The “how to” of de-biasing the startup selection process with Fluent, the FICO score for startups
[June 22, 2021 equity research findings article by Fluent Studio Inc.]
Every year, investors pump $300+ billion dollars into startups that seem like good investments. Maybe they write a check based on a gut feeling. Maybe they write it based on a strong referral to the founder or on a really great pitch presentation.
But these methods of choosing who is allocated capital or resources and who is passed over are proxies the industry relies on because there has not been more reliable data. These subjective proxies are inherently biased against underrepresented founders, and such methods of investing have led to years of inequity of funding for women and minorities.
This article outlines this problem and offers research findings as an immediate call to action that can affect real change, revealing how adding the Fluency Score to selection processes increases diversity and inclusion outcomes.
The devastating side effects of the traditional way of allocating capital
The current system for allocating capital to startups has devastating side effects, as has been well documented. These side effects happen in two main ways.
First, most companies are shut out of funding: 83% of all new businesses access neither venture capital (VC) nor bank loans, and when we focus only on tech startups, we see that about 9 in 10 do not get seed funding.
Second, founders who do not fit the white male Silicon Valley mold (“non-traditional” startup founders based on gender, race/ethnicity, geography) are the most affected. In fact, 80% of VC in the U.S. is in the top five hubs; women make up only 14.1% of tech founders, receiving only 3% of VC.
The combined blow to the economy associated with lack of inclusion in entrepreneurship is overwhelming. The U.S. could have 10 million more jobs if minorities had the same entrepreneurship rates as non-minorities.
Most investors are aware that this disparity is a problem and would like to fix it, but until now no one has been able to spell out to change their systems to affect actual change.
How to de-bias the startup selection process: Fluent’s research design
Fluent, a Denver-based data technology company, is changing the way startups are selected, supported, and tracked with its flagship product the Fluency Score, which works like a FICO Score for startups.
The scores focus on business model risk and the company’s velocity of de-risking business model assumptions on its journey to reaching product-market fit.
To put Fluency Score decision intelligence in action, Fluent worked with seven accelerators and parsed their investment choices comparing:
- their traditional selection process, using subjective expert opinion, to
- the Fluent-enhanced selection process, leveraging both Fluent data combined with their expert opinions.
The results were impressive.
Tech expert and Rebootedauthor Arnobio Morelix analyzed the data and found that 100 percent of these organizations changed their investment choices after reviewing Fluency Score data in addition to their existing due diligence process.
Additionally, every cohort that the accelerators selected was more diverse and inclusive than it would have been without the Fluency Scores (something Fluent is continuing to study, to increase sample size and understand in more detail).
While accelerators’ original selection strategies necessarily include factors such as a preference for companies based in a certain region, using a specific type of technology, or in a particular industry, without objective data to bolster the decision, the default determinant is a continued reliance on pitches, networks, gut feelings, or pattern matching.
How Fluency Score data overcomes the bias of the pitch: Examples from the study
Fluent asked each of the seven accelerators it studied to rank business ventures prior to seeing the Fluency Scores, then again after reviewing the scores.
In one case, a well-established accelerator had placed a company in its top three picks. However, that same company’s score was last on the list based on Fluent’s analytics.
The founder knew how to give a great pitch. Her slide deck showed a relationship with 15 well-known brands. She checked all the accelerator’s subjective boxes. She showed up as an impressive founder.
However, the Fluency Score report showed that in three years, the company had never made a dollar—it had zero revenue.
Exposure of that schism is critical to both parties. In looking at the score, the accelerator knows the actual degree of fit of this business to their preferences, and the founder can clearly see areas to work on so that she can move forward and begin to generate revenue.
The study also offered an opposite scenario.
A founder had identified a problem in the immigrant community of which he is a member. Through extensive research he developed technology that would solve the problem for a large number of people, and he had done extensive high-quality work to de-risk his assumptions.
What he had not done is craft a great pitch.
Before the accelerator saw his Fluency Score, they ranked him in the middle of 20 possible investments; his idea seemed forgettable, maybe not like a viable company at all.
However, evidence in his Fluency Score algorithm indicated that he was building the right thing for the right people and that his technology was something those customers would be willing to pay for.
Once the accelerator reviewed the data, they made him their top pick.
Adding Fluent’s data tool to your organization’s work multiplies D&I outcomes
The Fluency Score has the power to elevate companies in a way that goes beyond checking the traditional boxes investors already know to check. The scores offer a set of insights and actionable intelligence that are proven to generate equity and inclusion in allocation of resources.