Tips for Mitigating Bias in Performance Reviews

Cognitive biases sneak into our everyday lives, but in the workplace, the effects of biased decision-making have heightened consequences — people’s careers and livelihoods. Performance management cycles are where the crux of decision-making around promotions and pay raises occurs, making biased performance reviews a direct pathway to inequitable advancement tracks.

When unstructured, performance reviews perpetuate bias, but when structured properly, they become powerful tools to combat it. The difference between these two outcomes isn’t just about fairness — it’s about engagement, retention, and business performance.

Below, we look at the types of bias that show up in performance appraisals and offer actionable suggestions to combat them.

{{rich-takeaway}}

Understanding Bias in Performance Management 

Bias in performance reviews isn’t about intentional discrimination, but rather the systematic errors in judgment that affect how we evaluate others. These biases operate like insidious mental shortcuts that influence our decision-making, often without our awareness. 

Performance appraisals are a point of focus when we talk about bias because they’re the process through which promotions, pay raises, and opportunities for professional development are decided. And yet, “When you go into a performance review, you should assume there is bias,” said Nadia Eran, fractional HR leader and founder of Future in Work, an HR consulting firm.

Yet even after decades of research and strategy development, eradicating bias remains an elusive goal. Part of this persistence stems from the slippery nature of how biases show up in the workplace and the many forms they take. Here’s a non-exhaustive list:

• Recency bias: Overemphasizing recent performance while overlooking behaviors and achievements from earlier in the review period.
• Halo and horns effect: Allowing a positive trait (halo) or negative trait (horns) to influence an overall assessment.
• Gender bias: Treating a person differently because of their gender identity or expression.
• Racial bias: Applying different standards or using different language to describe people because of their race.
• Affinity bias: Favoring employees with whom you share a similar background, interest, or personality.
• Anchor bias: Allowing a single perception, sometimes one’s first impression, to disproportionately influence later assessments.

The Cost of Biased Performance Reviews 

Biased performance reviews don’t just affect individual employees. They create ripple effects throughout the organization that impact everything from engagement and retention to the employee experience and bottom line. 

• Financial impact: Organizations with biased performance management systems may experience higher turnover rates, particularly among underrepresented groups. According to the Society for Human Resource Management (SHRM), the cost of replacing an employee averaged nearly $4,700 in 2022. However, that same article suggested the total cost could be as much as four times the position’s salary. That means bias-driven turnover directly affects the bottom line.
• Employee engagement and morale: When employees perceive unfairness in how performance is evaluated, engagement wanes and their trust in leadership and the organization’s integrity erodes. But when employees are engaged, they are more productive, profitable, and likely to stay with their organizations, Gallup research shows.
• Diversity, equity, inclusion, and belonging (DEIB) implications: Biased performance reviews disproportionately affect marginalized groups and create barriers to advancement that compound over time. People of color, women, and people with disabilities, among others, may receive different types of feedback, face different performance standards, or find their contributions undervalued compared to their peers.
• Legal and compliance risks: Systematically biased performance reviews can create long-term risk exposure for the organization. When promotion and compensation decisions consistently disadvantage certain groups, companies become vulnerable to discrimination lawsuits and scrutiny.
• Wasted human potential: When talent isn’t accurately identified and developed due to bias, organizations miss massive opportunities for innovation, growth, and competitive advantage. The cost isn’t just what bias takes away — it’s also what could have been achieved with fair, accurate performance evaluations. 

{{rich-highlight-3}}

Strategies to Mitigate Bias in the Performance Review Process 

While eliminating bias entirely may be impossible, organizations can implement systemic approaches to reduce its impact. The key lies in prevention through structure, training, and gathering multiple perspectives. 

“Eliminating bias or mitigating it in performance reviews is really hard,” said Liz Kofman-Burns, PhD, cofounder of diversity, equity, inclusion, and belonging consulting firm Peoplism. “The best bet is to try to prevent it in the first place.”

Bias loves ambiguity...Structure creates a shared standard, a shared language that we can all rally around.

Use structured review systems.

Structure is the enemy of bias. When performance review processes rely on clear, consistent frameworks, bias has fewer places to hide.

“Bias loves ambiguity,” Eran said. “Structure creates a shared standard, a shared language that we can all rally around to make sure that we have inter-rater reliability, which means that it’s not just me evaluating. If somebody else had this information, they would also evaluate it in the same kind of way,” she added.

Structured systems help managers: 

• Apply uniform criteria that were established before the review period begins. 
• Use consistent formats and rating scales for all team members. 
• Document feedback throughout the year to combat recency bias. 
• Support more equitable feedback and ratings with metrics and data points.

Performance review software and templates play a crucial role in maintaining this consistency across the organization.

Train managers to give better feedback.

Effective bias mitigation begins with comprehensive manager training, but the approach needs to go beyond traditional unconscious bias workshops.

Kofman-Burns emphasized that HR should train managers on how to give better feedback in general, irrespective of specific bias training. “People are afraid to give critical feedback to people who don’t look like them, which means they don’t provide the kind of feedback that’s needed to actually improve,” she explained.

This inclination to withhold constructive feedback from those who differ from us is called “protective hesitation,” and it needs to be overcome to ensure everyone benefits from feedback. 

For HR teams that don’t know where to start, frameworks like the Situation-Behavior-Impact (SBI)™ model or the COIN (connection, observation, impact, next steps) model support managers in providing actionable, timely feedback that is linked to outcomes. The value of these approaches in combating bias lies in their structure, which serves as a bulwark against our natural tendency to default to bias-driven evaluations.

Collect feedback from several sources.

Relying solely on a manager’s perspective creates a narrow evaluation channel, which makes the appraisal more susceptible to individual biases. By implementing 360-degree reviews and peer feedback, organizations get multiple perspectives that can balance each other out.

According to Sunaina Lobo, strategic advisor at AI compliance company TrustMe.ai and a former chief people officer, “The most accurate predictor of someone’s ability to operate at the next level is a peer review. The peer line is the most accurate predictor of whether this person will actually be promotable.”

Why are peers such reliable evaluators? “You are most yourself with your peers,” Lobo explained. “With a manager, you’re trying to manage up…Your peers are the people who see you as who you are.”

Lobo said organizations can implement peer reviews gradually, starting as an opt-in process and eventually making them a standard part of the performance evaluation cycle once employees understand their value. This approach allows organizations to build trust and competency in peer evaluation while maintaining the stability of the current review process.

Calibration is the best system we have for ensuring we’re mitigating bias and aligning and using the same definitions.

Hold calibration meetings.

Calibration is the process of reviewing and adjusting performance ratings to ensure rating criteria are being applied consistently across the organization. Because managers can interpret rating scales differently, these discussions — which create a collective understanding of ratings and push managers to justify their assessments — serve as a final check against bias during performance reviews. 

“Calibration is the best system we have for ensuring we’re mitigating bias and aligning and using the same definitions across the organization,” Amanda Myton, head of learning and development at software development company Snowflake, said in a Lattice article about ratings in performance reviews. The calibration process is especially important for decisions around pay raises and promotions, where bias can have the most significant impact on employees’ careers. 

Calibration meetings are also a moment to push for specificity and clarification. Lobo said that “great guy” is a term that catches her attention and signals she needs to push for more information about that person to justify their rating. “How have they performed and what have they accomplished versus being someone who is well-liked?” she asked. 

{{rich-highlight-2}}

The Role of Technology and AI in Reducing Performance Review Biases 

The growing presence of generative AI in our professional lives has intensified both opportunities for and concerns about the technology’s role in performance management. AI algorithms can risk replicating and amplifying disparities that exist in the data they’re trained on, but they also offer the potential for bias reduction when used correctly. 

Technology can be leveraged to create more objective performance management processes in several key ways. 

• Flagging bias in language and ratings: According to a 2025 peer-reviewed study, “AI systems can analyze performance reviews to identify patterns of biased language or scoring, providing insights into potential areas for improvement.” For example, a well-meaning performance appraisal comment might focus on personality traits rather than specific behaviors and outcomes. AI tools can scan comments for bias and suggest more fact-based, actionable alternatives that focus on performance rather than personal characteristics.
• Incorporating comprehensive performance data: When AI is integrated into your performance software, it can create a more holistic picture of performance by weaving in examples from one-on-ones, goals, and more. Opt for tools that make it possible to combine multiple data sources to reduce reliance on memory and support a more evidence-based evaluation of an employee’s overall performance.
• Identifying organizational patterns: AI algorithms can detect patterns of bias in performance evaluations, promotions, and compensation across the organization, enabling targeted interventions to address systematic issues. As Lobo noted, “With the right tools, we’ve gotten to the point of being able to say, here’s who the data is telling us should be next in your promotion pipeline.” 

{{rich-highlight-1}}

How Lattice Supports More Equitable Performance Reviews

Lattice’s AI-driven approach to performance management helps address the challenges of bias in performance reviews by providing the structure, data, and insights necessary for more fair and evidence-based evaluation processes. 

• Continuous feedback features reduce recency bias by supporting continuous performance conversations throughout the performance period.
• Goal-setting and tracking capabilities provide objective performance data that grounds evaluations in measurable outcomes rather than subjective impressions.
• Calibration tools help managers align on fair standards by providing frameworks for comparing performance ratings across teams and departments.
• Analytics capabilities spot potential bias patterns in ratings and alert HR teams to insights to improve fairness. 
• AI-powered insights complement human judgment by offering suggestions for more objective language and highlighting potential areas of concern in performance evaluations.
• Integration capabilities create a holistic view of employee performance by combining feedback, goals, and performance data in a single platform.

Ultimately, Lattice supports both the what and how of performance assessment by providing structure for what to evaluate, and guidance for how to evaluate it fairly.

Starting the Journey to Combat Bias

Combating bias in performance reviews requires ongoing commitment and continuous improvement. It’s no easy task. The strategies outlined — structured systems, comprehensive manager training, multiple feedback sources, calibration processes, and thoughtful technology integration — work best when implemented as part of a holistic approach to combat bias. 

Keep in mind that achieving less-biased performance management isn’t a destination but an ongoing journey of learning, adjusting, and improving. With the right combination of structured frameworks, technology support, and organizational commitment, HR leaders can transform performance reviews from potential sources of inequity into a tool for more fair, equitable, and effective talent development.

The question isn’t whether bias exists in your performance reviews — it almost certainly does. The question is what you’re going to do about it. 

Start by scheduling a demo to explore Lattice today.