Measuring for bias in our hiring practices

A few weeks ago, we published the extensive list of all freelancers we hired in 2022. The campaign is now a five year old tradition we call “Hire These People” with the goal of showing our crews some love and using our recommendation of them to get them new work (and anecdotally, it’s working!).

In 2018, we hired just about a dozen freelancers.

Last year, we hired 250.

Production and advertising can be a great career ladder for people to climb. Formal higher education is helpful but not at all necessary. Most crew members – both above and below the line – are self-taught and have worked incredibly hard to get where they are. For all of its issues with exhaustion and burn out, production and advertising are relatively accessible to anyone willing and able to fully dedicate themselves to it.

But like any industry, it’s not immune to nepotism, favoritism, and bias. And while we would like to think we are doing a good job at leveling the field for who we hire, we are also a company that is owned entirely by straight, white men. We owe it to our crews and our community to hold ourselves accountable when we talk about diversity and equity.

It’s time to start measuring not just how many people we are hiring, but what types of people we’re hiring, too.

To measure for unconscious bias and create a more equitable and accessible hiring practice at Windy, we’re asking our crews to participate in surveys to self identify based on race/ethnicity, gender identity, and sexual orientation. Ultimately, this information will be saved in each freelancer’s profile, so they will just fill it out once when we first hire them.

Here’s some information you should know about why and how we’re collecting this data, and where it will be used:

  • The survey will not be anonymous (but is for now while we ask for feedback).
  • People can select multiple answers to each question.
  • All questions are optional.
  • Our goal is to analyze this data internally, to recognize trends in our hiring we may not have seen as clearly. Is there a connection between gender and role on set, for example? How do these answers compare to the industry standards? Or to the demographic data of the region we’re working in?
  • For the sake of transparency, this data will appear in an annual blog post published in January of each year. The data itself will not be published on our social media accounts out of concern for using it as performative marketing.