If you would like to read to the full report you can download it here:
Summary of the findings
Based on our analysis of about 3200 high growth internet startups approximately 70% of the startups in our dataset scaled prematurely.
(inconsistent startup = show signs of premature scaling)
1. 74% of high growth internet startups fail due to premature scaling.
2. No startup that scaled prematurely passed the 100,000 user mark.
3. Startups that scale properly grow about 20 times faster than startups that scale prematurely.
4. 93% of startups that scale prematurely never break the $100k revenue per month threshold.
5. Before scaling, funded inconsistent startups are on average valued twice as much as consistent startup and raise about three times as much money.
6. The team size of startups that scale prematurely is 3 times bigger than the consistent startups at the same stage. However startups that scale properly end up having a team size that is 38% bigger at the initial scale stage than prematurely scaled startups, and almost surely continue to grow. Startups that scale properly take 76% longer to scale to their team size than startups that scale prematurely.
7. Inconsistent startups are 2.3 times more likely to spend more than one standard deviation above the average on customer acquisition.
8. Inconsistent startups write 3.4 times more lines of code in the discovery phase and 2.25 times more code in efficiency stage.
9. Inconsistent startup outsource 4-5 times as much of their product development than consistent startups.
10. In discovery phase 60% of inconsistent startups focus on validating a product and 80% of consistent startups focus on discovering a problem space. In the validation phase, where startups should be testing demand for a functional product, inconsistent startups are 2.2 times more likely to be focused on streamlining the product and making their customer acquisition process more efficient than consistent startups. It’s widely believed amongst startup thought leaders, that successful startups succeed because they are good searchers and failed startups achieve failure by efficiently executing the irrelevant.
Startups that scale prematurely are classified as inconsistent and startups that scale properly are classified as consistent Startup Genome Report: premature scaling v 1.1 . Copyright 2011, contents under creative commons license . Page 1411. Inconsistent startups monetize 0.5 to 3 times as many of their customers early on.
12. The following attributes have no influence on whether a company is more likely to scale prematurely: market size, product release cycles, education levels, gender, time that cofounders knew each other, entrepreneurial experience, age, number of products, type of tools to track metrics and location.