Done

Investing in Founders Beats Investing in Startups

Investments in founders directly can be more profitable for venture capitalists

Summary

The goal of our study was to examine the professional journeys of entrepreneurs who have successfully launched startups and to determine whether their success is a trend worth investing in. During our study, we sought to understand how long entrepreneurs stick with their startups and what their careers look like after they launch.

We selected a pool of US tech entrepreneurs who founded a company and got Seed Round investment in 2010-2013. We tracked their career paths from 2010 to 2022.

Here's what we found: On average, tech founders spend about 4.64 years with their startups. After that, they typically invest roughly 3 years in launching other businesses and another 3 years in senior roles like CEOs, CTOs, or Directors.

Analysis

Startup Founder career course

We used original data from the Pitchbook database, looking at U.S. tech entrepreneurs from founded companies between 2010 and 2013 that received venture capital investments. We selected a group of 1,746 entrepreneurs who were Founders or Co-Founders of companies that secured their first VC round in 2010. We then combined this data with publicly available LinkedIn profiles to explore their six most recent career steps from 2010 to 2022. Each job title was assigned a rank to reflect its seniority.

Our graph illustrates the average years spent in each job role, with the vertical axis showing the time in years and the horizontal axis indicating the job's rank. Rank 9 represents the Founder position in the first Y10 startup, and Rank 8 denotes Founder positions in subsequent startups, with a complete list of rank correspondences for various job positions.

In general, Y10 Founders dedicate 5.75 years to their initial startups. The entrepreneurs then spend about 3 years establishing other businesses and about 3 years in high-level positions (C-suit, SVP\VP, Head, Director), ranging from Rank 7 to 4. They also allocate around 3 years to roles like managers or software developers, which fall under Ranks 2 to 3 and often offer substantial compensation, especially in major tech companies.

We further adjusted Rank 9 data by excluding medical and science positions and singular job roles. This adjustment resulted in an average of 4.64 years for Y10 startups, compared to 5.75 years for all job categories, taking into account the overlap between medical and science roles and single-job positions.

image
image

Time funnel by funding round

Within the Y10 cohort, we categorized companies that received various funding rounds, including Seed to Series D. We considered each company as if it were a Founder and calculated the average time Founders spent per round:

  • Seed Round: 4.965 years per Founder
  • Series A: 2.11 years
  • Series B: 4.01 years
  • Series C: 5.91 years
  • Series D: 7.83 years

These findings align with our earlier discovery that Y10 Founders typically invest approximately 4.75 years in their Y10 company. It also takes about 2 years to secure funding for each round.

We further examined the number of companies and the average time spent per round, which can be summarized as follows:

  • Seed to Series A: 1574 companies with an average of 2.11 years
  • Series A to Series B: 864 companies with an average of 1.9 years
  • Series B to Series C: 461 companies with an average of 1.9 years
  • Series C to Series D: 228 companies with an average of 1.92 years

Of particular note is the classification of 413 sub-companies within Series A, designated A1-AAA, demonstrating an average duration of 2.15 years. Consequently, we decided to omit Series B1-BB and analogous subcategories in future calculations.

Hey
Series A
5/9/2008
Series B
6/1/2005
Hipmunk
Series A
8/17/2010
Series B
6/1/2005

Unicorns

Within the initial Y10 cohort, comprising 1018 unique companies, 21 companies reached Unicorn status. Notable Unicorns include PagerDuty, Fab, MX Technologies, WhatsApp, Duo Security, and others.

Narrowing our focus to tech-exclusive Unicorns, we identified 15 companies within the initial cohort.

In the subsequent 627 companies, data was obtained for 346. Among this subset, nine companies achieved Unicorn status, including Mux, Digit Insurance, Vercel, Vimeo, Apollo.ai, Dermira, Commure, Kin Insurance, and Fast Radius, with five of them belonging to the tech-exclusive category.

Our previous findings indicated that Founders typically invest approximately 4.6 years in their first company and about 3 years in subsequent ventures. This suggests that they created 15 Unicorns during the initial 4.6 years and an additional 5 Unicorns within the subsequent 3 years. This indicates a growing Unicorn creation rate, progressing from 0.3 to 0.6 Unicorns per annum, with the potential for further augmentation among seasoned Founders.

The key takeaways

  • Our analysis showcases the transformation of 37 Founders within the Y10 startups into Unicorns over a 12-year span, supplementing 28 Founders who founded Unicorns after their involvement with YC startups.
  • The revelation of an escalating Unicorn creation rate, particularly among experienced Founders, underscores the potential for future growth.
  • An intriguing investment insight arises: by engaging directly with Founders over their 12-year professional journey, investors could potentially secure 0.3x more Unicorns in contrast to exclusive investment in the initial startups.
  • On average, Founders within our cohort dedicate 4.6 years to their Y10 startup.
  • After moving on from their Y10 startup, Founders require only 3 years, on average, to replicate the production of Unicorns.
  • Founders in our examined cohort, during each year invested in building their startups, allocate an average of 0.7 years in executive roles within other enterprises.

Y Combinator case

We analyzed 219 founders and 119 startups that graduated from Y Combinator (YC) over four consecutive batches. Of those, 11 founders grew their YC startups into 6 unicorns, a 5% startup-to-unicorn conversion rate. Typically, a startup-to-unicorn conversion rate is only 1%.

Why are YC alumni so much better at turning their businesses into unicorns?

Selection principles: Founders over Companies

We found that one of the most reliable predictors of unicorn-type success is whether a founder had prior exits. Nine out of eleven unicorn founders had previously successfully exited their startups. The conversion-to-unicorns rate for repetitive founders is 5.6x times higher than for founders without exits.

These findings are consistent with those of Ali Tamaseb's Super Founders study, which found that founders with prior successful exits have a 6.5 times higher chance of creating a unicorn compared to first-time founders.(Ali Tamaseb study).

Our analysis suggests that evaluating founders instead of companies can be a more fruitful approach for VCs. We found that investing in people can lead to significantly greater returns than investing in a particular company. Within a 10-year time frame, VCs who invest in founders can expect to see approximately 2x better returns than those who rely on evaluating business models.

Analysis of YC founders

We analyzed the success of 219 founders and 119 startups who graduated in 2 years from the four Y Combinator subsequent batches.

Key takeaways:

  • Over the course of 10 years, 11 founders grew their startups into unicorns, and an additional 11 founders created unicorns after pivoting from their YC startups.
  • Investing in all the founders directly could have resulted in 2.3x more unicorns compared to investing in just their initial YC startups.
  • On average, founders spent 4.2 years in their YC startups, and only 1.8 years on average per startup to create a unicorn after pivoting.
  • Founders spent 0.3 years working in executive roles per year building their own startups.
  • A key predictor of unicorn success is whether a founder had prior successful exits. Of the 11 founders who founded unicorns after pivoting from their YC startups, 9 had successful exits from their YC companies - a 7.2x higher chance than founders without successful exits.

To create a dataset for our analysis, we gathered the data on Y Combinator (YC) startup founders and combined it with publicly available information from sources such as Crunchbase, LinkedIn, and Google. To ensure a clear and meaningful timeline, we focused on a 10-year period, selecting four YC batches from 2009 to 2011. For each YC founder, we identified all of their associated startups and co-founders. We then examined each co-founder's subsequent startup activity within the 10-year timeframe. Additionally, we obtained financial data on each startup, such as funding rounds, valuations, and exits.

As the first step of the analysis, we evaluated the track record of this cohort of founders and discovered that they had created a total of 333 companies within a 10-year period, of which only 119 were part of the YC sample. This suggests that the founders keep a consistent track record of creating companies and maintaining their careers as founders.

image

Continuing our analysis, we shifted our focus to the success of the startups associated with this cohort of founders. Given that a significant portion of exit values tend to come from unicorns, we examined the unicorns. Our analysis revealed that 11 of the founders grew their YC startups into unicorns, while another 11 founders created unicorns after moving on from their YC ventures and starting new companies. At a time, 6 startups from the YC batches grew into unicorns. Another 8 unicorns were created by the same cohort of founders later during the 10 years period.

By combining the data, we calculated a 5% conversion rate of YC startups to unicorns within the analyzed batches. Moreover, the total number of unicorns created by the founder cohort was 2.3 times higher, indicating that these founders not only repeated but surpassed their previous successes with subsequent ventures. It is worth noting that the performance of the startups in the YC batches significantly exceeded the market average of 1%.

Conclusively, our analysis highlights that the founders demonstrated exceeding performance in creating unicorns. Most importantly, the same group of founders has continued to create unicorns even after they gave up on their YC startups. Investing in the founders directly could have resulted in 2.3x more unicorns within the first 10 years compared to investing in only the initial YC startups.

As the next step, we examined the duration of time that the founders spent on YC startups compared to subsequent companies.

Our analysis found that, on average, founders from the sample spent 4.2 years working on YC startups. However, after moving on from their YC ventures and starting new companies, these same founders were able to create the same number of unicorns in just 1.8 years on average. We also found that these founders spent an average of 0.3 years working in executive roles at other companies per every year they spent building their own startups.

image

Next, we examined whether the experience of the founders could predict the likelihood of them creating a unicorn. Our analysis revealed that of the 11 founders who went on to found unicorns after leaving their YC startups, 9 had experienced successful exits from their YC companies. This represents a 5.6x times better chance compared to founders who did not have successful exits from their YC companies.

These findings are consistent with those of Ali Tamaseb's Super Founders study, which found that founders with prior successful exits have a 6.5x times higher chance of creating a unicorn compared to first-time founders. (the Ali Tamaseb study).

Our findings on the YC founder cohort are consistent with our study on a larger sample of US tech entrepreneurs, which included 1,746 individuals who created startups outside of YC. This larger sample also demonstrated a pattern of creating multiple companies and spending an average of 4.2 years in a startup before moving on to the next venture. However, the unicorn rates in this larger sample were less significant, which can be attributed to the fact that the startups in the YC batches significantly outperformed the market average.