Category Archives: startups

Highlights from the Fenwick & West 2Q11 Venture Capital Survey

Each quarter the legal eagles at Fenwick & West run a great survey on the state of venture capital and write a brief report that rounds-up data from other sources and publishes their survey results.  Here are some quick highlights from the 2Q11 venture capital survey:

  • Total VC investment was $8.0B, a 20% increase compared to the $6.4B invested in 1Q11 per VentureSource.  Of this, $2.9B was invested in Silicon Valley.
  • 14 venture-backed companies went public in 2Q11, raising $1.7B.  In 1Q11 11 companies went public raising $700M, per VentureSource.
  • Venture capitalists raised $2.7B in funding in 2Q11, a 65% decline relative to the $7.6B raised in 1Q11, per Thompson/NCVA.
  • The Silicon Valley Venture Capitalist Confidence Index dropped to 3.66 out of 5.0, a sharp drop from the 3.91 recorded in 1Q11.  I added the red line to chart below which seems to indicate that confidence is about average since 1Q04.

  • 19% of financing rounds were series A, about normal for the past two years, somewhat contradicting the analysis in this recent TechCrunch story, The Series A Squeeze.  (Though it’s unclear how Fenwick handles seed fundings in their study.)
  • 61% of financing rounds were up-rounds, 14% were flat, and 25% were down.
  • The Fenwick & West VC Barometer, a measure of per-share pricing, was up 71%, with the software sector leading the way at 123% and internet / digital media at 115%.
  • 37% of rounds included senior liquidation preferences and, of those, 29% were multiple liquidation preferences.
  • 38% of rounds had participating preferences.
The full survey is available here.

Startups are Hard, Really Hard: Ergo Seek Mentors and Allies

A friend forwarded me a link to this presentation — So You Wanna Do A Startup, Eh?  I liked it so much, I thought I’d do quick post with some brief commentary.

Highlights:

  • Slide 30:  ”Seek Mentors and Allies.  This is the most important point I make in this entire presentation.”  Why it’s listed as bullet 5 on slide 30 is beyond me, but it is nevertheless a key point.  I’m doing some startup advisory work of l ate and I certainly believe that some friends with experience, wisdom, and connections can go a long way towards helping a new venture head down the right path and avoid some obvious mistakes.
  • Slide 11:  Five myths about startups, particularly myth 2 (the average tech startup founder is a 25 year old Ivy league dropout) and myth 5 (location doesn’t matter)
  • Slide 30:  Ask rejectors for feedback.  Critical.
  • Slide 36:  Too funny!
  • Slide 40:  I love the Venn diagram and also note that the delusional aspect that enables founders to do the impossible in starting companies can lead to problems later on.

Thoughts on the Qlik Technologies (QlikTech) IPO

I spent an hour or so browsing the QlikTech S-1 and thought I’d share some observations.  (See here for my prior post on the company.)

  • The company has achieved good scale (2009 revenues of $157M) but growth has been decelerating from 82% in 2007 to 47% in 2008 to 33% in 2009.
  • Gross margins are high at 89% due largely to normal margins on license (96%), unusually  high margins on support (96%), normal margins on consulting (27%), and a fairly small consulting business (10% of total revenues) which reduces the pull-down effect on the weighted average.  Wall Street will like this.
  • Sales and marketing expense is high at 59% of sales.  Provided switching costs are high, you can argue this is a good investment, and provided growth is high, you can justify it.   I’m going to assume they make some “lost year” arguments about 2009 in their story and will guide to re-accelerated growth, but I’m not sure.  If not, then they will get pressure about the inefficiency of their sales model.
  • R&D is spectacularly low at 6% of sales.  There is an argument that if you have a largely completed (cheap and cheerful) BI tool that you should simply go sell the heck out of it and not artificially spend money in R&D when you have neither the vision nor the immediate need to either create new products or investment big money in enhancing your existing one.  I’ve just seen few companies try to make it.  I suspect Wall St. will pressure them to increase this number, regardless of whether it’s the strategically right thing to do for the company.
  • Expanded customer base from 1,500 customers in 2005 to over 13,000 in 2009.
  • I like their argument that because it’s easier to use than traditional BI tools that it should get greater penetration than the average 28% of potential BI users cited by IDC.
  • The unique business model (free downloads and 30-day guarantee post purchase) are consistent with the cheap and cheerful product positioning, which is good.  It does beg the question why sales costs so much, however, if you’re primarily upselling downloaders in a low-commitment fashion.
  • I think the claim “analysis tools are not designed for business users” is over-stated.  I can assure you that at BusinessObjects we were designing products for business users.
  • I dislike the small piece of huge pie argument, but I suppose that particular fallacy is so embedded in human nature that it will never go away.  I’d rather hear that QlikTech thinks its 2010 potential market is $400M and it wants 50% than hear – as it says in the prospectus — that they think it’s $8.6B and they presumably want somewhere around 2%.
  • They expect 63M shares outstanding after the offering, implying that if they want a $10-$15 share price that they think the company can justify a market cap in the $750M to $1B range.  If it were generating more than a 4% return on sales and growing faster than 33% that would be easier to assume.
  • 50% of 2009 license and FYM came from indirect channels.  This again begs the question why sales cost so much; indirect channels are, in theory, more cost-effective than direct.
  • They had 124 “dedicated direct sales professionals” as of 12/31/09, which suggests to me that at an average productivity of $1.8M (including all ramping and turnover effects) they could do $223M in revenues in 2010, or growth in the 40% range.  So they seem well teed-up from a sales hiring perspective.
  • If my US readers are wondering why you’ve not heard of them, it’s because they were originally founded in Sweden and do 77% of revenues “internationally” (which now means outside the US given that they moved their headquarters in 2004).   This relative lack of US presence should presumably hurt the stock.
  • They have a pretty traditional enterprise software business model:  perpetual license and maintenance.  They even state potential demand for SaaS BI as a risk factor.
  • They had $35M in deferred revenue on the balance sheet as of 12/31/09.  This strikes me as high; some quick back-of-the-envelope calculations led me to expect ~$25M if it was all the undelivered portion of pre-paid, single-year maintenance contracts.
  • Per IDC, 44% of QlikView customers deploy within a month and 77% deploy within three months.  It sounds impressive and is consistent with the small consulting business.  But it also depends on the definition of deploy.
  • This is no overnight success story; the company was founded in Sweden in 1993.  There was a six-year product development phase (which perhaps explains the low R&D today) from 1993 to 1999.  From 1999 to 2004 they sold almost exclusively in Europe.  From 2004, they added USA sales and relocated the HQ to Pennsylvania.
  • 2009 maintenance renewal rate of 85%
  • They intend to increase R&D expenses to increase in both absolute dollars and as a percent of sales going forward.
  • 73% of revenues are not dollar denominated.  This means that foreign exchange rates should hit them more (both ways) than for a typical software company.
  • This sounds typical:

Our quarterly results reflect seasonality in the sale of our products and services. Historically, a pattern of increased license sales in the fourth quarter has positively impacted sales activity in that period which can make it difficult to achieve sequential revenue growth in the first quarter. Similarly, our gross margins and operating income have been affected by these historical trends because the majority of our expenses are relatively fixed in the near-term.

  • USA revenues grew at 28% in 2009, a bit slower than company overall. Fairly surprising, given the late USA start and the presumably huge market opportunity.
  • R&D remains in Lund, Sweden with 54 staff as of 12/31/09.
  • 574 total employees as of 12/31/09 with 148 in the USA and 426 outside.
  • Accel is the biggest shareholder with 26.7% of the stock, pre-offering.
  • The proposed ticker symbol is QLIK
  • My brain started to melt around page 120.  (Somehow the document set I managed to pull down from the SEC site is about1,000 pages and includes a zillion appendices.  The regular S-1 is here.)
  • Click on the image below to blow up their recent financials.

Five Rules for Competing with Giants

I’ve spent my career competing, for the most part successfully, against companies from 10 to 1,000 times bigger than my own.  Thus, over the years, I’ve developed some rules that can help maximize your odds of success when competing against giants.

  • Concentrate force.  The easiest way to be bigger than your competitor is to focus.  While Oracle was around 100x our size when I joined Business Objects,  our BI team was bigger than theirs; in 1995, we had nearly 300 people who did nothing but BI.  Focus can be about either product or market.  At Mark Logic, I believe that Endeca is around 2-3x our overall size, but by my estimation Mark Logic is 3-4x bigger than they are in our core markets of media and government.  While Autonomy is more than 10x our overall size, I believe that we may be bigger  in media and government (for relevant use-cases), and I’m nearly positive that we’re bigger in the dead center of our markets:  STM in publishing and intelligence in government.  Focus is hard because there are always people who are more obsessed with the opportunities you’re not pursuing than with those you are, so have a clear sense of your growth goals, decide rationally if you can meet them with your chosen focus areas, and then jettison those who can’t get with the focus program.
  • Be the best.  I like to say that no sane person wants to buy software from a startup.  Most IT folks sleep much better at night buying from the mega-vendors, even if they feel like they’re getting gouged on price.  People buy from startups not because they want to, but because they have no choice.  How can you give people no choice but to buy from you?  Solve one problem better than anyone else in the world.  Those are easy words to say, but they’re very hard to do.  Ask yourself:  what is the one problem that we can really solve better than anyone else in the world.  That’s what the VC cliché “world class” means.  Most startups aren’t honest with themselves in this department; they tell themselves white lies about where they can realistically be the best.  The result is they overextend and end up with three or more mediocre products instead of one great one.  Sometimes this is driven by greed for more addressable market; sometimes it’s driven by fear and the desire for diversification.  Remember the Andrew Carnegie quote:  put all your eggs in one basket and then watch the basket.
  • Split pins.  Most technology strategists are familiar with Geoffrey Moore‘s “bowling alley” model which says that startups should view markets as bowling pins, using one market to knock down the next.  This model encourages startups to skip through markets hastily, like American travelers skipping through countries in Europe (e.g., If this is Tuesday, it must be Belgium).  Instead of skipping pins, startups should split pins.  Without sounding too cosmic:  look for micro-alleys within bowling pins.  When I started at Mark Logic, I thought “publishing” was a pin and that all publishers were basically the same.  When I focused on publishing and looked not just for similarities among publishers but also differences between them, I learned that STM, education, news, market research, credit/financial, legal, trade, and B2B publishers were all different.  I like to say that all beagles look the same unless, of course, you’re a beagle.  By splitting pins instead of skipping them, you learn more about your customer’s needs, can serve them better, and — best of all — typically discover that the market you were about to skip over is about 10-100x bigger than you originally thought.
  • Hire stars.  Giant-fighting startups are not places for the weak or mediocre.  You need a team of aggressive, high-energy people who understand the mission and are ready to make the sacrifices required to win.  High-growth startups are lousy places to learn on the job.  That’s why the VC model gives nice chunks of equity to experienced managers with safe jobs in big companies.  They want to lure them into the startup and compensate them for the risk in so doing.  In the end, VC’s are not risk takers; they are risk eliminators.  They try to isolate all risk to the fundamental innovation and do so by setting every other lever of the business to standard. (See Chris Dixon’s recent post, Don’t Be Creative About the Wrong Things, for more.)  That’s why you need to build an A-team and be sure the people on it are scaling with the company.  Rest assured, even if you’re not asking the “can they scale” question about your team, the board is asking it about you.
  • Work together.  I’ve seen too many startups with divisive, prima-donna-laden cultures where staff meetings devolve to finger-pointing contests.  “I was the top salesperson at SAP and I can’t sell this stuff unless it works.”  “Well, I was the smartest guy at Harvard and my technology is so wonderful that a monkey could sell it.”  On and on.  This doesn’t work.  When you’re competing with giants you need the extra advantage that comes from brilliant people — working together — to solve problems.  All of us, when working in a functional group, are indeed smarter than one of us.  It took years to get this lesson through my head.  I first got it doing an exercise at a leadership program where each individual rank-ordered a list of items required for wilderness survival.  Then we broke in about 8 groups of 6 and re-did the exercise.  The worst group score beat the best individual’s score, and one of the individuals was a Brigadier General in the US Army.  Years later I discovered The Wisdom of Crowds and learned it again.  While it may sound hokey, teamwork is an amplifier of talent.  That’s why All-Star teams don’t do well in sports:  while each individual may play superbly; they just don’t play together.

Veterans vs. Up-and-Comers in Startups

The conventional Silicon Valley /  venture capital (VC) wisdom is that startups should not bet on first-time managers in just about any position, but particularly at the executive team level.  It’s best captured by the statement:  a high-growth startup is not the place to learn how to do your job.

This is the conventional wisdom because, while counter-intuitive to some, VCs are not actually risk-takers, they are risk-isolators.  A typical VC is trying to isolate risk down to one thing:  the unique value proposition behind the startup.  Those value propositions can vary considerably:

  • Sometimes, it’s about the technology.  Mark Logic, for example, is a technology disruptor.
  • More in vogue these days, it’s about the business model.  Salesforce disrupted the on-premises, perpetual license business model with SaaSMySQL disrupted the traditional license model with open source.
  • Sometimes, it’s about both.  My friends at Clearwell will rent you an appliance that includes an innovative e-discovery application.

But the point is that VCs are trying to isolate risk down to the one key value proposition.  They do that by setting every other lever in the business to standard.  For example, per the conventional wisdom, a SaaS BI business model disruptor should:

  • Hire standard managers with experience in big BI companies, and use equity to lure them from their cozy jobs.
  • Develop a standard BI application/product that contains the features users expect.
  • Build a standard enterprise sales force, hiring salespeople from the established BI vendors
  • Implement a standard BI partnering strategy, with the usual suspect technology and systems integration partners
  • Devise a standard marketing strategy, typical of those used by other BI companies but with a key emphasis on the unique value proposition.

Like most VC wisdom, at the first order the approach makes a lot of sense.  At the second order, however, it presents some problems.

  • It encourages cronyism, where the first such experienced manager knows a whole clan of other folks who also are looking for jobs, often for the same reason he or she was (e.g., recent of acquisition by Oracle, a new CEO, a strategy shift).  While one of the benefits of hiring experienced managers is undoubtedly their networks, I’ve seen this work out both quite well and spectacularly badly.    The key issue boils down to whether you are hiring drivers or passengers.  Was the company from which you’re hiring successful because of these people, regardless of these people, or indeed in spite of them?  Are you hiring real results drivers or people who, Fooled by Randomness, have great resumes and think very highly of themselves, but who are incapable of solving your company’s problems?
  • This cronyism often creates a divisive environment that drives out your top existing talent.  As the “Company X” mafia takes over, they typically show insufficient respect for those who got the company where it is, ridicule some past practices, and talk boisterously how easy it’s going to be to fix all this.  While problems in operational practices are easy to spot and fix, this approach overlooks the startup’s need for process maturity (e.g., size relative to Company X) and the startup’s strategic position in its market.  I remember when the experienced (manufacturing-oriented) managers from ASK took over Ingres (then a ~$200M company) and decided that implementing a heavyweight quality process was the answer to our problems.  In reality, our problem was strategic:  in a land-grab market we’d made some poor technology choices (e.g., Quel vs. SQL) that hampered sales and we had been too conservative about grabbing land.  Just as the Ingres executive team’s only hammer was technology, the ASK executive team’s only hammer was process.  Neither, unfortunately, was called for given the company’s situation.
  • It limits career growth for talented up-and-comers within the company:  either individuals with management potential or existing managers with executive staff potential.  If every new management job will be filled by an experienced outsider, then insiders quickly feel trapped and unable to advance in their careers, making them — particularly the more ambitious ones — more likely to leave the company.

The answer to managing all this is, of course, balance.  Both the CEO and the executive team need to take some calculated risks in betting on up-and-comers in a number of posts.  This generally will cost the CEO some political capital (debited at promotion time and never credited back, even if the up-and-comer is highly successful), but will help him or her retain both institutional memory and some key people for the future of the company.

Having a stronger-than-usual preference for up-and-comers, I’ve developed a few rules for managing this process.

  • Always do a external search.  You can turn the dial on how hard — from a check-the-network or calling a few contingency recruiters all the way up to a retained search — but you should always expend energy to see “who’s out there” so you have a sense of the market in making the veteran vs. up-and-comer decision.  You owe this to yourself, your board, and your shareholders.
  • Run up-and-comers through the same process as the external candidates.  The only exception here is when you are restructuring in which case many people may be changing roles without following an interview process.
  • Keep a mental balance of how many up-and-comer chits you have used and how many you think you have left.  You need to view them as a scare resource, because they are.
  • Ensure the up-and-comer is “all in.”  If you are going to bet political capital on someone they can’t either be [1] telling you what you think you want to hear or [2] be unsure of whether they can do the job.  You should only bet on up-and-comers who are certain they can be successful, and so certain that they will probably quit in the not-too-distant future if not offered opportunities.
  • Limit up-and-comers’ ability to bet on other up-and-comers.  Force them to prove they merit their posts by demonstrating how they can bring in veterans.  This is a both a solid practice and a great test.  The worst outcome is that your up-and-comer hires no veterans for his team and you end up with a whole multi-level hierarchy of inexperienced people.  (I’ve seen this happen, too, though happily not in my department and it’s one heck of a mess because there is typically no organizational awareness that anything’s even wrong! )

10 Lessons from a Failed Startup

I found this great post on VentureBeat, 10 Lessons from a Failed Startup, where entrepreneur Mark Goldenson tells you the ten things he learned from his failed internet TV network for games, PlayCafe.

Here’s a summary of the ten things Mark learned:

  • Find quick money first
  • Content businesses suck (or, do it for love and expect to lose money)
  • Know when to value speed vs. stability
  • Set a dollar value on your time
  • Marketing requires constant expertise
  • Control and calculate user acquisition costs
  • Form partnerships early, even if informal
  • Plan costs conservative and err on the side of raising too much [money]
  • The key to negotiating is having options
  • Knowing isn’t enough

You can read the complete post here, which is passionate and full of first-hand, hard-earned wisdom.

Let’s hope Mark has better fortunes on his next try which, per the bio, is going to be an innovative venture in web health care. Good luck with it!

Built to IPO, Flip, or Last?

While it’s taken me a while to post on this Wall St Journal article, it’s still as relevant today as it was back in July. The article discusses the recent dearth of IPOs, arguing that the long-closed IPO window is changing the way startups think about themselves, they way venture capitalists think about startups, and threatening the great Silicon Valley venture-capital-driven innovation machine.

In a blog that generally offers more critique than praise, I’d simply say: I think the author’s right. Fewer startups run the gauntlet to IPO and I think that’s the result of three things:

  • The SOX “tax” – an estimated $2M-$3M annual nut – which all but wipes out the bottom line of what were previously IPO-ready companies and reduces market caps. Example: for a 50% growth company with a 1.0 PEG ratio, $3M in SOX expense wipes out $150M in market cap.
  • Lack of demand in the public markets. As mentioned here before, when you look the Software Equity Group’s IPO pipeline, you can impute that the IPO window is what I call 50/50/0 — i.e., $50M+ in TTM revenues, 50%+ growth, and 0% EBITDA. But, while that may be the window to make it potentially worth filing – make no mistake – the IPO market is currently closed.
  • Industry consolidation. The article surprisingly misses this point, but the software industry has sufficiently consolidated that plunking down $75M to buy a plateaued startup is nothing, and even paying $300M – $500M to buy someone on a roll is basically chump change. And, if you’re SAP, Oracle, Google, or Microsoft, even $1B isn’t much to buy your way out of a strategic headache – and heck – since goodwill is no longer amortized and they’re typically buying with stock and can cut enough costs to make the acquisitive instantly accretive, it’s effectively “free” anyway.

The last point sometimes makes me wonder if software will end up like pharma or biotech where it seems that big companies have effectively outsourced innovation to startups. The big guys are willing to pay big dollars for the few who succeed in order to avoid billions of R&D that it takes to find the winners. Simply put (and from quite a distance) it seems they’ve outsourced the financing of innovation to venture capitalists.

If I were at one of the big software oligopolists, I probably do the same thing. I’d watch ten startups, let 3 fail, let 3 fail into mediocrity and buy them for chump change, and pay 10x revenue for the one that went red hot. You win some, you lose some. And – even when you lose you win – because you are so much larger than your targets that you can let them grow to even $200M in revenues and still buy them without much pain.

That’s a new dynamic.

This prompts the question: is the next-generation of VC-backed startups built-to-flip instead of built-to-last? Frankly, I think the answer’s a mix.

Increasingly, I think web 2.0 startups that take relatively little capital are running a different formula than classical enterprise software vendors. The latter might raise $30M in VC, hoping to go public with a $500M market cap. The former might raise only $10M, hoping for a quick sale at $50M. This changes venture economics, but the system can still work.

Prior to Mark Logic, I’ve worked at only three software companies: Ingres, Versant, and Business Objects. All three were venture backed. All three went public. And all three went public – more or less – in the year in which they did $30M in revenues. My, how things have changed!

By contrast, let’s look at Endeca, a player in enterprise search who started out in e-commerce search, bringing OLAP-style dimensional navigation to the content world. Later, the company branched into more areas (seemingly too many if the recent stuff I’m reading about spend management, other apps, and a DBMS-like positioning is correct).

Per a recent 451 Group report Endeca did about $100M in revenues in 2007, growing 70% over 2006, with 500 staff, 500 customers, an average deal size of $350K and a 90/10 direct/indirect channel model. They’re silent on profitability, though they recently raised a $15M venture round bringing total investment to about $65M, suggesting they’re still burning cash. The numbers, with the exception of the unknown profitability and the high direct sales dependency (which are quite possibly linked), overall look pretty good.

But Endeca first talked about an IPO in 2006 and 2+ years later they’re still all dressed up with nowhere to go. Why? I’d guess it’s a combination of the IPO window closure and (perhaps) some process issues related to compliance, which these days are another leading cause of IPO stall-out and an indirect form of SOX tax.

Frankly, I think it’s too bad. While I want to crush Endeca in the relatively few deals in which we compete (and complement them in the relatively few where we do that as well), I nevertheless believe that Joe Investor should be able to buy their stock. By forcing the de facto IPO bar ever higher, the US is locking out individual investors from participating in early-stage technology companies. That’s not good.

Why’d we do it, then? Because of the excesses of the web bubble and the early 2000s, one says. But, when I think about that era, the problems fall into two distinct classes:

  • Investors awarding $1B valuations to startups with $5M in revenues. While I think this was ostensibly insane, it should nevertheless be permissible – no one forces you to buy a share of Beyond.com in 1999. No one forces an investor to participate in a speculative bubble. Some would argue they’re a normal market phenomenon. They shouldn’t be outlawed. Caveat emptor.
  • Fraud a la Enron. This needs to be wiped out. No question. (For an interesting perspective on Enron, read Open Secrets by Malcom Gladwell.)

Somehow, I think we mixed up the two different problems along the way by enacting laws that throw the early-stage baby out with the anti-fraud bathwater. The result is that individual investors are denied access to early-stage growth companies and, the Journal argues at least, that we are threatening the health of the Silicon Valley innovation machine.

Startup Zeitgeist

Seedcamp, a London-based, week-long camp for European entrepreneurs recently did an interesting exercise. They took the several hundred applications they received for their event and made tagclouds. Here’s what they found.

What are you creating?


How will you make money?


What tools will you use?

(I’d love to see XQuery in the toolset, but happy to see that database, server, and XML are already there.)

And who says you can’t do interesting analytics on content? I thought this was fascinating. Check out Seedcamp’s blog post about the exercise, here.