The study indicates premature scaling is the number one cause of startup failure. Y-Combinator's results seem to indicate the number one cause of failure among its startups is kind of the opposite: the startup just kind of peters out, and the founders go work on something else.
I assume this is a result of selection bias on both sides: Y Combinator only funds extremely small startups (generally 2-3 people), and this study likely (though I'm having trouble verifying) only includes startups that got beyond this phase. Does this sound reasonable?
Our study contains startups that are in stages across the board, (Discovery, Validation, Efficiency, Scale).
While many of the YC startups don't reach the Scale stage, and maybe don't scale up their team or or raise too much money, they can still prematurely scale the product by over-engineering the product and not doing enough customer development. There are more nuanced case of premature scaling that are also discussed in the report.
I was going to post here asking what sort of scaling the report was talking about since asking here would be faster than registering to get the report. Now I have your answer, but the answer is intriguing enough that I'll probably go ahead and register.
I assume this is a result of selection bias on both sides: Y Combinator only funds extremely small startups (generally 2-3 people), and this study likely (though I'm having trouble verifying) only includes startups that got beyond this phase. Does this sound reasonable?