Purpose: This study provides a strategic analysis of capacity utilization in a manufacturing company by examining workload distribution and transition loss through process mining to facilitate effective decision-making.

Research Methodology: The study was conducted at PT XYZ, a cosmetic manufacturing company in Indonesia that operates a 24-hour, three-shift system. A descriptive quantitative approach was applied using historical event log data from the daily production reports. Event log data from 24,553 production activities (Jan 2020-Mar 2021) were analyzed using Disco (Fluxicon) to visualize production flows, measure transition loss, and evaluate capacity utilization across three shifts.

Results: The results indicated a notable disparity in capacity utilization across shifts, with Shift 1 (50.56%) and Shift 2 (45.15%) overutilized and Shift 3 (4.29%) significantly underutilized. Consequently, the effective production capacity decreased, and the overall operational performance was reduced.

Conclusions: The findings indicate that uneven workload allocation leads to inefficient capacity use, resulting in opportunity and transition loss. Both overuse and underuse during shifts lower the overall production effectiveness. These findings support strategic decisions regarding capacity planning, resource allocation, and performance improvement.

Limitations: This study was limited to a single manufacturing company and relied on manually recorded event log data, which may limit the generalizability of the findings.

Contributions: This study builds on the fields of strategic management and operations management by demonstrating how process mining can be useful in strategic capacity planning and resource allocation decisions.