ASN Profiling Strategy: Improving ASN Data Quality towards Data-Driven Talent Management

Abstract

The State Civil Service Agency (BKN) implements the ASN data quality index (IKD) as an integrated instrument to ensure the quality of national ASN personnel data. The dimensions of ASN data quality are completeness, timeliness, accuracy, and consistency. These dimensions provide a comprehensive picture of the quality of ASN Profile Data and serve as the basis for coaching, standardization, and improvement of data governance. The implementation of IKD maintains the integrity of civil service data and enables more accurate and evidence-based ASN talent planning and management processes. This study uses a gap analysis approach to formulate ASN profiling strategies through improving the quality of ASN data. Gap analysis is able to map the differences between actual and ideal conditions objectively so that organizations can set targeted and strategic improvement priorities. The results of the study show that there are four strategic recommendations, namely the formulation of ASN data quality regulations, the structuring of ASN data quality development services and business processes, ASN data quality assistance and development, and the development of services in a shared digital platform.