An Analysis of the Skill Sets of the Top 15 Startups Incubated by Entrepreneur First (EF)
‘It matters what the most ambitious people do with their lives,’ thus reads the home page of Entrepreneur First’s website, Europe’s top startup incubator. So far, Entrepreneur First has helped 2,000+ people create 300+ companies, worth a combined $2bn. Among the rising stars of Entrepreneur First are Tractable, Kheiron Medical, Chattermill, Mavryx, and many more.
In this report, we attempt to investigate in more depth what the Entrepreneur First’s most successful startups have in common to know ‘what the most ambitious people actually do’ to build these startups. We ask the question, ‘What kind of knowledge and experience does EF look for in the startup founders it supports?’ and ‘What knowledge and skills do they look for when building their startup teams?’.
To that purpose, we have employed our Talent & People Insights in Knowledge Officer to select the top 15 startups that have been incubated by Entrepreneur First since their founding in 2011. The selection has been made according to the total amount of funding these startups have succeeded to secure since their graduation from the EF program. Then, we have put our Talent & People Insights at work to analyze the knowledge, skills, and work experiences of these startups’ founders and teams to develop a better understanding of the DNA of the successful startups that EF backs.
The Products of the Top EF Startups
Artificial Intelligence Takes the Lead
‘73% of the top EF startups have artificial intelligence at the base of their solutions.’ Click To Tweet
There is no one domain that is specifically driving the interest of Entrepreneur First. In fact, the 15 startups analyzed offer solutions in a wide array of domains such as real estate, healthcare, education, communications, marketing insights, personal finance, manufacturing, gaming, disaster recovery, geographical positioning, and agriculture. However, the common pattern of the data shows that 73% of them employ some level of artificial intelligence to deliver their solutions.
- 73% of the top EF startups leverage artificial intelligence versus 27% that do not use AI.
- 13% of the top EF startups focus on offering solutions to enhance the use of AI technologies helping artificial intelligence engineers worldwide.
- 13% of the top EF startups are focused on employing AI to reach more accurate customer insights.
The Founders of the Top EF Startups
Two Heads are Almost Always Better than One
The majority of the top EF startups have been founded by more than one entrepreneur, with (2) being the most common number of founders for the startups. The data suggests that, as conventional startup wisdom has it, it’s always a good idea to find a co-founder to help you with your startup and it seems that this is what EF believes too. The data also suggests that ‘too many founders’ is not ideal.
- 53% of the top EF startups have been built by 2 founders, followed by 20% by 3 founders, and 13% by only one founder.
- The least common number is 4 and 5 founders, each representing only 7% of the top startups.
It’s All About the Tech Edge
44% of the top EF startups’ founders have a university degree in computer science or computer engineering.’ Click To Tweet
The academic disciplines of the founders of the top EF startups vary with computer sciences and computer engineering leading the way, followed by degrees in the social and behavioral sciences, primarily economics. This can be attributed to the fact that, according to Entrepreneur First, almost 80% of its cohorts members are selected based on a tech ‘edge’.
- Computer engineering and computer science lead the way with 44% of the top EF startups’ founders holding an academic degree in it, followed by 22% in the social and behavioral sciences, primarily economics.
- Non-Computer engineering comes in as the third most common academic discipline among the startups’ founders, being studied by 17% of them.
- Business administration comes at 8%, law at 6%, humanities at 3%, and surprisingly mathematics & statistics at 3%.
A Postgraduate Degree is an Asset
The data reveals that 69% of the top EF startups’ founders hold postgraduate degrees. It appears that, contrary to common business adages, holding a postgraduate degree, in fact, boosts an individual’s ‘edge’ in their fields. A postgraduate degree makes it much easier for startups to validate the ‘why me’ and ‘why now’ questions that EF asks as it selects which startups to move forward with.
- 53% of the top EF startups’ founders hold master’s degrees, followed by 17% holding PhDs.
- Only 17% of the top EF startups’ founders hold only a Bachelor’s degree, with the highest academic degrees of the other 14% remaining unknown.
‘44% of the top EF startups’ founders have had at least 10 years of work experience before attempting to launch their startups.’ Click To Tweet
Despite the commonly-propagated image of startup founders being fresh, young Ivy-League-college dropouts, the data reveals that the top EF startups have founders grounded in previous work experience. In fact, most of the top EF startups’ founders, on average, have at least 10 years of work experience prior to launching their startups. This blends well with EF’s thesis that having a ‘domain’ edge puts aspiring founders at a strong position that enables them to propose innovative solutions that have not been put forward before.
- 28% of the top EF startups’ founders have at least 10-15 years of prior work experience, followed by 25% having at least 7-10 years of work experience.
- 17% of the top EF startups’ founders have more than 15 years of experience prior to their startups’ launch, followed by 11% with 5-7 years of experience.
- The least common experience ranges are the 0-3 year experience range and the 3-5 year experience range ranking at 6% and 3% respectively.
The Domain Edge Counts Too!
‘10 out of the 15 top EF startups have at least one of their founders with significant domain experience.’ Click To Tweet
Although the data may seem to point otherwise at first glance, a deeper look makes it clear that 10 out of the 15 top EF startups have at least one of their founders with significant ‘edge’ in the target domain. This implies that although 61% of the startups’ founders have a ‘technical edge’ in total, a ‘domain edge’ is still an important asset to have, although not at a 1:1 ratio.
- 42% of the top EF startups’ founders have significant domain experience, as opposed to 47% with no domain experience at all, suggesting that domain experience does not matter.
- A deeper look reveals that 10 out of the 15 startups have at least one of their founders with significant ‘edge’ in the target domain, implying that as founders come together to build a startup, the shortage of ‘domain edge’ in some of the founders is offset by the significant ‘domain edge’ of at least one of them.
- The domain edges vary to cover different areas such as real estate, healthcare, education, communications, marketing insights, personal finance, manufacturing, and gaming.
The Teams of the Top EF Startups
Engineering at the Center
‘Engineering appears to be the most important function in all of the top EF startups, comprising on average 32% of their teams.’ Click To Tweet
As 80% of all Entrepreneur First’s cohort members join with a ‘tech edge’, it comes at no surprise that the startups these founders build are highly engineering-focused. The data also reveals a promising interest in building up research, operations, and customer support functions.
- Engineers comprise the biggest group of the startups’ teams as they represent 32% of the top EF startups’ teams, on average.
- Next, comes the group of founders and advisors, representing, on average, 12% of the top EF startups’ teams.
- Almost equal attention is paid to research, operations, and customer support, representing an average of 9%, 8%, and 7% of the top EF startups’ teams respectively.
A Clear Inclusion of Global Talent
‘27% of the top EF startups’ teams come from 40 different countries around the world.’ Click To Tweet
Although 93% of the top EF startups are headquartered in the UK and 73% of their teams are located in the UK, the data shows that the remaining 27% are located in 40 different countries around the world. This suggests that global diversity is built in the DNA of the top EF startups as they give priority to acquiring and maintaining a ‘tech edge’ in their domains.
- The top two countries for global tech talent are the UK and the USA, with 73% and 12% of the top EF startups’ teams being located in them.
- Excluding the UK and the USA, the top EF startups’ teams are mainly distributed across Europe, Asia, and Africa at 5.7%, 3.7%, and 2.6% respectively.
- 27% of the top 15 startups’ teams are located in 40 different countries across all continents covering countries such as Germany, Somalia, China, Japan, and Russia.
Experience Still Counts
The data is almost equally distributed across all work experience ranges, except for the 7-10 year work experience range. This suggests that seasoned professionals are the most sought after talent group in the top EF startups and that they are necessary to build a successful startup that EF would support.
- 24% of the top EF startups’ teams have 7-10 years of work experience before joining the startups.
- This is followed by 17% in the 3-5 year work experience range and 16% in the 10-15 year work experience range.
- The 5-7 and the 15+ years of work experience ranges are both equally popular, comprising 15% of the teams each.
- The least attractive talent group for the top EF startups is the 0-3 year work experience group, comprising only 14% of their teams, indicating that freshers are the least favorable group for the top EF startups.
A Team with an Edge
The coincidence is worth mentioning– 69% of the top EF startups’ founders hold postgraduate degrees; similarly, 69% of the teams they build hold at least one postgraduate degree. This finding suggests that from an EF perspective, a Master’s or Ph.D. is a great way of attaining a ‘technical edge’ and that this edge is as necessary for the teams as it is for the founders.
- 57% of the top EF startups’ team members hold Master’s degrees in their fields.
- In addition to Master’s degrees, 12% of the startups’ team members hold PhDs.
- Only 31% of the startups’ team members do not hold any postgraduate degree, suggesting an overall preference for talents with research experience.
A Clear Preference to the Technical Edge
‘41% of the top EF startups’ team members have a degree in computer engineering; 29% in business administration.’ Click To Tweet
The data reveals that when it comes to building teams, the top EF startups are built around high computer engineering skills with other skills being complementary. There is a clear preference, according to the academic backgrounds of the top EF startups’ teams, to calibers with a ‘technical edge’ as they comprise a significantly higher proportion of the teams, in comparison to calibers with a ‘domain edge’.
- Degrees in computer engineering are the most common degrees held by 41% of the team members in the top EF startups.
- The second most common degrees are degrees in business administration, being held by 29% of the startups’ team members.
- Degrees in social & behavioral sciences, primarily economics, come in third at 20%, followed by degrees in non-computer engineering at 18%.
- Degrees in humanities, life sciences, physical sciences, and mathematics and statistics are less common, being held by 12%, 11%, 11%, and 10% of the startups’ team members respectively.
This preference to the ‘technical edge’ is evident even in the startups operating in the most domain-heavy industries such as Mavrx and Kheiron Medical, where computing and engineering degrees significantly surpass the number of degrees in the life and physical sciences by 31% and 40% respectively.
A Diversity of Work Experiences
‘Experience in tech companies comprises 31% of the total work experience of the top EF startups’ team members, followed by experience in the financial and investment services companies at 11%.’ Click To Tweet
No specific domain dominates the work experience of the top EF startups’ team members, as a combination of 98 different domains appears in their background experiences. Some domains appear more often than others, though, such as tech, finance and investment, and marketing and advertising. This supports the thesis that currently EF shows no specific interest in any particular domain when it makes its investment decisions.
- Experience in IT services companies, internet companies, and computer software companies comprises 31% of the total experience of the top EF startups’ team members, further supporting the preference to the ‘tech edge’.
- Prior work experience in financial services and investment companies comprises 11% of the total work experience of the top EF startups’ team members, indicating this domain to be the second most important domain that needs to exist in the DNA of an EF startup team.
- Experience in the marketing and advertising industry comes in third as it comprises 5% of the top EF startups’ team members’ backgrounds, indicating its less, yet essential, importance as a domain edge to have in an EF startup.
The Rise of the SME Edge
‘Small and medium sized companies dominate the backgrounds of the top EF startups’ teams.’ Click To Tweet
Most of the top EF startups’ team members have had significant experience in small and medium-sized companies that employ 11-200 employees. The second best incubator for EF startup talent seems to be huge corporations employing 10,000+ employees.
- Prior work experience in small and medium-sized companies (11-200 employees) is the most common factor among the top EF startups’ team members, comprising 41% of their total experience.
- The second most common organizations where the top EF startups’ teams gain their experience from are the huge corporations consisting of 10,000+ employees, as they comprise 18% of the total work experience of the top EF startups’ team members.
- Experience in companies of other sizes seems unfavorable as experience in companies that consist of 200-500 employees comprises 9% of the total work experience of the startups’ team members, companies with 500-1000 employees 6%, companies with 1000-5000 employees 11%, and companies with 5000-10000 employees 4%.
- Experience in micro-companies, consisting of less than 10 employees, is equally unfavorable, comprising only 11% of the total work experience of the startups’ team members
The Way Forward
According to the sample analyzed in this report, it is plausible to deduce that, all in all, EF seems true to its vision. The incubator clearly shows no specific preference to innovations in any particular domain, but does give preference to startups built by teams, not individuals, making up a healthy combination of ‘tech’ and ‘domain’ edges, although clearly not at a 1:1 ratio.
It can also be deduced that postgraduate education does signify a ‘domain’ or ‘tech’ edge to EF along with a minimum of 10 years of work experience. Both are not prerequisites for entry into the program but seem as assets that increase a startup’s chances of success with EF.
It is also clear that the DNA that EF looks for in its aspiring founders is the same DNA that the founders themselves look for in the teams they build. It is also apparent that having a significant tech edge with reasonable skill in finance, investment, and marketing are important components of a successful EF startup.
We are not perfect! The results of this research remain inconclusive and further research across larger datasets are required to reach conclusive results. In the meanwhile, it is clear that being powered with skills data analysis enables companies to objectively investigate the skill sets of their employees and make decisions for the future.
The 15 startups analyzed for the purpose of this report are:
- Atlas AI: Acquired by Facebook in 2019, Atlas AI is a startup focused on producing state-of-the-art deep learning papers.
- Bloomsbury AI: Acquired by Facebook in 2018, Bloomsbury is a startup aiming at making natural language processing (NLP) commercially available to the average user.
- Chattermill: With a $13.3M fund, Chattermil is a startup focused on leveraging machine learning technologies to reach more in-depth customer insights.
- Cleo: With $13.3M in debt finance, Cleo is a startup that leverages artificial intelligence to help users manage their personal finances.
- Cloud NC: With a $16.7M grant, Cloud NC is a startup that leverages artificial intelligence to help in creating better CNC machines for prototyping and mass manufacturing.
- Hadean: With $11.9M in funding, Hadean is a startup focused on developing cloud engines that can better support multi-player games.
- Hubble: With $7.6M in funding, Hubble is a real-estate startup that helps you find the best office space for your company and design its interior if needed.
- Kheiron Medical: With $22.1M in funding, Kheiron is a startup that leverages artificial intelligence to help eliminate the need for double-reading for breast cancer diagnosis.
- Magic Pony: Acquired by Twitter for $150M, Magic Pony is a startup that leverages machine learning to create better social media experiences.
- Mavrx: Acquired by Taranis in 2018, Mavrx is a startup that uses satellite imaging and machine learning technologies to better assess crop health and predict potential crop problems.
- Mobilus Labs: With $22.4M in funding, Mobilus Labs is a startup focused on developing the hardware and software needed to make hand-free ear-free communication possible in harsh industrial environments.
- Permutive: With $11.5M in funding, Permutive is a startup that leverages artificial intelligence to gain more accurate insights about any publisher’s audience to help them better target advertisers.
- Pi-Top: With $24.6M in funding, Pi-Top is a startup that aims at developing devices that assist in remote learning especially of engineering and coding skills.
- Scape: Acquired by Facebook in 2020, Scape is a startup that leverages both machine learning and augmented reality technologies to develop more accurate GPS services.
- Tractable: With $59.9M in funding, Tractable is a startup that leverages artificial intelligence to evaluate disaster damage in real-time to speed up the disaster recovery process.
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