Meeting of 5-18-16 - Promoting Diverse and Inclusive Workplaces in the Tech Sector
Good afternoon, it is an honor to be here.
My name is Benjamin Todd Jealous. I am a Partner at Kapor Capital. I am also the immediate past President and CEO of the NAACP.
I am here today to speak as a venture capitalist. I also happen to be experienced at uncovering and exposing patterns of discrimination and exclusion.
With that said, there is nothing hidden about the ways in which African Americans, Latinos, Native Americans, and many Asian American & Pacific Islander ethnic groups and women of all colors are excluded from employment in the Silicon Valley.
Demographic Patterns in Tech
A multitude of data revealsdisturbing patterns in the lack of racial and gender diversity across the technology ecosystem. Despite comprising a combined 38% of the labor force in the United States, African Americans and Latinos comprise just 15% of the tech workforce.[i] Women comprise 47% of the overall U.S. labor force, and just 25% of the technology workforce.[ii] This underrepresentation is even more pronounced in Silicon Valley; African Americans and Latinos represent between 1% and 3% of all technology employees, and women comprise between 13-24% of all technology employees (depending on the company).[iii]
What is more, in many ways, the problem has gotten worse with the growth of the technology industry. Three decades ago, two of my partners- Mitch Kapor and Freada Kapor Klein- respectively founded Lotus and led many of its HR efforts, including diversity and inclusion. They would tell you that tech is much less inclusive today than it was in the 1980s.
Demographic Patterns in Venture Capital
In response, we at Kapor Capital have established a venture capital firm with unusually inclusive leadership and a similarly inclusive investment portfolio: 75% of our partners are Black, Latino, or female; more than 75% of our investment team is Black, Latino or female; and approximately 60% of the companies we have invested in have founders who are Black, Latino, or female. These are tech startups with ambitious business plans to scale.
Our unusual perspective makes us especially impatient with the state of our industry and the ways in which venture capitalists generally contribute to the pervasive disparities in the tech ecosystem.
First, a little background on the demographic characteristics of Venture Capitalists and the entrepreneurs that they invest in.
· Who Works In Venture Capital? The gender and racial diversity at venture capital firms is worse than the overall technology industry. An examination of 71 firms managing over $160 billion in assets revealed roughly 92% of venture capitalists are male (8% female), and 78% are white (with African American and Latinos representing just 1% each of all venture capitalists).[iv][v] While arguably the demographic trends of venture capitalists indicate institutionalized practices and policies which prevent women and underrepresented racial groups from entering into venture capital, what is more revealing (and troubling) are the demographic trends of the entrepreneurs that these venture capitalists invest in and the obstacles facing women and underrepresented racial groups in VC-backed startups.
· Who do Venture Capitalists invest in? In analysis of VC-backed companies, 87% of founders were white, and less than 1% were Black. In examining the founding teams, 83% of the VC-backed startup companies had all-white founding teams, with just 11% having founders across multiple racial groups.[vi] Ninety-two percent of founders were male. Beyond the race and gender disparities, a closer look at other key characteristics of VC-backed founders indicates that 43% of VC-backed founders worked at a VC-backed company immediately before founding their own company.[vii] Further, an analysis of the top 10 schools producing VC-backed entrepreneurs reveals that all are elite institutions including Stanford, UC Berkeley, MIT, Harvard, and UPenn.[viii] A predictive analysis of the profile of the future startup founder (based on existing data), is a Stanford graduate with a Computer Sciences degree who is currently working at a VC-backed company.[ix]
What Do Demographic Patterns Reveal about Access and Opportunity?
Three key practices within venture capital ensure the disparities in venture capital and the startup/tech entrepreneurship landscape are perpetuated and the pool of diverse entrepreneurs remains disproportionately small.
(1)Pattern-Matching: Numerous venture capitalists have described the controversial practice of pattern-matching, or looking to invest in founders that match a previous pattern of "successful startup founders." Thus, given the demographic profile of the industry and of the entrepreneurs who have previously been funded, a young, white, male, Stanford graduate with several years of experience in the tech industry will undoubtedly match the pattern of predictive success in a way that women, people of color, graduates from less elite institutions, and individuals who do not have experience working for a VC-backed firm in the past, will not. Thus, judgements about ability, merit, innovation, and the model of the proposed business are not the basis for funding decisions and instead proxies for predictive success are. Two of the largest factors in many venture capitalists controversial "pattern matching" formulas are: "Where did they go to school?" and "Where have they worked?"
(2) University Preference: Using the undergraduate or graduate institution that a potential founder graduated from as a proxy for intelligence and ability overlooks several problems. The racial/ethnic diversity of the top 10 universities for VC-backed founders is minimal, and the majority of diverse computer science graduates and entrepreneurs do NOT attend the elite, Ivy institutions for reasons that have nothing to do with their ability to get in to those schools (e.g., cost of tuition, racial context/environment, proximity to family). Admission to these schools requires near-perfect SAT scores; research reveals that the single greatest predictor of one's SAT score is family income. Internships and gap years are also key differentiators of applicants to highly selective schools; these opportunities are available through networks and privilege, not merit.
(3) Industry Experience: The preference for individuals who have worked within the tech industry and particularly, at a VC-backed company, excludes the population of potential entrepreneurs who lack access to the tech industry, thus creating a homogeneous pool from which to choose "successful entrepreneurs." Using industry experience as a proxy for knowledge, skill, ability and innovation erroneously assumes that all groups have equal access to the tech industry and excludes all of the talent that has not had experience in the highly-networked group of tech companies and startups. In this respect, employers become the ultimate gatekeepers not just to jobs in the Silicon Valley but to the ranks of those who are considered talented enough to be considered for investment by VCs.
It is through these three practices that many venture capital firms play a role in exacerbating the existing disparities in entrepreneurship and creating a cycle of wealth creation and high-paying employment opportunities in tech entrepreneurship that systematically excludes women and people of color. Instead of widening these disparities, venture capital firms should be looking for ways to bring new entrepreneurs with innovative ideas into the pipeline, rather than rewarding those who have had advantages along the way. It is for this reason, we are encouraging our peers themselves to make strategic efforts to diversify their partners and employees, encourage their portfolio companies to sign on to the Kapor Capital Founders' Commitment,[x] follow the recommendations of Project Include,[xi] and create incentives and opportunities for portfolio founders to lead the diversification of their staff.
However, venture capitalists are further upstream than major tech employers and startup companies in the tech ecosystem and tech companies and startups have maximum leverage and opportunity to accelerate change across the ecosystem.
How Tech Companies and Startups Can Lead the Charge to Increase Diversity and Inclusion in Tech
Given the role of Silicon Valley's marquee tech companies and startups as the industry's ultimate gate keepers, the cause of increasing representation (through recruitment, hiring, promotion, and retention) in Silicon Valley is extremely urgent. Universities graduate African American, Latino, and female computer science graduates at twice the rate they are hired in the tech industry. Further, in the large Silicon Valley tech companies, African Americans, Latinos, and females are represented at rates 8-16x lower than their representation in the national population[xii], which is of great concern given the rapidly changing demographics of the nation. Additionally, individuals within the tech industry gain critical social and financial capital and opportunities for economic growth that African Americans, Latinos and women are excluded from and which has concerning implications for the future economic opportunities of these groups.
We believe that for these reasons, it is incredibly important for tech companies and startups to lead efforts to diversify the tech ecosystem, starting with increasing diversity and inclusion within their own companies. The following is a list of strategies that tech companies can and should be taking to increase diversity and inclusion within their companies:
1. Remove names and schools from résumés. Hidden bias is very powerful and very real. Studies show that traditional "Black" sounding names get half the callbacks than "White" sounding names, even when the résumés are otherwise identical. Removing names also works to mitigate gender bias.
2. Use the "Rooney Rule" and add diversity to your interview rounds. In the NFL, managers are required to include at least one underrepresented person of color in the final round of interviews, and this is an easy step for every company to put into practice. Additionally, consider the positive effect of having multiple diverse candidates in interview rounds.[xiii]
3. Double the bonuses given for employee referrals of diverse candidates. Social networks in the United States are extremely segregated. Employee referral incentives simply ensure that your company will continue to look-and think-like it always has. Instead, transfer that bonus to employees who bring in qualified candidates from backgrounds that are underrepresented in your company.
4. Apply a "distance traveled" metric when evaluating candidates. For a young scholar from a tough neighborhood, getting into and thriving at a minor state school means overcoming all sorts of adversity, and those real-life skills are enormously valuable to your company. Keep that in mind when you're weighing strengths and weaknesses.
5. Partner with HBCUs and HSI's to set up internship programs, particularly those that can lead to a clear path to jobs.
6. Audit your physical environments for the messages they send. Studies show that Science Fiction posters on the wall, for example, send subtle messages to women that they don't belong in that computer science classroom[xiv]. Take a careful look at what your office environment may be conveying to applicants and employees.
7. Encourage the establishment of Employee Resource Groups in the workplace. Sometimes, women and employees of color need to have the space to talk to people like themselves and share experiences.
8. Update your conflict resolution processes. Often times, HR departments are more worried about protecting the company from litigation than actually helping employees solve disputes. And too often, offenses go unreported because an employee doesn't want to be labeled a troublemaker or suffer retaliation. There are all sorts of alternative dispute resolution processes that allow everyone to be heard without triggering a battle and managers, supervisors and staff must uphold obligations to prevent harassment and retaliation.
9. Encourage and reward employees who work with non-profits developing underrepresented talent. Make this a part of your company's DNA.
10. Use technology! There is an entire field of startups creating innovative solutions to workplace diversity and inclusion. It's called People Ops Tech, and there are dozens of companies working to eliminate bias in hiring, find diverse talent pools, and create welcoming work environments for everyone.
When intentional, strategic, and urgent efforts are implemented by tech companies and VC firms alike, we can build a more diverse, inclusive, representative, and sustainable industry and ecosystem to power our nation's economic future.
[i] Bureau of Labor Statistics (2014). Labor Force Characteristics, by Race and Ethnicity. Retrieved from: http://www.bls.gov/opub/reports/cps/labor-force-characteristics-by-race-and-ethnicity-2014.pdf.
[ii] AFL-CIO (2015). The Professional and Technical Workforce. Department for Professional Employees. Retrieved from: http://dpeaflcio.org/wp-content/uploads/The-Professional-and-Technical-Workforce-2015.pdf.
[iii] Molla, R. and Lightner, R. (2015). Diversity in Tech. The Wall Street Journal. Retrieved from: http://graphics.wsj.com/diversity-in-tech-companies/.
[iv] Cutler, K. (2015, October). Here's A Detailed Breakdown of Racial and Gender Diversity Data across U.S. Venture Capital Firms. Retrieved from: http://techcrunch.com/2015/10/06/s23p-racial-gender-diversity-venture/.
[v] Palihapitiya, C. (2015, October). Bros Funding Bros: What's Wrong with Venture Capital. Retrieved from: https://www.theinformation.com/bros-funding-bros-whats-wrong-with-venture-capital?shared=ae4cd7
[vi] CB Insights (2010, August). Venture Capital Demographics - 87% of VC-Backed Founders are White; All-Asian Teams Raise Largest Funding Rounds. Retrieved from: https://www.cbinsights.com/blog/venture-capital-demographics-87-percent-vc-backed-founders-white-asian-teams-raise-largest-funding/.
[vii] Morrill, D. (2014, March). How Mattermark Teamed Up With Bloomberg Beta to Predict Who Will Start Companies Next. Retrieved from: https://mattermark.com/how-mattermark-teamed-up-with-bloomberg-beta-to-predict-who-will-start-companies-next/.
[viii] Pitchbook (2015). 2015-2016 Pitchbook Universities Report. https://pitchbook.com/news/reports/2015-2016-pitchbook-universities-report.
[ix] Morrill, D. (2014, March). How Mattermark Teamed Up With Bloomberg Beta to Predict Who Will Start Companies Next. Retrieved from: https://mattermark.com/how-mattermark-teamed-up-with-bloomberg-beta-to-predict-who-will-start-companies-next/.
[x] Kapor Capital (2016). The Kapor Capital Founders' Commitment. Retrieved from: http://www.kaporcapital.com/founders-commitment/
[xii] Molla, R. and Lightner, R. (2015). Diversity in Tech. The Wall Street Journal. Retrieved from: http://graphics.wsj.com/diversity-in-tech-companies/.