Building product teams, part three: creating diverse teams.
A leaders most important job.
Building diverse product teams.
A product leader’s hardest and most important job is building a diverse product team.
Diverse teams build better products more profitably than monocultural teams. A diverse team uses its members’ varied ideas to innovate and pulls from a richer pool of perspectives and backgrounds to analyze and solve problems. Five men with advanced degrees from marquee schools might wield impressive IQ firepower, but that firepower doesn’t translate to higher-performing, more efficient teams.
In a past article, I talked about building well-rounded teams by matching the passions of your team members. Focus on passions and their associated skills while searching for team members, but make the primary focus of your search about diversity.
Margaret Heffernan’s TedTALK about team productivity and super chickens exemplifies the need to build well-rounded teams of individuals whose strengths and passions match. Perfectly well-rounded individuals–the so-called super chickens–don’t make a well-rounded team.
The MIT study Heffernan references puts a finer point on what makes a high-functioning team. The best teams shared three characteristics: high degrees of social sensitivity and empathy, an equal distribution of time, and more women. Members equally share a wider variety of ideas and consider them carefully before deciding a course of action. The more unique the ideas are to choose from, the more likely the team will find a differentiated and innovative solution.
Other research shows a more diverse workforce increases profitability by as much as 36%. Diversity creates similar increases in innovation, workforce retention, and job satisfaction.
And yet, women make up less than 30% of the tech workforce and hold just 16% of technical roles. Black and Latinx Americans hold 7% and 8% of tech jobs, respectively.
The data are clear, but the problem remains ingrained and systemic.
Company Leadership.
I scoured the internet and borrowed ChatGPT’s time and computing power to look at a handful of real companies and the composition of their executive teams. I won’t name the companies, and I welcome you to conduct a similar experiment. Then I used Generated Photos to find headshots representing the gender and racial composition of the companies’ executive teams.
Then, I invented a company run by the AI-generated people I found on Generated Photos.
SuperAwesomeTech is typical in our industry.
SuperAwesomeTech easily raised venture capital money when they were private and have been equally successful in “generating wealth” through the public markets post-IPO.
The company is conventionally successful, growing customer counts and revenues while resisting the capricious ups and downs of the market. In other words, they stay in business when things are horrible and rise with all the other boats when the tide comes in. Most years, they barely break even.
Nonetheless, the company’s success made a small handful of founders, executives, and investors very rich.
SuperAwesomeTech makes necessary but boring software that enterprises gobble up to keep pace with regulatory compliance and security vulnerabilities. The software is complicated, hard to use, and expensive to implement. Return on investment is meager but enough to justify a purchase.
Let’s take a quick gander at the headshots accompanying the executive bios on the company’s About page.
This photo collage is an amalgam of the companies I researched but, admittedly, very closely resembles one or two of them. As with the broader industry, 83.3% of the execs are white.
The CEO is a slightly older but still young-looking white guy. The women run People Operations and Marketing. A South Asian man runs technology and engineering. Product, sales, operations, services, customer success, legal, alliances, and other executive functions are uniformly white males. A Latino man runs the company’s business operations in Latin America.
Employee demographics follow suit. 70% of the company is white males. Blacks and Latinx aren’t just underrepresented; they are close to non-existent. Women are clustered in non-technical roles.
How to solve intractable problems.
Diversity in the tech industry appears to be an intractable problem.
According to womentech network, here’s what that intractable problem looks like.
Solving the tech industry’s diversity problem requires the same approach as other intractable problems like climate change. Focus on taking one action. One person taking one action becomes an example others follow until it becomes a trend.
Solve the problem immediately in front of you. Then solve the next and the one after that. Every step forward is momentum, and momentum is progress.
How to hire a diverse team.
Be deliberate about making diversity the priority for your next hire.
Write your job description and clearly state your intentions: our highest priority is building a diverse team and creating a balance of backgrounds, perspectives, ideas, and contributions.
Meet with your recruiter. Make it clear you expect them to source a diverse pool of candidates. I provide example LinkedIn profiles so the recruiter can pattern match.
You’ll have to force most recruiters to source this way. Recruiters do what you pay them to do, which is getting as many candidates into the pipeline as quickly as possible, doing basic qualifications of skills along the way. They’ll take the path of least resistance and do what makes them money the fastest, so don’t expect them to operate otherwise.
Letting recruiters take a business-as-usual approach will give you a candidate pool that matches the industry’s standard demographics, and about 70-80% of your resumes will be white dudes.
Continue meeting with the recruiter each week and reject the resume pool until it reflects the diversity you want for your team. Source more example candidates each week, even if it feels like you don’t have time. When skilled candidates aren’t a match for your team, hand them off to other hiring managers.
Prepare your interviewing team. Make it clear that your highest priority is building a diverse team. Give them permission to think about the demographic distribution of the team and the company. Coach them to challenge their assumptions and recognize unconscious bias when evaluating candidates and identifying so-called “A” players.
Finally, seek the support of organizations like Year Up, a nonprofit focused on equitable access to education and economic opportunity. I was fortunate to work with them at Salesforce. Make space for internships, nurture those young adults, and then hire them.
This hiring process forces culture shifts within the product organization because the deeper you go into technology, the less diverse the team becomes. Less than 20% of your engineers will be women. About 3% will be black. LatinX will be less than that.
Don’t stop with hiring.
Women absorbed an astonishing 69% of 2022’s tech job losses!
During layoffs, protect your diversity goals.
Observe your teams at work. Help them establish the characteristics of high-performing teams, especially maintaining social sensitivity and empathy and devoting equal time and input across team members.
Get rid of the team member who dominates meetings and talks over others. Managing by consensus is tough, but make sure everyone on the team is heard and has an opportunity to lead. Weed out the super chickens.
You are breaking with corporate culture and politics. People will not like it, especially ones occupying positions of privilege and power. Or ones that have assumed those positions tacitly within your teams.
OK, white dude.
Yes, I’m part of the problem. I’ve looked around my companies and said, “Wow, we should do better than this.” And then let things operate as normal. The problem was too big to solve on my own.
So I narrowed my focus to a solvable problem–my next hire. And then the hire after that. And then the one after that.
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A bunch of resources.
https://blog.gitnux.com/diversity-in-tech-statistics/
https://www.zippia.com/advice/diversity-in-high-tech-statistics/
https://www.womentech.net/en-us/women-technology-statistics
https://www.ted.com/talks/margaret_heffernan_forget_the_pecking_order_at_work