I have just finished reading the Start-up Genome report produced last year by a team from the Universities of Berkley, Stamford and the VC Black Box on whether there is a framework for understanding why start-ups ( specifically tech start-ups in Silicon Valley) succeed or not.

It is very interesting reading and I hope to incorporate many of the findings into future bootcamps particularly the Tech bootcamp and the “ Getting Started in Business” tasters events that I am happy to announce we  will be running with the Computer Science department of UCL and Imperial in the next few weeks.

There is a lot to digest especially concerning the 4 models they report tech start-ups can be segmented into and the subsequent different guidance and expert support services that companies that fall into one of these categories require. But I thought I would blog the summary of their overall findings and suggest that anyone who is interested should check out the report on   https://www.startupcompass.co/)

So here goes. The Start-up Genomes report key findings for tech entrepreneurs and the investors and mentors who support them are as follows:

1. Founders that learn are more successful-  Start-ups that have helpful mentors, track metrics effectively, and learn from start-up thought leaders raise 7x more money and have 3.5x better user growth. (The most important finding and lesson for anyone starting an ambitious business although given the sample size the exact numbers ( e.g. 3.5 x ) should be taken with a pinch of salt. )

2. Start-ups that pivot once or twice times raise 2.5x more money and have 3.6x better user growth, and are 52% less likely to scale prematurely than start-ups that pivot more than 2 times or not at all. (To pivot means to fundamentally change strategy to make sure your product fits the needs and demands of target customers. A pivot will require you to fundamentally change  what you are offering to customers, or the channel to market or the customer segment who will be your initial market. So it is good to adapt to market feedback but if you do it too often it is for obvious reasons not a good sign)

3. Many investors invest 2-3x more capital than necessary in start-ups that haven’t reached problem solution fit yet. 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.

4. Investors who provide hands-on help 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 but it does suggest that the role of mentor and investor are significantly different.)

5. 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.

6. Business-heavy founding teams are 6.2x more likely to successfully scale with sales driven start-ups than with product centric start-ups. ( N.B. The Y-combinator model suggests the ideal team has a combination of people with sector knowledge/ credibility, business capability and sufficient in-house technical ability to get the product/service designed, made and delivered.)

7. Technical-heavy founding teams are 3.3x more likely to successfully scale with product-centric start-ups with no network effects than with product-centric start-ups that have network effects.

8. 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.

9. Most successful founders are driven by impact rather than experience or money. (So they say)

10. Founders overestimate the value of IP before product market fit by 255%. (A classic example of endowment fallacy)

11. Start-ups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely. ( From first-hand experience this rings true)

12. Premature scaling is the most common reason for start-ups to perform worse. They tend to lose the battle early on by getting ahead of themselves. (Whether it is more important than other strategic decisions is debatable. Bad management decisions and the lack of market demand are the main reason business fail and or under-perform)

13. Startups that haven’t raised money over-estimate their market size by 100x and often misinterpret their market as new.

14.B2C vs. B2B is not a meaningful segmentation of Internet start-ups  anymore because the Internet has changed the rules of business. ( A kind of tautology but I agree that tech businesses can be divided between those who can use the web to complete the sales/distribution cycle ( such as Google) and those who still require a real world sales function to convince a sceptical customer to buy ( such as Sage)

The report (based on a very small sample size) also  believes there are  6 stages that allo entrepreneurs go through

  1. 1.       Discovery

Purpose: Start-ups are focused on validating whether they are solving a meaningful problem and whether anybody would hypothetically be interested in their solution.

Events: Founding team is formed, many customer interviews are conducted, value proposition is found, minimally viable products are created, team joins an accelerator or incubator, Friends and Family financing round, first mentors & advisors come on board.

Time: 5-7 months (average for all types)

Amount of External funding required: ( mostly from friends, family or fools) as $10-50K (or $7-35K)

  1. 2.        Validation

Purpose: Start-ups are looking to get early validation that people are interested in exchanging their money or time/attention on the product.

Events: refinement of core features, initial user growth, metrics and analytics implementation, seed funding, first key hires, pivots (if necessary), first paying customers, product market fit.

Time: 3-5 months (average for all types)

Amount of External Funding Required: Seed investment of between $100-1.5M ( £75K-£1m) depending on type of start-up.

  1. 3.       Efficiency

Purpose: Start-ups refine their business model and improve the efficiency of their customer acquisition process. Start-ups should be able to efficiently acquire customers in order to avoid scaling with a leaky bucket.

Events: value proposition refined, user experienced overhauled, conversion funnel optimized, viral/ sticky/ profitable promotion driven growth achieved, repeatable sales process and/or scalable customer acquisition channels found.

Time: 5-6 months (average for all types)

Amount of External Funding Required: 0 -recommended to wait until stage 4 until raising.

4) Scale

Purpose: Start-ups step on the pedal and try to drive growth very aggressively.

Events: Large A Round from Venture Capitalist, massive customer acquisition, back-end scalability improvements, first executive hires, process implementation, establishment of departments.

Time: 7-9 months (average for all types)

Amount of External funding Required: $1.5 – 7M depending on type. There is not much difference in the capital raised between stage 2 and 3, which is to be expected in our model because in Stage 3 a start-up should be focused on efficiency and there’s no need for excess capital beyond what was raised in stage 2.

5) Profit Maximization (not assessed in the Start-up Genome report)

6) Renewal or Decline (not assessed in the report)

I hope you agree all good food for thought.