The Ten Year Study – what we did
We looked at information on the Companies (773), Reviewers (1,067), and Business Plan Reviews (7,271) that were part of the MCN program between 2008 and 2018.
We focused on four areas
- What attributes of the company’s leadership team most strongly correlated to future success
- What attributes of the business plan most strongly correlated to future success
- What attributes of the reviewers most strongly correlated to an ability to more accurately predict companies that would succeed or fail.
- Internal research on the success of our program implantation.
What we mean by Company Success
We looked at four success measures. While all of our companies aspire to social, environmental, or cultural impact, those measures vary widely by industry, so we stuck with four items that could be more consistently tracked. Data came from interviews, LinkedIn, Pitchbook, Crunchbase, Owler, and other media reports.
- Annual Revenue — which we adjusted by relative country wealth, since $100K USD means different things if you are based in, and selling to people in, the USA vs. being based in, and selling to people in, saw Myanmar.
- Longevity — Years in business since participating in our program.
- Non-Founder Hires.
- Funds Raised.
The Ten Year Study – what we learned
1. Leadership Team Attributes
We tracked the entrepreneurs leading out companies by a variety of attributes. More data on our research in this area can be found here.
- Mixed-gender teams were at least twice as likely to be successful as all-male teams and all-female teams in all success categories.
- All-female teams slightly out-performed all-male teams, except in longevity, where they slightly under-performed.
- Entrepreneurs between the ages of 26 and 29 when starting their companies were 75% more likely to be successful at raising outside funds than other age groups.
- As entrepreneurs got older (measured by their age at company launch) men saw a slight decline in success measures. Women saw a far more dramatic decline — those starting their companies at the age of 37 of older were one-third as likely to be successful as the Men.
- The entrepreneurs formal educational backgrounds did not make much difference, excepting that entrepreneurs with doctorates being 75% more likely to be successful at raising funds. The least useful advanced degree in our study was the MBA.
2. Business Plan Strengths
Our review form looks at the strength of a business plan in six categories — Product, Market, Risk, Team, Financials, and overall Viability. We looked at the companies that received the highest marks in those areas, and the areas in which they ended up most successful. More data on our research in this area can be found here.
- Business plans with an excellent assessment of their market are three times as likely to be in the highest revenue group.
- The ability to define risk (including an overview of competition) is less related to eventual success that an the other categories, although a low score on risk is the strongest correlate to a company’s failure.
- Business plans that received high marks for their financials were three times as like to be in the group with the most funds raised, but only twice as likely to be in the group with the most revenue.
- The success measure least correlated to a strong business plan was years in business.
3. Reviewer Accuracy
Within our time from of 2008 to 2018, 500 reviewers reviewed 5 or more business plans through our program. We compared the representation of individuals with certain attributes (age, gender, education, professional background, etc.) in the entire set to their representation in the top reviewers for picking successes and picking failures. More details on our research in this area can be found here.
- Individuals with CEO experience (56% of the whole set) were 25% under-represented in the most accurate set.
- Individuals with professional investing experience (41% of the whole set) were roughly on par for the top performers at spotting fails and overall accuracy, but were under-represented in the group that was best at picking winners. Investors reviewing companies in their specific field did better.
- Past Participants in the MCN program (16% of the whole set) were slightly better at picking companies that would go on to do well, and slightly worse at picking companies that would go on to do poorly.
- Women (42% of the whole set) out-performed men in every category, most significantly in their ability to spot companies that would go on to fail.
- Individuals based in the USA (88% of the whole set) were outperformed by their international brethren in their ability to spot failures, but were on par for their ability to pick winners.
- Individuals with a legal education (6% of the whole set) did well in all categories.
- Individuals with MBA degrees (41% of the whole set) were on par for their ability to spot failures, but did slightly worse compared to others in their ability to spot companies that went on to do well.
- Individuals with any Masters degree or above (80% of the whole set) were on par for their ability to spot winner and failures, but slightly under par in representation in the most accurate category.
- Individuals with doctorates (11% of the whole set) outperformed in every category to a significant degree.
4. MCN Internal
Success Measure of Past Entrants
Companies that entered our program more than once were five times as likely to be successful in all areas. Alas, the sample size here is too small (20) to be presented with the rest of our research. But it’s still out favorite data point.
Accuracy of Reviewers over Time
Reviewers get better the more they work with the MCN. A small increase in accuracy at spotting companies that go on to do well or poorly starts around the 5th cohort that reviewers work with the MCN, and continues until around the 15th cohort, after which it levels off.
Our bias examinations take into account the for overall optimism / pessimism of the reviewer and the eventual success or failure of the company
- Reviewers showed no significant bias for or against entrepreneurs that they felt were more (or less) like them in terms of shared values, skills, and mission.
- We looked to see if our reviewers showed a bias for or against entrepreneurs when groups were compared by age, race, gender, and country of origin. In terms of mentor engagement (the resource that we distribute) there was little to no significant variance.
Other Presentations of this information
In March 2020, our work got a write up in the online magazine Blue Avocado.
In July 2020, we presented our findings to the Social Venture Circle.
In July 2021, we presented our findings via the Impact Entrepreneur Fireside chat series.