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Welcome To The Unicorn Club: Learning From Billion-Dollar Startups
- deleted 13y ago[deleted]
- yoloswag 13y agoAll that wankery to literally say nothing at the end of the article: "What does this all mean? For those aspiring to found, work at, or invest in future unicorns, it still means anything is possible". Oh gee? Anything is possible?! THANKS FOR LETTING ME KNOW! Sigh this is just more public startup masturbation as far as I'm concerned.
- jroseattle 13y ago"Few companies are the result of a successful pivot." I balance this statement against the notion of many incubators, whom I know/understand to focus heavily on the founding team more so than the idea. While the statement isn't damning in that respect, it does suggest that there's quite a bit more to success than just the people involved. Incubators aren't necessarily trying to fund the next billion-dollar idea, but I'm not sure the statement doesn't apply to all companies, regardless of exit valuation.
- lionheart 13y agoCouldn't Twitter be considered a pivot from Odeo?
- jroseattle 13y agoI'm not familiar enough with the history of Twitter and Odeo to say one way or the other.
- bpicolo 13y agoTwitter is just a new business, not a pivot.
- KaoruAoiShiho 13y agoPivots are a redefinition of a failed attempt. The part about how most of the companies are made by 30+ people who have worked together and most of them having had founder experience seems to indicate that they've had had failures in their past. It seems mostly a semantical issue to me. The impression I get is that pivots are neither a positive nor a negative indicator. It is neutral.
- jacques_chester 13y agoPivots are an attempt to internalise the market-fitting function inside the firm. Instead of failing at a company-bankruptcy level, the idea is to fail at a business-model level. However, company-bankruptcy is a much stronger signal, including to other companies and investors. Either way, the overall market-fitting function still resembles a kind of optimisation by simulated annealing -- local hill-climbing with a moderate degree of randomisation.
- melvinmt 13y agoInstagram was a pivot.
- unholiness 13y agoPeople starting their own startups are not likely to get anything useful out of this article. There is little to "learn", as the link-bait title suggests, from a statistical analysis of billion-dollar companies. There were, however, a few somewhat interesting takeaways amid the difficult-to-read mess: The average founding age is 34. 80% of founders have started a company before. Only 2 out of 39 have any female cofounders. The billion+ startups are pretty evenly split into free, freemium, paid, and enterprise only pay structures. Someone correct me if I'm wrong, but everyone I recognize on the list is a software-only company.
- imron 13y agoFrom the article: "We found 39 companies belong to what we call the “Unicorn Club” (by our definition, U.S.-based software companies started since 2003 and valued at over $1 billion by public or private market investors)." So yes, they are talking only about software companies.
- patmcguire 13y agoAverage founding age is something I wouldn't have been able to guess.
- hkmurakami 13y ago>Someone correct me if I'm wrong, but everyone I recognize on the list is a software-only company. Palo Alto Networks is a high security network infrastructure maker: https://www.paloaltonetworks.com/products/platforms/firewalls/pa-5000/overview.html https://www.paloaltonetworks.com/products/platforms/firewall...
- Nimi 13y agoMeraki sells devices, AFAIK. I have to kindly disagree with your opinion that there's nothing to learn here for aspiring entrepreneurs: one possibly actionable take-away seems to be "You haven't missed the train if you're 25, not even close. You still have time to learn, start a first company that probably won't take over the world, then try a second company."
- data_app 13y ago
- jquery 13y agoIt's missing several companies I can think of off the top of my head, including the one I work at.
- beambot 13y agoSuch as...? Enumerating would be more helpful.
- deleted 13y ago[deleted]
- jacques_chester 13y ago39 is a tiny sample, to be quite honest, especially since the selection doesn't include erstwhile competitors who failed. I've found studies of failures to be more illuminating. There are far more of them and you can draw more reliable conclusions as a result. Consider for example Billion Dollar Lessons by Carroll and Mui. They are able to demonstrate, from a large, methodologically-selected sample, that most of the B-school grand strategies of the 1980s were disastrous.
- mathattack 13y agoExactly. The problem with this sample is the same as In Search of Excellence - you can see what the good companies do, but what makes them unique? You can correct for it somewhat by adding comparison companies that failed, but the real thing to look for is very similar companies that had divergent choices at the same point in time, with everything being equal up until then. This is why VC and management is an art, not a science. :-)
- jacques_chester 13y ago> This is why VC and management is an art, not a science. :-) Granted, but that said, Tetlock showed that in at least one very messy problem domain (international geopolitics), embarrassingly simplistic linear models crush expert judgement in terms of predictive power. The problem is that the world is still sufficiently unpredictable that you can't use this insight to turn a buck, since events get "better" or "worse" with about the same frequency. I reviewed Tetlock's book here: http://chester.id.au/2012/07/29/review-expert-political-judgement/ http://chester.id.au/2012/07/29/review-expert-political-judg... And I heartily recommend it to anyone.
- 001sky 13y agoembarrassingly simplistic linear models crush expert judgement in terms of predictive power. This is true in the vas majority of cases (andecdoctaly). But the inflection points are the subject of this essay. The analogue in internatinaly geopolitics, would be 9/11 and the ruthless pursuit of anti-civillian warfare. Which nobody predicted, and which <gamed> the theory of linearity[1] to maximize its damage. [1] eg, the "expert" advice: 'go along with the hijackers', this has been empirically shown to be the safest/smartest course of action, etc
- SandersAK 13y agoSo a few things: It seems obvious that some types of companies (like entreprise) that have been started in 2010 are not going to be valued at >$1b yet. It takes time. This information would probably be more valuable if you cut it up by area (consumer v entreprise etc) and did comparables inside those areas. "Started since 2003 and valued at $1b or over by public OR private markets" To me, those are completely separate ways of valuing a company - one is realized (in that anyone who owns shares outright can sell them for the value stated) and the other is purely speculative. It doesn't matter that Fab is "worth $1b" especially as it heads towards the toilet bowl over the last 10 months. Again, companies valued at >$1b on private is an interesting group to look at, but trying to compare it to public doesn't strike me as very useful. The one thing this article does is tell me that it's hard to hit $1b realized or unrealized. But I don't think anyone thought otherwise, no?
- programminggeek 13y agoOk, I don't read TechCrunch that often, but leading a story with a giant unicorn picture that literally takes up the entire screen on my 13" MacBook Air, such that all of the meaningful content is not even on the screen is really terrible design. I wish that design trend would go away like yesterday.