Evidence that investors penalize female founders for lack of industry fit

Behind the Research with LBS Assistant Professor of Organisational Behaviour Dana Kanze.

We “sat down” with LBS Assistant Professor of Organisational Behaviour Dana Kanze to talk about the work she and her colleagues—Professors Mark A. Conley of Stockholm School of Economics, House of Innovation; Tyler G. Okimoto of The University of Queensland; Damon J. Phillips of Columbia Business School; and Jennifer Merluzzi of George Washington University—recently published in Science Advances called, “Evidence That Investors Penalize Female Founders for Lack of Industry Fit”.

See: https://advances.sciencemag.org/content/6/48/eabd7664

Can you walk us through the studies you and your co-authors performed?

We conducted two complementary studies: One was an observational study of funds raised by hundreds of comparable tech ventures led by female versus male founders catering to industries of varying gender dominance based upon the percentage of women’s employment provided by the US Bureau of Labor Statistics. The other was an experimental study where we exposed actual investors to detailed venture opportunity profiles manipulated for founder gender and industry served to see what funding decisions they would make. Across both studies, we made every effort to depart from a point of comparability and then adjusted our models to account for key factors that can influence funding-related outcomes.

What did you and your co-authors find?

In keeping with my prior work and that of other researchers as well, we first confirmed that female-led ventures remain significantly disadvantaged in their efforts to raise funding vs their male-led counterparts. Then we extended these results to explore additional metrics besides funding amounts and found that female-led ventures also receive significantly lower valuations than male-led ones, and their female founders retain significantly less equity than male founders do—differences that remain significant when accounting for our model adjustments.

On all three of these important metrics—of funding, valuation, and equity—we went on to find that the disparities become more pronounced depending on industry served: female-led ventures are at a particular disadvantage when catering to male- as opposed to female-dominated industries. For instance, a female founder will experience significantly worse funding-related outcomes if she is at the helm of a FinTech venture (for example, a cryptocurrency play) than a FashionTech venture (for example, a wearables play). In contrast, our studies revealed industry served does not affect funding-related outcomes for male-led ventures.

Were you and your co-authors able to find out why this may be happening?

Yes, in fact, one of the reasons we conducted the experiment was to get at why this occurs. Our results showed that—although investors rated the standalone ventures and founders similarly— they perceived a female founder to be significantly less of a fit with her venture when catering to a male-dominated as opposed to a female-dominated industry, while investors did not perceive cross-industry fit differences for the male founders with their ventures. We went on to find support for perceived lack of fit as a mediator for the effect, helping to explain why female- but not male-led ventures received less funding at lower valuations according to industry served.

Together, our results imply that a cognitive bias rooted in the representativeness heuristic can influence lower-level perception of how we “see” female founders fitting with their ventures depending on their industry representation. This mechanism is consistent with Madeline Heilman’s “Lack of Fit Model,” which demonstrates that women face discrimination in various forms when there’s some sort of mismatch between those qualities perceived necessary for performance in a male-typed domain and ones that women are stereotypically believed to have. Here, we extend the Lack of Fit Model beyond fit with an individual job and its corresponding role and into the organisational level via fit with the venture and its corresponding industry.

What would you say the key implications are here?  

Our work indicates that female founders seeking to bypass the discrimination they already experience as employees in male-dominated industries are unfortunately met with another set of bias-induced hurdles preventing their advancement. The implications of these distinct challenges are multi-fold. When you combine our work with recent findings from the finance and economics literatures, you notice that—contingent on receiving comparable amounts of capital—female founders actually outperform their male counterparts on a variety of KPIs when catering to male-dominated industries. So, the misperception of fit that we find in our studies is thwarting labour market productivity in attractive sectors by handicapping female founders’ ability to get the resources they need there. And confining women to the prospect of success in a subset of the labour market has downstream consequences for these female founders. Not only are their ventures unable to survive and grow, but female founders are inhibited from accumulating personal wealth to the same extent as their male counterparts, given the valuation haircut they receive and limited equity they retain. With comparatively less opportunity to achieve successful exits and other liquidity events, financially constrained female founders are in turn less likely to become serial entrepreneurs and investors as well.

If you were talking to practitioners, what would you want them to do with your findings? 

We do have some long-term aspirations and near-term prescriptions based on this work. Over time, we are hopeful that greater representation of women employed across industries will continue to chip away at the underlying bias at the heart of this effect. In the near-term, we recommend that investors take steps to combat the bias from creeping into their decision making. Research indicates that evaluators tend to fill in the missing pieces with gendered assumptions when information is ambiguous, asymmetrical or in some way incomplete. And we also know that these gender stereotypes tend to involve confirmatory categorisation, whereby evaluators make ex post justifications when information is introduced after they’ve already been swayed by bias instead of updating for the new data points they receive.

So, it’s important for investor groups to build this knowledge into data retrieval and dissemination from the get-go. That means reforming your intake processes to ask the same questions and capture the same data points from all funding candidates. In doing so, you can kick off an investor committee meeting with a baseline along the lines of, “All the opportunities up for discussion today have been pre-vetted to determine comparability for the following criteria,” making sure to include founders’ industry experience. Lastly, we found that lack of fit-driven gender gaps appear to tighten for female-led ventures in female- vs. male-led industries when evaluated by accredited as opposed to non-accredited investors. This suggests the benefits of allocating resources to foster financial decision-making literacy among investors, increasing their degree of sophistication.

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