conclusion

In this post, I’ve tried to highlight some of the common sources of potential misalignment between the various shareholders of a startup enterprise:  founders, venture capitalists, CEOs, executives and rank-and-file staff.  Hopefully, I’ve demonstrated that things aren’t as simple as they might appear and that just because everyone might own shares, doesn’t mean they have aligned goals and motivations.

If you think I’ve missed any good examples, please let me know.

19 Comments

Posted in Management, Strategy, Uncategorized, VC

A Fun Taxonomy of Technology Executives

Posted on May 19, 2011 | 12 comments

Building on on a post by 10gen’s Max Schireson which in turn built on a post by me, I thought I’d have some fun by playing with and enhancing Max’s taxonomy of technology senior executives.

Max’s theory is that a surprisingly number of executives have “just one play” in their business playbooks which fall into a number of categories.  Building on Max’s grouping, and based on my 20+ years in business, here is mine:

  • The Band Leader.  They get the old band back together from a prior company.  Band leaders are often surprisingly hands-off managers who swear by their teams and travel with them from gig to gig.  They often alienate existing employees, viewing themselves as “professionals” compared to the regime they are replacing.  These types are effective to the extent that the band’s capabilities are aligned with the company’s needs.
  • Joe Process.  Joe’s never met a problem that can’t be solved with process.  Consultants, methodologies, training, flowcharts, and stoplight-based performance dashboards appear from the woodwork.  Joe is effective to the extent that lack of process is a company’s problem.  In Joe’s world, by the way, that includes everything:  even a strategy problem is a process problem (“we just need a good strategy process”).  What Joe fails to grasp is that knowing how to do things is different from knowing what to do.
  • The Strategist.  Strategists focus on developing a deep understanding of the company’s current situation and then evaluating future scenarios based on it.  Good strategists are quantitative as well as qualitative in their analysis — paying attention not only to business and marketing strategies but also the resources required to execute them.  Bad strategists forget what I call “the strategy compiler” — i.e., for a given company in a given situation with a given set of resources and capabilities, is a chosen strategy executable?  A great strategy that’s only executable by some other  company is definitionally not a great strategy for yours.
  • The Cost Cutter.  Cost cutters love to take cost out of a business and spot potential inefficiencies everywhere.  They love scale economies, and eliminate anything that resembles rework with a passion, sometimes whether that rework represents valid customization or pure redundancy.   Beware when a cost cutter asks “what exactly do you do here?”
  • The Salesperson.  Born charmers, salespeople generally make a great first impression, appear sincere, and are unfailingly positive. They are power-centric, often political, and are sometimes more focused on ensuring they have the power to get things done than they are on ensuring that they are doing the right things.  Good salespeople are charismatic leaders who inspire their organizations.  Bad ones develop credibility problems if they cannot deliver against their own high expectations and if they deliver a series of expedient “in the moment” messages that are inconsistent over time.
  • The Headless Chicken.  In response to a reader comment, I’ve added this type.  Every so often, executives are “pattern matched” by boards/CEOs  into positions that are well beyond their capabilities.  When this happens, a headless chicken results — a person who is truly lost.  This becomes evident quickly to those immediately around the chicken and happily, is usually only a matter of time before those in charge see it as well.

Note that as skills, each of these is required in an effective executive.  Good CEOs, for example, need to understand strategy, eliminate waste, personally sell, build teams which leverage their networks, and define process.  It’s only when an executive becomes one dimensional — and all about one muscle — that it becomes a problem.

12 Comments

Posted in Management

The Open Source Software Paradox

Posted on May 10, 2011 | 11 comments

As a marketer, I’m a fan of open source software.   After all, if you can’t dislodge Microsoft from mid-range server operating systems, Microsoft Office from desktop productivity suites, or Oracle from relational databases — and doing so through traditional means is a virtual impossibility —  then blowing up the whole business model isn’t a bad start.  It’s creative and it cuts right to the core of the problem.

But as a business-person I am not.  When you play the role of market spoiler it’s much easier to be famous than rich.  For example, when MySQL was acquired by Sun in 2008 for $1.2B, MySQL was doing only about $65M in annual revenues.  While the revenue multiple on the exit was spectacular, their capture rate was not:  MySQL disrupted literally billions in “big three” (i.e., Oracle, DB2, SQL Server) database revenues.  But if your value proposition is rooted in “almost free relative to leading commercial alternatives,” then you won’t succeed at 50% of their cost; you’ll need to be more like 2-5%.

I refer to open source as both a development model —  i.e., a way of building software — and a business model.  While the former is more well defined than the latter, the typical way to make money in open source is through selling subscriptions or licenses to certified and more-quickly-patched releases as well as selling technical support and/or consulting services to go with them.

While a spectacular exit multiple may occasionally pay off big time for shareholders (e.g., JBoss, MySQL), my theory is that in general it’s very hard to make money with the open source business model.  Red Hat is the obvious exception, and we’ll talk about them in a minute.

The basic paradox of open source is this:

  • The smaller the community the worse the software quality and the more people need certified releases and support.
  • The bigger the community the higher quality the software and the less people need certified releases and support (i.e., the community version will do).

So you can have a large community who doesn’t need to buy from you or a small community who does.

Two other drivers complete the picture:

  • The nature of the software and to what extent it truly requires an almost-daily stream of patches and updates and …
  • The monetization rate which is a function of the commercial market structure.  For example, the lower-level the software (e.g., operating systems) the more the market tends towards natural monopoly as customers want to minimize entropy at the bottom of the stack.  This should drive high pricing/margins on the commercial side of the market, and a parallel opportunity for someone to establish clear leadership on the open source side.

This is why Red Hat does so well when most others end up stagnating in the tens-of-millions of revenues range. The market is huge.  The software is low-level and thus the market “wants” a clear leader (think:  increasing returns) who can provide a hardware-independent, low-cost, supported product as an alternative to the proprietary Unix-es of days past.

Put differently, the bigger the commercial market and the more monopolistic its structure, the better the open source opportunity.  Conversely, the smaller the commercial market and the more fragmented leadership is within it (e.g., enterprise search, document management, and to some extent BI), the worse the open source opportunity.

11 Comments

Posted in Open Source, Strategy, Uncategorized

If We Can’t Have Repeatable Success, Can We At Least Have Repeatable Failure?

Posted on April 27, 2011 | 7 comments

I’ve always found business to have a fair amount of accidental, built-in hubris, largely resulting from the strategy formulation process.  I remember one time at Business Objects we had a strategy offsite where, in our infinite wisdom and with a fair bit of groupthink, we came up with the idea for a BI workflow solution, which we dubbed Sundance for the name of the lovely venue at which it was conceived.

I remember coming home from the offsite and having a conversation akin to the following:

Me:  What if Sundance doesn’t work?

Exec:  What do you mean, “doesn’t work?”

Me:  Well, for example, what if nobody wants to buy it?

Exec:  What do you mean, what if nobody wants want to buy it!?  It’s strategic.  We can put incentives in the salesforce compensation plans and bundle it.  Don’t worry, we can sell it.

Me:  I didn’t say what if no one wants to sell it.  I said what if no one wants to buy it.

Exec:  But, it’s strategic.  We decided it at the offsite.  You’re talking crazy Dave.  Come have another beer.

As a marketer by background, I tend to view most everything as an experiment.  That is the nature of marketing.  You never know what’s going to work.  You can try different things.  You can measure them.  You can see what works and what does not.  You can even try to build explanations for why certain things work and certain things don’t.  But you are trained to approach business with humility and with an experimental spirit.

Exec:  Look.  Sundance is not an experiment.  We can’t tell Wall Street it’s an experiment.  We need to tell them it’s the future of the company.

Me:  But what if it isn’t?  What if we’re wrong?  Heck, it’s not a bad idea, but we dreamed it up in two hours on a white board.

The problem is that things fail all the time in business.   Products fail.  Startups fail.  Business models fail.  Heck, Sundance failed.  And the bigger problem is that when we dismiss the possibility of failure in our planning, we dismiss the possibility of learning along with it.

Yes, business — and particularly so in startup-up land — is the quest for finding a repeatable, scaleable model.  (Why?  So you can “just add water” and create an arbitrarily large business — and valuation to go with it.)  But quite often in the hurry for repeatable success, managers fail to design things scientifically so they actually have some degree of repeatability and can thus learn from either success or failure.

Example:  you take a new product and put it in the hands of 8 different salespeople (all of whom are “world-class” as defined by the VP of sales) with 8 different backgrounds in 8 different cities selling to numerous types of different target customers with a variety of different sales pitches.  Consider these scenarios:

  • Everybody sells.  Buy more stock quick.  Anyone can sell this stuff to anybody saying pretty much anything.  (Hint:  this does not happen very often.)
  • Some sell and some don’t.  This is tricky.  Did the folks who sold sell because of their background, their territory, the target customer, their approach, or their salespitch?  Well, we don’t know.  We can look for patterns but we haven’t designed the experiment to make things easy.  The quick assumption is that the folks who sold did everything right and the folks who didn’t did everything wrong, but if you think about it, you can’t assume that’s the case.  Did we have a great salesperson in Chicago pitching the wrong message?  The guy in DC who sold a lot carries a rabbit’s foot — should we dispatch rabbit’s feet instantly to the whole salesforce?  After firing the VP of sales, we learn that “world-class” actually meant “I liked him/her” and can find virtually no additional common traits among the salesforce.  Hum.
  • Nobody sells.  This is hard, too.  Was everybody doing everything wrong?  Unlikely.  Yet, no one came together with the right combination to sell.  But are we sure the lady in Chicago is a bad salesperson?  Can we be sure that the pitch they’re using in DC doesn’t work?  Can we be certain that there is “no market” for the product as the VP of sales is insisting?  What can we learn from such a random experiment?  The answer is nothing.

Thus, my statement:  if we can’t have repeatable success, then can we at least have repeatable failure?

If instead of hiring 8 salespeople, we hired only 3,  put them all in NYC, and called only on the same handful of titles within investment banks using the same sales presentation and demo, could we have learned more?   Yes.

  • If it works, it’s great news, because you know exactly what to go scale.
  • If it doesn’t work, it’s still good news (perhaps for your successor) because you can, with a pretty high degree of certainty, conclude that mix of levers tried will not work.  Or, in the spirit of Thomas Edison, you’ve learned one more way not to make a light bulb.

I’ve picked two extreme cases and there certainly is middle ground in between, but the two key questions are:

  • Are we assuming only successful outcomes in our planning?
  • Are we designing things as an experiment from which we can learn no matter the outcome?

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Posted in Management, Marketing, Strategy