Offshore wind energy is rapidly expanding, making efficient logistics and maintenance operations crucial for optimizing performance and controlling costs. This study explores ways to improve the efficiency of logistics and maintenance for offshore wind farms—a key factor in operational cost control. By analyzing public Automatic Identification System (AIS) data from a Danish wind farm, we tracked maintenance vessels to model their routing and scheduling practices. The analysis revealed significant inefficiencies, including suboptimal maintenance sequencing and illogical routing that increase travel distances, fuel use, and operational time. Leveraging these data-driven insights, there is a clear opportunity to streamline vessel logistics. Optimizing routes and schedules can substantially reduce operational costs and the environmental impact of maintenance fleets, supporting the sustainable expansion of the offshore wind industry. This research establishes a foundation for future optimization models and highlights the importance of real-world data analysis in driving more efficient offshore wind farm maintenance.