Performance Review Score Normalizer
Adjust raw performance scores to account for manager rating tendencies. Get fair, comparable scores across your organization.
Why do we need to normalize performance scores?
Managers have different rating tendencies - some are harsh, some lenient. Without normalization, an average performer rated by a tough manager gets penalized vs the same performance rated by an easy manager. Normalization ensures fair, comparable ratings across the organization.
What is the difference between normalization and calibration?
Normalization adjusts individual scores based on rating distribution. Calibration aligns ratings across teams by comparing employees against common standards. Both work together: normalize individual scores first, then calibrate across teams for consistent evaluation.
What is a bell curve in performance management?
A forced distribution that limits how many employees can receive top or bottom ratings. Typical: 20% top performers (exceeds), 70% solid performers (meets), 10% underperformers (needs improvement). Some companies are moving away from this due to criticism, but it helps prevent grade inflation.
How do you handle small teams in normalization?
For teams under 10, use broader organizational data or manager benchmark data. If data is insufficient, apply conservative normalization or skip. Small sample sizes produce unreliable normalized scores. Consider using manager averages across multiple review periods for stability.
What is the best rating scale for performance reviews?
5-point scale is most common (1-Poor to 5-Exceptional). Some use 3-point (meets/doesn't meet/exceeds) or 7-point for more granularity. Whatever scale, ensure managers are trained on what each level means. Anchor descriptions reduce rating variance significantly.