How Do You Identify Bias Without Coming Off As Overly Sensitive?

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Does Calling Out Bias Make You Thin-Skinned?


I just completed a new-hire onboarding that included videos on promoting diversity at work. One issue the videos didn’t talk about was how to ID bias without coming across as thin-skinned. I’m a WOC and this is my biggest concern when it comes to office bias. Would love to hear your take.


Between micro-aggressions, accusations of quota-filling, and reverse-affirmative action—the institutionalized “way to win in the workplace” manual tells us to wade carefully in matters related to bias and diversity. Or better yet, stay quiet altogether.

But staying quiet in the face of inequity doesn’t sit well with me and it doesn’t sit well with you either. It shouldn’t sit well with anyone. So how can we speak up and call out bias without jeopardizing our professional reputation?

Well, good news. We have a roadmap—data, and it will lead us out of these murky waters. It will help us identify instances of bias with confidence. Or as you said, without fear of coming across as “thin-skinned.”

Here’s a live walk-through of how data can help identify bias.

  1. In your annual performance review, your manager says that teammates have been complaining about your communication style, calling it rude and snappy.
  2. You’re caught off guard because this is the first time you received a negative evaluation of your communication style.
  3. You ask your manager for specific examples of times when you’ve been rude and snappy.
  4. Your manager provides nebulous references to what other team members have allegedly said. You’re told to review past communications with colleagues and going forward, you’re advised to re-read your messages before clicking send.
  5. You don’t think this is a fair evaluation of your communication habits but don’t know what to tell your manager. You don’t want to sound like you’re complaining.

Is the above scenario an example of gender bias? If so, how can you prove it?

Let’s dig into the research. Here’s what we find:

  • Women receive more criticism in performance reviews than men: a linguistic analysis of 248 performance reviews across 28 organizations found that 87.9% of women were given negative feedback compared to only 58.9% of men.
  • Women also receive more diluted feedback than men: their performance evaluations are less likely to include specific, objective-driven feedback than men’s.
  • When women do receive constructive feedback, it’s often focused on their communication style—and how it doesn’t strike the right chord.
  • What does it mean to not strike the right chord? In the linguistic analysis referenced above, the word “abrasive” appeared 17 times in 13 separate performance reviews of women. The same word appeared zero times in male performance reviews.
  • Moreover, negative comments based on personality traits appeared in 76% of women’s critical performance reviews.

Now, imagine you return to your manager, present them with this data, and make another request for specific feedback on why they flagged your communication style as rude and snappy. It’s difficult to come across as “too sensitive” when you’ve done your research and have the facts to support your claim.

Data helps us make decisions based on facts, not emotion.

Data-as-a-roadmap is not a new or novel idea. Nor is it the takeaway I want to leave you with today.

The lesson I want you to take away from this is not that you need to spend x-amount of time per week digging into the research so you can confidently spot bias. Yes, it’s important to educate yourself. To know your worth. To understand how bias impacts you and those around you.

But if we truly want to create diverse, equitable, and inclusive workplaces, we have to stop asking the subjects of inequity to fix a system they didn’t break.

Imagine if instead of retroactively going back to your manager with data on gender and racial bias in performance evaluations, your workplace proactively identified biased decisions to stop inequity before it spreads and multiplies. What if your organization—and all organizations across the world—could do this at scale.

Guess what? It’s already happening. The Fourth Industrial Revolution ushered in a new suite of possibilities to hardwire equity into our organizations. We have the tech tools to achieve equity in this lifetime, and these tools are becoming sharper every day.

And until company leadership picks up these tools and starts running, it’s still on the subjects of inequity to fix a system they didn’t break.

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