Integrating Performance Evaluation with HR Analytics Using Analytic Hierarchy Process
Performance evaluation of an employee is a procedure to assess success of an individual in achieving assigned goals. But, the problem arises when evaluation is based on perceptions rather than reality. Application of analytics in human resource management (HRM) is still a new idea to most of the organizations in India. This research paper integrates analytics with performance evaluation process at a branch of a private sector bank in India using Analytic Hierarchy Process (AHP). In first part of this research, a performance evaluation committee was created which comprised of the bank manager, general manager and human resource (HR) manager of the bank. This committee identified performance evaluation criteria and sub-criteria for performance evaluation. Then, final weights for each criteria and sub criteria were calculated by researcher through combining responses on data collected using AHP questionnaire. These weights were not disclosed to any of the committee member. In second part of this research, performance appraisal discussions were conducted for branch employees in which bank manager evaluated employees qualitatively. Performance evaluator was responsible only for individual qualitative evaluation and not for rating or ranking of employees. These qualitative performance evaluations for employees were processed through AHP for determining final evaluation score for each employee and employee ranking among peers. The study contributes to existing literature on performance evaluation by introducing a new approach for conducting performance evaluations using HR Analytics. The study also has practical implications as it reduces bias as evaluators were not aware of final weight of evaluation parameters and implication of their qualitative decision made for each parameter on employee’s performance evaluation. They were just responsible for making qualitative evaluation which was later converted to local and global AHP score using calculated weights.