Reducing Bias in Performance Review Processes

As performance review season approaches, I've been reflecting on a conversation from over a decade ago that still sits with me today. During my review, my manager told me I "needed to work on my confidence." When I asked for clarification, she said, "Think about how [male colleague] would have handled this situation." I can't fully fault my manager - who was herself a woman. We all carry internalized biases that we've absorbed from years of working in systems that often value traditionally masculine behaviors. It's a stark reminder that unlearning these patterns requires conscious effort from all of us, regardless of gender. That moment crystallized something I've observed throughout my career: vague feedback often masks unconscious bias, particularly in performance reviews. "Lack of confidence" is frequently used as shorthand to describe women's leadership styles, while similar behavior in male colleagues might be viewed as "thoughtful" or "measured." Here's what I wish that manager had said instead: 🔹 "I'd like you to take the lead in proposing solutions to the team, rather than waiting to be called on." 🔹"Let's work on defending your decisions with data when faced with pushback from folks." 🔹"I noticed you often preface your ideas with "I think..." Let's practice delivering recommendations with clear rationale and conviction." 🔹"Here are specific techniques to influence cross-functional stakeholders more effectively." As leaders, we are responsible for being intentional and specific in our feedback. Vague critiques like "needs more confidence" or "should be more assertive" without concrete examples or actionable guidance don't help our reports grow – they perpetuate harmful stereotypes. To my fellow managers preparing for year-end reviews: 🔹Be specific about behaviors, not personality traits 🔹Provide clear examples and contexts 🔹Outline actionable steps for improvement 🔹Check your biases - are you applying the same standards across your team? Remember: The impact of your words may last far longer than the conversation itself. #Leadership #PerformanceReviews #UnconsciousBias #WomenInBusiness #ProfessionalDevelopment

"We had to manage out people days after they got promoted." That's what a well-known, 2,000-person company told us in our early days of building Confirm. A company praised for its great culture. After the promotion cycle, a flood of feedback emerged about how problematic some of the promoted people were—serious enough that they had to be fired. That’s what happens when you rely on poor and biased data to assess talent performance. Most promotion decisions rely on a manager’s limited view. But in today’s world of work—where collaboration happens across teams, often remotely—managers don’t see everything. They miss impact that happens outside of one-on-ones or team meetings. Active Organizational Network Analysis (ONA) surveys fix this. ONA analyzes real workplace interactions to identify key influencers, quiet contributors, and hidden problems — things like who employees turn to for advice, problem-solving, and execution, and who is toxic but good at managing up. It gives leaders a clear view of impact beyond titles, tenure, or office politics. When companies use ONA in performance reviews, they: 1) Identify quiet contributor high performers—not just those who are visible to leadership. 2) Reduce bias by making promotion decisions informed by data beyond selection-biased, cherry-picked peers. 3) Retain mission-critical employees by recognizing their contributions early. 4) Improve employee engagement by ensuring talent is evaluated fairly. The old way of evaluating talent is broken. Performance reviews based on manager opinions leave too much room for bias and blind spots. People deserve better. And we are going to keep pushing until fair, data-driven promotions become the norm—not the exception.

Personality Traits Don’t Belong in Performance Reviews Performance reviews should focus on skills, outcomes, and behaviors—not personality traits. An article by Suzanne Lucas for Inc. Magazine highlights a troubling finding from Textio: ✅ 88% of high-performing women receive feedback on their personality compared to only 12% of men. When men do get personality-related feedback, the descriptions differ significantly: Women: "Collaborative," "nice," or "abrasive" Men: "Confident," "ambitious" This disconnect reflects stereotypes that don’t help anyone grow. What NOT to do in performance reviews: ❌ Describe someone as "introverted" (personality-based language). ❌ Focus on general traits like "nice" or "helpful" without linking them to outcomes. What TO do instead: ✅ Address observable behaviors and impact: Instead of: "You're too quiet." Say: "I noticed you didn’t contribute in meetings; your ideas could add value if shared." ✅ Focus on outcomes: Highlight measurable results, goals, and areas for development tied to skills. ✅ Offer actionable feedback: Provide steps to improve performance, like asking someone to prepare discussion points to engage more actively. By focusing on behaviors, outcomes, and skills, reviews can help employees grow without reinforcing unhelpful biases. 🔗 https://lnkd.in/gWTeTw5a What do you think? How does this impact women of color? How can we improve feedback processes to create fairer, more -actionable- reviews? #LeadershipDevelopment #PerformanceManagement #InclusiveLeadership

Dear People Managers, Subject Line: Subtle biases during performance reviews - watch out... Many of you are entering either a mid-year or an annual review cycle in the next 1-2 months and are starting to think about performance ratings for the people on your teams. You’ve done your equity and inclusion training, and you are hopefully well poised to avoid common biases based on age, gender, and race. However here are 3 biases that aren’t quite as commonly discussed, but incredibly easy to succumb to and important to avoid: 🔙 *Past performance bias*: Calibrating someone based on their past performance history instead of assessing THIS performance period. This can either show up as defaulting to an exceeds rating for someone who exceeded expectations over the last few cycles OR defaulting to an achieves rating for someone who achieved expectations in the last few cycles. Sure, there are some folks who have genuine streaks of outstanding performance over long periods of time, but your job Is still to treat every cycle as a fresh opportunity for fair evaluation. 📣*Shiny project bias*: The name says it all. This is where you lean towards the stronger ratings for folks working on the big shiny visible projects, and average ratings for folks working on ‘keep the lights on’ projects. Sure, it could be a chicken and egg situation where strong performers were assigned to the highest stakes work, but what you want to avoid is the ‘scope penalty’ where you evaluate people on the merits of their scope (which they often did not get to choose) and not their performance. Shiny projects also create compounding bias where the people working on them get greater exposure AND the shiny project badge of honor, so be especially careful about this one. 🎆 *Competence bias*: I know this sounds ridiculous, but stay with me for a minute. Competence bias is when you overlook how difficult an individual is to work with or how poor they are at collaborating with others simply because their work - and let’s admit it, sometimes, how they show up - seems SO impressive to you. (#notallcompetentpeople) It’s when you disregard indicators that their partners are having a hard time working WITH them and are often resorting to working AROUND them. When you continue to reward these folks, you send not-so-subtle signals to everybody else about what you truly value. It’s a dangerous and slippery slope for team morale so watch out for this one. ❓What are other not so commonly discussed biases that you would add to this list? ❓

We all want to reward employees fairly, yet decades of research--and for many people, their lived experience--show that bias persists. In other words, for the same performance, people earn less or more due to managerial error. New research from researchers at our Stanford VMware Women's Leadership Innovation Lab shows that many interventions are only targeting half the problem. Bias shows up both in how managers describe (view) performance as well as how they reward (value) behaviors. Viewing biases often show up in how performance is described differently based on who is performing it. Men’s approach may be called “too soft,” thus “subtly faulting them for falling short of assertive masculine ideals.” Valuing biases can show up as the same behavior being rewarded when men perform it but not when women do. Examples from the research show that men benefitted when their project specifics were described, whereas women were not. So the same description and behaviors showed up in reviews, but they were only rewarded on men’s. What can be done to curb biases? ✅ Standardize specific guidelines for how managers should view employee behaviors and assign corresponding rewards when giving employees feedback and making decisions about their careers. ✅ Help managers catch bias in both viewing and valuing. ✅ Monitor these impacts from entry level to executive leadership. It turns out that as the criteria shift, so can the way these biases work. A key lesson from our research shows that the work takes discipline, consistency and accountability. These steps may seem like a lot of “extra” work, but at the end of the day, managers also benefit when they weed out biases and fairly promote the most talented employees. Article by Alison Wynn, Emily Carian, Sofia Kennedy and JoAnne Wehner, PhD published in Harvard Business Review. #diversityequityinclusion #performanceevaluation #managerialskills