A few months ago, I hired an equally qualified woman for less money than I offered a man for the same position. It was an accident, but it was my fault. This is the story of how my unconscious bias was interrupted by effective and systematic review.
We’re still not there: equal pay for equal labour
Equal pay for equal labour continues to plague every economy and company around the world, with the median pay for women remaining stubbornly 15-20% lower than men, even in countries working hard to do better with legislation, education, and systemic interventions.
The reasons for this pay gap are myriad: women are under-represented in senior jobs and over-represented in low-paying jobs, have career interruptions due to childbirth, and regularly take on more household responsibilities thus limiting their career advancement.
But the pay gap is in many ways a symptom of the common biases women face in hiring interviews, promotion opportunities, and daily work. Women are perceived as less technical during hiring interviews, they have to prove competence more often than men to justify rewards, including promotions, and they are more likely to take on or be assigned “office housework”.
Many companies publicly work to improve the situation, including taking the 50/30 challenge (as Siemens Canada has done, and it’s worth noting that our CEO is also a founding member of CILAR) or publishing the progress they’re making towards a more diverse and inclusive workforce.
But one clear problem is bias, frequently unconsciously applied. This is when otherwise well-meaning people, men or women, fail to treat women equally because of underlying societal training. Millions have been spent trying to train employees to recognize the moments at which they may be unconsciously biased, but there’s mounting evidence to suggest that such training is less effective than we would like.
Unconscious bias is really unconscious
So back to my story. In January, I hired a woman for a position that started in May. At the time, I worked with my HR division to review my team’s salaries and established what we believed to be a fair salary, given that she was newly graduating from an engineering program I knew well.
She happily accepted.
Three months later, I sat down to build an offer for a man, entering into the same position at the same seniority level, graduating from the same university at the same time from the same engineering program. Without looking at the salary I had offered the woman, I worked with my colleagues to establish what we believed to be a fair salary. It was over 3% higher.
Fortunately, Siemens insists that we review all job offers with our HR team and one of the steps is a review of existing salaries. I’ll be honest, it was almost missed here as well because the woman was not yet on my team — neither applicant had yet graduated and started the job. But then it occurred to us…
“What salary did we offer in January to the woman who will be starting at the same time?”
The really good news is that Siemens made everything else easy. Within 48 hours, we were able to call the woman and inform her that she, before even starting, was going to get a 3% raise. We also told her why.
Unconscious bias is a terrible thing. I and the team of people (both men and women) putting together these job offers have every intention of being utterly fair in salaries across the board. Yet even with the best of intentions, we needed to have a system in place that would interrupt any bias. This was an easy case because the parity between applicants was so simple to establish. But wide-ranging reviews of job offers by multiple actors are one effective way to interrupt unconscious bias. I’m thrilled that reviews worked in this instance… and glad that it’s there for me next time that I fail to account for my biases.
However, most companies are too small to be able to have a team dedicated to ensuring fair pay. Or they don’t have the resources to develop a strong diversity & inclusion policy with practical systems for interrupting bias.
If unconscious bias training is increasingly seen as having limitations, what new steps can we take to ensure bias interruption across our economies?
Further reading on interrupting bias, highly recommended: https://hbr.org/2019/11/how-the-best-bosses-interrupt-bias-on-their-teams