This research study explores the challenges the automotive industry faces in simplifying logistics processes amidst intense market competition and rapid changes. Adopting a qualitative approach, this study ensures the accuracy and reliability of the respondents 90 from 103 people, and interviewed individuals of two people. This main objective is to explore optimizing automotive logistics at PT XYZ using scenario planning (TAIDA), identifying inefficiencies, integrating IoT technologies, and proposing tailored strategies for future industry conditions to drive improvements. Data analysis was conducted using the TAIDA models (Tracking, Analysis, Imaging, Deciding, and Acting) to guide the scenario planning process. This comprehensive approach allows for a better understanding and anticipation of future trends. The study highlights the importance of process uniformity for ensuring accuracy and reliability in logistics operations. Four scenarios, A is Incremental Improvement, B is Digital Integration, C is Transformational Change, and D is Strategic Partnership and Outsourcing, were identified, each offering strategic options tailored to the company's objectives. Scenario B: Digital Integration emerged as the most suitable, emphasizing the implementation of Internet of Things (IoT) technologies and digital tools for real-time tracking and automation of logistic processes. These capabilities are crucial for optimizing logistics by improving forecasting accuracy, reducing downtime, and enhancing overall efficiency. However, the study focuses on a specific automotive segment (logistics department) and the generalizability of the results is limited. Despite this limitation, the study provides valuable insights and a clear pathway for automotive companies to optimize their logistics processes through strategic scenario planning and digital integration.