Exit Numbers – $100M is rarer than you think

Fred Wilson put up a post today that grabbed a slide from a recent presentation Mark Suster gave at a Founder Showcase event. The chart (and Fred’s post) back up with numbers the qualitative argument I was making in my recent post on Pattern Recognition (I wish I had these data when I wrote my original post!).

In my post I argued that while there is plenty of talk about a handful of high flying companies (Zynga, Twitter, Facebook, etc.) that vast majority of venture back companies can expect significantly more modest outcomes. In fact history suggests that a majority won’t even return invested capital to investors. All this talk about the stratospheric valuations of this small group of companies however has investors fundamentally misjudging the chance that their latest investment will do the same. As the chart from Mark’s presentation clearly shows, not only is it the extreme exception for a company to hit the kind of valuations that are getting all of the press attention but even hitting the $100M mark is rare. On some level I think we all know this, but seeing the numbers in black and white really puts a exclamation point on exactly how rare it is. And as Fred points out (as did I in my prior post), investing in early stage companies at the kind of valuations that are prevailing today is a losing bet…

  • Seth – great post – and even more evidence (from some *really* surprising nameplates) in this WSJ article from 2009: u00a0http://on.wsj.com/klGHH0nnThe kewlest part of the WSJ Article? u00a0The use of Tableau Software where theyu00a0analyzed the financial statementsu00a0of 100 of the largest (by market capitalization) publicly traded software companies. It then adjusted the sales numbers for inflation to compare the performance of these companies across more than three decades. u00a0nnTheir point was slightly different (how long it takes to get to $100M in sales) – but highlights the timeline it takes for many *very* successful companies to achieve that milestone the old fashioned way – by earning it.

    • Dan – I can’t tell you how many times I’ve had this conversations withrncompanies that come in and pitch to us (especially enterprise softwarerncompanies). A few times I’ve asked something like “those are pretty robustrnprojections. how many years do you think it took PeopleSoft to reach $20M inrnrevenue (answer is 5 years)? what are you doing to be 2x as successful asrnthey were?”. We love to talk about the flash in the pan businesses that growrnrevenue (and valuation) extremely quickly. While they do exist they’re thernexception, not the rule.

  • Thanks for sharing Seth :)nnIn addition i heard anu00a0analysisu00a0that there are manyu00a0companiesu00a0who sell u00b1$20m, and decide/ don’t have the Board backup to growu00a0to a $100m company…nnThis analysis are very important for us to read, as it show us the REAL stats … and with good stats good decisions can be made :)nnThanks,nSharel

    • I’d love to see that analysis Sharel. While I’m sure there’s some amount ofrntruth in that statement, I’d suspect that most of it is bluster (and byrn”support” they also mean another $20M in capital!). Like you say, however,rnseeing the numbers in black and white is pretty important.

      • Indeed… this analysis really help us to see the real picture.. and better plan for the futre… e.g maybe its time to prepare youru00a0businessu00a0Moat.. as it seem we are headed for another bubble :)nnThanks for theu00a0personalu00a0reply, i have been reading your and Brad blog for a while and learn a lot from it.nn10x,nSharel

  • Sunil Wadhwa

    Great stuff! Now you don’t need a research analyst to drum up the data, and can finally write that Freakonomics chapter I was talking about … j/k :)n

  • +1 on ‘seeing the numbers in black and white’.u00a0 It’s always magical to me how much better our intuition becomes when used in the context of good data well presented.u00a0

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