This study investigates the reliability and validity of the 360-degree feedback method by focusing on three primary sources of bias: respondent roles, interpersonal relationships, and individual evaluative styles. Drawing on data from over 15,000 respondents across multiple organizations, it applies a Python-based statistical algorithm to quantify the impact of these biases on competency ratings. Findings reveal that such factors can account for up to half of the variance in assessments. Mitigation approaches include evaluator anonymity, structured training, and correction coefficients. With these measures in place, 360-degree feedback continues to serve as an effective tool for fair and accurate performance appraisal, supporting personnel decisions and sustainable talent management.