I read a very interesting article on TechCrunch today about why startups fail. They shared data from research that Blackbox conducted for their Startup Genome project, which is trying to uncover what makes Silicon Valley startups succeed vs. fail. You can gain access to the free full report here. I highly recommend that you take the time to read through it. Pretty fascinating data.
My biggest takeaway from all of this? Startups absolutely need great mentors. Surprisingly, hands-on help from their investors did not have a significantly positive effect on their performance. I believe that most startup founders assume that they are going to get the guidance they need to be successful once they have secured the backing of a solid VC firm. This certainly does not appear to be the case. As I look through the key findings from the report, these points of failure seem to quite avoidable if a startup had a strong, smart team of mentors that they could turn to for advice on these issues. In particular, the most common reason for startup failure was “premature scaling” along one or more key dimensions (i.e., Customer, Product, Team, Financials, and Business model). Knowing how and when to scale a startup appropriately along these dimensions is something that an experienced mentor understands (e.g., someone who has learned from his or her own scaling successes and failures).
15 Key findings about startups from their report
- Founders that learn are more successful. Startups that have helpful mentors, track performance metrics effectively, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth.
- Startups that pivot once or twice raise 2.5x more money, have 3.6x better user growth, and are 52% less likely to scale prematurely than startups that pivot more than 2 times or not at all. A pivot is when a startup decides to change a major part of its business.
- Premature scaling is the most common reason for startups to perform worse. They tend to lose the battle early on by getting ahead of themselves. Startups can prematurely scale their team, their customer acquisition strategies or over build the product.
- Many investors invest 2-3x more capital than necessary in the discovery phase. They also over-invest in solo founders and founding teams without technical cofounders despite indicators that show that these teams have a much lower probability of success.
- Hands-on help from investors have little or no effect on the company’s operational performance. But the right mentors significantly influence a company’s performance and ability to raise money. However, this does not mean that investors don’t have a significant effect on valuations and M&A.
- Solo founders take 3.6x longer to reach scale stage compared to a founding team of 2 and they are 2.3x less likely to pivot.
- Business-heavy founding teams are 6.2x more likely to successfully scale with sales-driven startups than with product-centric startups.
- Technical-heavy founding teams are 3.3x more likely to successfully scale with product-centric startups without network effects than with product-centric startups with network effects.
- Balanced teams with one technical founder and one business founder raise 30% more money, have 2.9x more user growth and are 19% less likely to scale prematurely than technical or business-heavy founding teams.
- Founders that don’t work full-time have 4x less user growth and end up raising 24x less money from investors.
- Most successful founders are driven by impact rather than experience or money.
- 72% of founders find out that their initial intellectual property is not a competitive advantage.
- Startups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely.
- Startups that haven’t raised money overestimate their market size by 100x and often misinterpret their market as new.
- B2C vs. B2B is not a meaningful segmentation of Internet startups anymore because the Internet has changed the dynamics of customer interaction. We found 4 different major groups of startups that all have very different behavior regarding customer acquisition, time requirements, market risk and team composition.
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