This research concluded that the declining construction performance and schedule delays in the Kucing Liar Fan 7 project, reflected by an average Project Performance Factor of 0.82 and a cost overrun of approximately 10% beyond the available contingency, resulted from the interaction of multiple factors, including design readiness, change control, material planning, communication and coordination, supervisory competency, and constrained underground working conditions. These issues were not caused by a single factor, as Management, Method, Material, People, and Environment collectively accounted for 84.93% of the prioritized relative importance among the six investigated factors. The identified lessons were documented in a Lesson Learned Register and translated into a proposed Controlling Project Management Office (PMO) implementation framework through a four-phase roadmap consisting of organizational assessment and preparation, PMO development and pilot implementation, organizational integration, and continuous improvement. The proposed PMO was designed to strengthen governance, standardization, coordination, and knowledge management without replacing the existing balanced-matrix authority structure of Project Managers and functional departments.It is recommended that PT Freeport Indonesia’s Central Services Division prioritize design readiness and constructability reviews before construction authorization, strengthen project planning beyond analogous estimation through detailed work breakdown structures and integrated risk assessments, implement earned-value-based monitoring with standardized dashboards, and formally establish the proposed PMO to improve governance, communication, and knowledge management across future underground ventilation construction projects. Future research is recommended to evaluate PMO performance following organizational implementation, compare PMO maturity levels across other underground mining projects, and examine the integration of digital project management technologies, such as Building Information Modeling (BIM) and predictive analytics, into project governance.
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