Well, no. They don't. At all. But that's what the current performance evaluation models (yes, I'm looking at you 360's) will tell you.
The Bias in Performance Reviews
Women tend to receive more constructive (negative) feedback in performance reviews, and it often focuses on unrelated personality traits, emotions, and other aspects not linked to actual performance. This issue is pervasive and has far-reaching consequences. Harvard Business Review highlights that women often receive more critical feedback related to their personalities rather than their work.
The Impact on Career Progression
The current performance models, which are often key components for salary reviews, are actively driving the gender and salary gap. They create fewer opportunities for women to be promoted and contribute to an unequal workplace. When performance reviews are biased, they can undermine a woman’s confidence and career progression, perpetuating a cycle of inequality. A study by McKinsey & Company found that performance evaluations contribute to the gender gap in promotions and pay.
Additionally, research shows that men generally rate themselves higher than women in self-assessments. A study by Psychology Today indicates that men are more likely to overestimate their abilities compared to women. This self-promotion leads to a higher likelihood of getting promoted, as self-assessments often play a role in performance reviews. Consequently, men and women end up on different career paths, with men being more likely to secure leadership promotions. This disparity further perpetuates the gender gap in the workplace.
The Solution: Structured Performance Reviews
So, what’s the answer? Structure. We know that a structured approach to performance assessments can counteract gender bias and ensure fairness and inclusivity. In fact, Harvard Business Review supports the idea people are more likely to rely on gender, race, and other stereotypes when making decisions when there is a lack of structure, using clear definitions and criteria that are consistently applied across all employees.
Implementing a Fair and Inclusive Process
Define Clear Criteria: Ensure performance criteria, and behaviours, are directly related to job responsibilities and outcomes. Avoid vague or subjective measures that can be influenced by personal biases.
Regular Check-ins: Implement regular performance check-ins rather than annual reviews. This helps to capture performance more accurately over time and reduces the impact of recency bias. Gallup reports that regular feedback significantly improves employee performance and engagement.
Training for Reviewers: Provide training for managers and reviewers on unconscious bias and how to conduct fair and objective performance reviews. The Harvard Implicit Association Test (IAT) is a tool that can help reviewers become aware of their unconscious biases.
Use of Data: Utilize performance data to identify patterns and discrepancies. This can help highlight areas where bias may be occurring and provide a basis for making improvements.
Behavioral Anchors: Incorporate Behaviorally Anchored Rating Scales (BARS) to provide clear examples of behaviors that correspond to different performance levels. This helps to reduce subjectivity in evaluations. According to the International Journal of Business and Social Science, BARS can significantly enhance the accuracy and fairness of performance assessments.
The Role of Continuous Improvement
Creating a fair and inclusive performance review process is not a one-time effort. It requires continuous improvement and adaptation. Regularly solicit feedback from employees about the performance review process and make adjustments as needed.
How Asaya Labs is Leading the Change
At Asaya Labs, we are dedicated to solving this problem. Our platform leverages established mechanics, grounded in research, to improve fairness, efficiency, and measurability through structure. We believe in the power of data and structured processes to drive meaningful change in performance evaluations.
Our approach includes:
- Advanced Algorithms: Utilizing sophisticated algorithms to ensure unbiased performance assessments.
- Performance-driven behaviours: Asaya helps you to identify, and measure the critical behaviours that drive performance in each role.
- Comprehensive Data Analysis: Offering in-depth analytics to identify and address biases.
- Structured Performance Pulses: Utilizing clearly defined behaviours, BARS, and peer-to-peer comparison for a fair, efficient, and scalable performance evaluation.
Join the Conversation
By addressing the gender bias in performance reviews, we can create a more equitable workplace where everyone has the opportunity to succeed based on their actual performance, not unfounded biases.
Interested in learning more about creating fair and inclusive performance reviews? Contact us today and join the movement!
