ENHANCING LOGISTICS PERFORMANCE THROUGH DATA GOVERNANCE AND PROCESS OPTIMIZATION FOR COST REDUCTION AND DELIVERY TIME IMPROVEMENT

Abstract

This research enhances logistics performance at PT. XYZ Indonesia by addressing high costs and delivery inefficiencies through data-driven strategies. It examines how structured data governance, process optimization, and visualization can jointly support cost reduction and delivery accuracy. A mixed-method approach was employed, integrating CRISP-DM for data analytics and the DAMA-DMBOK framework for data governance. The study established a governance structure, conducted simulation-based optimization of logistics processes, and implemented a BI dashboard for real-time monitoring. Focus Group Discussions (FGDs) were conducted to validate outcomes and gather stakeholder perspectives. Findings reveal that governed data significantly improved logistics visibility and analytical reliability. Simulations demonstrated cost savings of 74%–76% across two shipment scenarios, while delivery delays dropped from 24% in May 2025 to 6% in July 2025, reflecting an 18% improvement in delivery accuracy within two months. The dashboard further enhanced responsiveness by enabling proactive issue detection and timely decision-making. The study concludes that integrating data governance with process optimization and visualization provides a practical framework for organizations seeking to reduce costs, improve delivery performance, and strengthen competitiveness.