Workload disparities in police organizations threaten the effectiveness of internal oversight functions. The Regional Inspectorate (Itwasda) of Gorontalo Regional Police faces an imbalanced distribution of workload across sections reaching 35%, with indications of overload in some personnel and underutilization in others. This study aims to analyze the effectiveness of Workload Analysis (WLA) implementation as a human resource management instrument at Itwasda Gorontalo Regional Police, identify supporting and inhibiting factors, and formulate strategic recommendations for optimizing human resource management. The research methodology employs a descriptive qualitative approach with data collection techniques through in-depth interviews, participatory observation, and documentation studies. Data analysis was conducted using the Miles and Huberman interactive model, with data validity ensured through source and method triangulation as well as member checks. Research findings reveal significant workload disparities: Itbid Section (138% - overload), Dumasan Section (142% - overload), and Renmin Section (76% - underutilized). WLA implementation successfully reduced disparities from 66% to 23% following task redistribution, with a 35% increase in organizational efficiency and 20% improvement in personnel job satisfaction. Supporting factors include leadership commitment, data availability, and quality human resource capacity. Main constraints are limitations in integrated information systems, personnel resistance to change, and limited technical understanding of WLA methodology. The study concludes that WLA implementation effectively addresses workload disparities and enhances organizational performance through proportional task redistribution. Strategic recommendations include strengthening leadership commitment, continuous training, digital information system development, effective change management, and replicating best practice models to other police units to achieve professional and accountable human resource governance.
                        
                        
                        
                        
                            
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