De-Bias Your Next Performance Review
The setting where gender bias will hurt your career the most is also the one where it is hardest to detect: in your performance review. This is because performance evaluations usually happen behind closed doors, often in a one-on-one setting. Many women we talk to are surprised that after a great year, they receive lukewarm performance feedback. And while it is clearly frustrating to feel like you’re not getting the accolades and career benefits you deserve, it can be even more frustrating to try to make sense of the feedback you receive. Is it gender bias? Or have you simply miscalibrated? The explanations offered to you for your lower-than-expected evaluation might seem reasonable. In fact, it is hard to be certain that you have experienced gender bias without a perfectly-matched male peer.
In this post, we want to shed light on some of the ways how gender bias manifests itself in performance reviews so you can be prepared any time you sit down with your manager.
How Stereotypes Shape Perceptions of Your Performance
Stereotypes are a belief or expectation about a particular group of individuals. Like all stereotypes, gender stereotypes are beliefs about women and men that are generalized and over-simplified. Every woman has encountered gender stereotypes in her career. Maybe you have heard that -
Women are too emotional to be effective leaders;
Women will always prioritize family over work, so they cannot be trusted with demanding work assignments;
Women lack the aptitude to succeed in STEM fields;
Women are too soft for the rough and tumble worlds of finance or law.
The list is endless. But if you were to list every single stereotype you had ever heard about women and men, you would find that they all fall along two dimensions: warmth and competence. Warmth captures qualities relating to how communal, caring, and nurturing you are, whereas competence captures qualities relating to how much capacity for achievement you have. Warmth and competence are known as the two universal dimensions of social cognition. In simple terms, this means that every single judgment or attribution we make about other people is ultimately a judgment about their warmth or their competence.
Considering some of the commonly held stereotypes about women and men, it should come as no surprise that warmth is stereotypically associated with women, whereas competence is stereotypically associated with men. Indeed, you may have noticed that all of the stereotypes we listed above portray women as lacking the competence needed to succeed at work, while at the same time emphasizing women’s communal qualities. If we were to plot these stereotypes along warmth and competence, it would look like this.
One of the consequences of this “presumed incompetence” of women is that women are held to a higher performance standard than men. In order to be seen as equally competent as a man, women must outperform men. This may sound nonsensical. After all, if a woman and a man both bill the same number of client hours, achieve the same number of sales, or publish equally, how can they be seen differently?
To understand how this is possible, it is important to understand that there is a gap between the data about your performance and how individuals interpret it. Put another way, we don’t respond to the world as it is, but as we see it, and how we see the world is partly determined by gender stereotypes. Stereotypes about the competence of women versus men guide what we look for and what we pay attention to when evaluating others, meaning we pay less attention to data that indicates high performance when evaluating women, while the opposite is true when we evaluate men. Our stereotype that men are competent guides us to look for evidence of men’s high performance, while our stereotype of women as incompetent guides us to look for evidence of women’s low performance.
Stereotypes also help “fill in the blanks”. This means that when we encounter performance data that is ambiguous (for example, an average month of sales in an otherwise good quarter) or subjective (for example, style of client interactions) individuals tend to make negative interpretations about women’s competence, but not men’s. Gender stereotypes help us interpret ambiguous or subjective performance data so that we “see” incompetence when that data is attached to women, but not when the same data is attached to men.
What about the highfliers?
Of course, sometimes women perform highly, so highly that we cannot help but notice. Think about the incredible cases of women who are the first, or the only, ones to achieve something in their field.
High-performing women contradict people’s expectations that women are incompetent. In this situation, people are implicitly motivated to find a way to resolve the inconsistency between what they expect and what they see. One way individuals do this is to find a way to discount evidence of high performance. People subject women to a high degree of scrutiny in performance evaluations to find a reason to discount their performance.
Or, they fixate on an external factor that may explain away women's high performance. One of the most obvious external factors in organizations is also one of the most ubiquitous: teams. In one study, individuals received information about a fictional person working in a team, including their job and associated responsibilities, their CV, and feedback about her or his team performance, which was unequivocally excellent. Everyone received the same information, the only difference was that half the participants read about a woman and half the participants read about a man. They found that individuals who read about the woman judged her to be less competent, as having contributed less to the task and as having displayed less leadership in the team, in comparison to the individuals who read about a man. Remember, the information was exactly the same, the only thing that changed was whether individuals judged a woman or a man. But when they read about the woman, they attributed her high performance to the team whereas when they read about the man, they attributed his high performance to his competence and abilities.
So even when women are unequivocally the highest achievers around, their accomplishments are discounted. When people begrudgingly admit their excellence, this often also goes along with penalizing women on the warmth dimension – calling them “difficult to work with” or complaining that they have an ego.
These are the key biases women face in performance evaluations. So how can you take action? Below is a list of things you can do to reduce the degree of bias you face in your next review, as well as a list of requests to take to your organization.
1. Data is the enemy of stereotyping, so make sure that your organization is evaluating you based on good data. Push your organization to use objective and reliable performance metrics. Objective means that the metric does not rely on individuals’ subjective judgments or interpretations of your performance, but rather reflects facts about your achievements and impact in the workplace. Reliable means that the metric produces consistent indicators of performance across similarly performing individuals. If your organization is not evaluating the questions on their performance rating system for whether they produce equal outcomes for women and men, your organization cannot say that they have a reliable system.
2. Decision-making rules preclude bias. Gender bias tends to creep in when we ask individuals to make subjective interpretations. For example, organizations frequently ask managers to rate the performance of their subordinates on a 1 to 5 scale, with 1 being “below expectations” and 5 being “exceeds expectations”. This is an entirely subjective measure. One way to reduce gender bias is to give managers rules for making performance judgments. These rules should explicitly link the performance standard to the performance evaluation. For example, a rating of 5 means that the individual billed “x” number of hours. Demand that your organization uses rating systems that are anchored to objective and reliable measures of performance. If that is not possible for a particular type of evaluation, ask that these subjective ratings always be explained using specific evidence from your work performance.
3. Refuse bias in-bias out. Many organizations rely on feedback from other stakeholders in performance evaluations, for example, 360-degree feedback, client feedback, student evaluations. Unfortunately, this type of data is usually riddled with gender bias because the inputs are the views of individuals whose views are necessarily affected by gender bias. Ask your organization how they mitigate and correct gender bias in this type of performance data and if there are measures in place, ask your organization for evidence that those measures are effective. Remember, it the responsibility of your organization to use a performance evaluation system that does not discriminate against women.
4. In your performance evaluation, ask for, and provide data. Look at your performance criteria – what data can you produce that shows you have met it? Present this data in your performance review. When your manager makes an evaluation about your performance, ask what data they have based it on and how that links to their evaluation. The idea behind this approach is twofold. First, you are pushing people out of heuristic thinking to deliberative decision-making, which tends to be more reliable and less prone to bias. Second, by asking your manager to articulate criteria, they are more likely to apply them consistently in the future.
5. Claim credit. Women are encouraged to be humble and share their successes with their co-workers. But as you have read, this does not do women favors in performance reviews. The study we described showing that women don’t get credit in high-performing teams comes with one important caveat – women are credited when there is specific and irrefutable evidence of their contributions. This means you should document – in detail – how you contributed to your team’s success and bring this data to your performance evaluation.
Get in Touch
Our favorite part of teaching is the end of class, when students come to chat with us about the content, share examples from their own lives, ask questions about what they are struggling with, and challenge our thinking. We invite you to do the same – let us know how this exercise worked for you, what you are still struggling with, and what questions we can answer in our upcoming podcasts and newsletters.
If you have found this newsletter helpful, please subscribe and share it with your friends.