With my daily helping of all things TechCrunch, GigaOM, VentureBeat and what have you I pretty much can’t go a day without hearing about yet another up and coming start-up that’s poised to take the world by storm. Whilst I was developing Lobaco these kinds of stories were the inspiration fuel that kept me going as it seemed like even the most wacky ideas were securing funding and it was my fervent belief that should I follow in their footsteps that I’d then also reach some level of success. Of course 1 year and 1 failed Y-Combinator application later taught me that the road to success isn’t always paved in the same way for you as it is for others.
Indeed I vented my frustrations with all these positive stories, likening it to inspiration fatigue.
After coming to that realization I started trying to seek out the stories of failure, stories of people who were in situations like mine and what caused their idea to fail. Such stories would provide me with a framework of what to avoid and what I should be doing that I’m not doing now giving me a much better shot at achieving success. Trying to find such information amongst my feed reader proved to be quite fruitless except for the tales of large companies that were in the long downward spiral of decline. This is to be expected however as a failing start-up that’s only received seed or series A level funding doesn’t seem like much of a story since 90% of them fail anyway.
The Startup Genome project then was exactly what I was looking for as when I first read about them they were looking to gather information from both sides of the table. I’ll be honest though I was sceptical that they’d ever come up with anything, figuring they were just another think tank that would use metrics that no one could be reasonably expected to apply to the real world. That all changed when I read their first report, especially their insights on premature scaling:
Since February we’ve amassed a dataset of over 3200 high growth technology startups. Our latest research found that the primary cause of failure is premature scaling, an affliction that 70% of startups in our dataset possess.The difference in performance between startups that scale prematurely and startups that scale properly is pretty striking. We found that:– No startup that scaled prematurely passed the 100,000 user mark.– 93% of startups that scale prematurely never break the $100k revenue per month threshold.– Startups that scale properly grow about 20 times faster than startups that scale prematurely.
