Sequencing the Startup DNA - @mrogati's talk at StartupFest 2011
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What makes entrepreneurs different, and where do they come from? Are they born or taught? Are they unusually mobile in their careers? Does geography play a role? Do mentors and relationships matter? Numerous studies explore these questions by surveying hundreds of entrepreneurs. At LinkedIn, we take a different approach, on a different scale. By sifting through more than 120 million public profiles, we can analyze tens of thousands startup founder# profiles - and find common threads linking their careers. (make sure you follow along w/ the speaker notes; my slides are minimalist.)
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Sequencing the Startup DNA - @mrogati's talk at StartupFest 2011
- 1. @mrogati
- 2. Born to be wild?
- 3. I’ve seen all good people…
- 4. Who are you
- 5. Don’t let me be misunderstood #define startup founder US companies … founded after 2000 … 2-200 employees … with 1+ .*founder.* Out LLCs HR, Real Estate, consulting, PR, legal
- 6. Fire Starter 13K founders 2% “serial entrepreneurs” Entrepreneur Age Distribution
- 7. We can work it out UNDER-represented OVER-represented
- 8. We don’t need no education … Most entrepreneurial majors Entrepreneurship Computer engineering Computer science Physics Electrical engineering Theology Civil engineering Pharmacy Education Social work Human resources Administration Nursing Theology Civil engineering Pharmacy Education Social work Human resources Administration Nursing Least entrepreneurial majors
- 9. Takin’ care of business 1. 1. 2. 2. 3. 3. 4. 4. 5. 5. 6. 6. 7. 7. 8. 8. 9. 9. 10. 10.
- 11. t’s a long way to the top Founder career histories on LinkedIn Average position length: 2.5 years
- 12. Cisco kid Where are founders coming from? Under-represented Over-represented
- 13. Should I stay or should I go? you work in internet computer games biotech software advertising medical devices banking research edu management non-profit investment banking automotive you want to do a startup you will likely Go Stay
- 14. Are you experienced? Law practice Semiconductors Pharmaceuticals Retail Leisure & Travel Professional Training Nanotech Biotech Medical Devices
- 15. California Dreamin’ Boston New York City San Francisco
- 16. With a little help from my friends
- 17. Start me up
- 18. The End @mrogati
Editor's Notes
- Title : Sequencing the Startup DNABy: MonicaRogati – data scientist at LinkedIn. This presentation was given at 4:20PM – the perfect time for having hippie songs as my slide titles.
- There are many studies out there looking into what makes entrepreneurs different – whether they are born or taught, where they go to school, whether it’s about relationships or whether geography plays a role.The best ones (by GEM, Kauffman foundation, the Startup Genome Project and Ernst and Young) are based on surveys of 600 or so entrepreneurs; these are high precision, in depth studies, measuring numerous variables. But the number of data points is still very small.Can we get more data?
- Yes! There are >100 million people on LI
- LinkedIn profiles allow us to explore entrepreneurs’ backgrounds – education, past careers, connections – and attempt to answer these questions about entrepreneurs.
- How do we define an entrepreneur, or a startup founder?We look for companies with at least Using these rough guidelines, we came up with about 13K entrepreneurs, 2% of which are serial entrepreneurs.
- What’s the entrepreneur age distribution? In the LinkedIn data, entrepreneurs skew older. But is this selection bias? Don’t LinkedIn members skew older in general?That’s true – so, for all future data, we’re going to look at what characteristics are *over-represented* among entrepreneurs vs. the rest of the people on LI?…According to the Global Entrepreneurship Monitor, people over the age of 35 mad\\e up 80 percent of the total entrepreneurship activity in 2009. That same year,\\ the Kauffman Foundation conducted a survey of 549 startups operating in "high-\\growth" industries -- including aerospace, defense, health care, and computer a\\nd electronics -- and found that people over 55 are nearly twice as likely to l\\aunch startups in these industries.
- Here are two memorable images to explain – and help you remember- the concept of over-represented and under-represented.Babies are UNDER-represented in prison: fewer of them there vs. the overall population.What are a few animals over-represented on geeky t-shirts? Wolves, elefants and pigs.
- What schools are they coming from? The Princeton Review put together a ranking of the best business schools for entrepreneurs – based on surveys, shown on the left. We’ve put together our own ranking, on the right, based on business schools OVER-represented among entrepreneurs.
- What are other over-represented schools among entrepreneurs, other than the business schools (in blue)? There are a few technical schools (in orange), and a few general schools (in green) , some of which skew technical.
- Are entrepreneurs unusually mobile in their career? They switch jobs every 2.5 yrs before becoming founders, In general, it’s 4.4 years cf. Bureau of Labor Statistics
- Which companies are over-represented in founders’ histories?
- What industries do people STAY when they do a startup?
- What industries are hard to break into? (i.e. founders have previous industry experience before doing a startup): Law, semiconductors, PharmaceuticalsEasy: retail, consumer goods, leisure & travel, professional trainingMost academic startups: nanotech, biotech, medical devices
- Does geography matter? Yes! Most over-represented regions among entrepreneurs are SF, NYC (which is half as over-represented as SF) and Boston (which is half as over-represented as NYC)
- Founders are disproportionately connected to VCs, online publishing, people in the internet industry and recruiters
- Startup GATTACA Leave banking & move to California Go to Stanford BS and major in entrepreneurshipConvince your IIT graduate co-founder to leave YahooConnect with VCs and bloggers on LI
- It’s about Location, experience, relationships