Data driven diversity

Last week, I had the pleasure of touring the Atlassian offices in San Francisco as part of Startup Catalyst’s Future Founders mission. Now I can’t say I was overly enthused before this tour, it isn’t in the nicest part of town and I didn’t see how it would be relevant to myself, a neuroscientist. Man would I soon be eating those words (as well as some delicious sourdough crusted pizza).

The offices were built into an existing warehouse space, that was open plan for collaboration but offered a variety of individual working and chill out spaces. One dark room was entirely dedicated to massage chairs. There was one corner dedicated to mindfulness colouring in. It was awesome.

The highlight of this tour, and indeed one of the Catalyst cohorts overall favourite talks, was by Global Head of Diversity and Inclusion, Aubrey Blanche. Now, this was by no means the first talk on diversity this group of young scientists and engineers had ever heard, and would not be the last. But it may be the only one we ever needed to hear.

How do you create a space for those who are different to you?

When Aubrey started working at Atlassian, the company was only hiring around 10% women for their technical roles. In their last round of graduate hiring, they hired 57% women. Some key points that Aubrey made that resonated with me were these:

  • People are biased to want to hire people who are like them. It’s obvious when you think about it, if you have to hire someone, who want someone you can relate to and be friends with. This person is probably a lot like you.
  • It’s a common attitude to expect someone to fit into your workplace culture, and ask them how they could do so. Instead, why not hire someone for what they can add to your workplace culture?
  • Keep track of your data, conduct experiments and evaluate your results. What works for another company may not work for yours. Pure numbers reflect representation, but not true diversity. There is no book to work from when it comes to creating a workplace with a balanced diversity of thought.
  • Don’t set benchmarks. Saying you need 50:50 gender balance may lead to the processes being wrong, and hiring the wrong people, to meet a bench mark that may not even be representative of the population.

My favourite thing she said, was something that surprised me the most:

  • Don’t start with gender equality.

I am a mad advocate for gender equality in science, but I could not agree with her more. Fix the processes, grow your pool of applicants and ensure your team is trained to hire only the best people. How did Aubrey achieve a 57% female graduate hire? She told the hiring team simply to ‘hire the best people’. There was no quota to meet. Simply put, 57% of the best candidates were women. To start with trying to tackle gender equality in a business is seen as noble, and at the moment let’s be honest, it’s fashionable. At the moment, I can see it leading to women in jobs they feel like they don’t deserve, because there was a quota. I see men judging womens technical skills, because there was a quota. I honestly believe we won’t achieve gender equality until we have equality overall. Starting with only getting more women into tech, well that seems to a step in the wrong direction to me.

Read more on Aubrey’s work here.


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