Subjektivitas Penilaian Kinerja ASN sebagai Tantangan Implementasi Manajemen Talenta
DOI:
https://doi.org/10.31539/be2r9603Abstract
This study aims to analyze the subjectivity of Civil Servant (ASN) performance assessments and their implications for the implementation of talent management from a merit system perspective. The research method used is a qualitative approach with a descriptive case study method in one disguised regional apparatus. Data were obtained through a documentary study of the results of the 2025 Employee Performance Targets (SKP) assessment documents, regulations related to ASN performance management and talent management, and relevant scientific literature. Data analysis was carried out through the stages of data reduction, data presentation, interpretation, and drawing conclusions using the concept of central tendency bias, administrative formalism theory, and the perspective of ASN talent management. The results showed that 98.15% of employees received a Good performance predicate, only 1.85% received a Needs Improvement predicate, and no employees received a Very Good, Poor, or Very Poor predicate. These findings indicate the occurrence of homogenization of performance assessments that reflect central tendency bias, so that the assessment system loses the ability to objectively distinguish the level of employee contribution. This condition has implications for the emergence of talent identification errors, namely errors in identifying high-performing employees, which has an impact on decreasing the accuracy of talent pool mapping, weakening the effectiveness of talent management implementation, and potentially reducing the legitimacy of the merit system. In conclusion, that the objectivity of performance assessment is a primary prerequisite in supporting the successful implementation of ASN talent management because the quality of performance data is the foundation for the process of talent identification, career development, and merit-based personnel decision-making.
Keywords: Civil Service, Talent Management, Performance Assessment, Merit System, Subjectivity
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