The importance of Digital Twins has increased significantly in recent years. Despite a large number of papers on Digital Twin concepts, Digital Twins are hardly implemented in manufacturing companies, especially in the area of intralogistics. Companies lack know-how, implementation concepts and methods. Thus, the potential of digital twins to improve performance in intralogistics remains largely unused, although, logistics processes have a significant impact on manufacturing performance. For lean, customer-oriented logistics, process thinking and measurement must prevail. Hence, processes should be planned, controlled, and optimized by means of Key Performance Indicators (KPI). Consequently, KPI are the pivotal point for so-called Digital Process Optimization Twins (DPOT). The focus of this paper is to develop an approach to support the planning and implementation of DPOT in the area of intralogistics. For this purpose, a process analysis method as well as an evaluation model for DPOT are presented. The approach analyzes and evaluates the processes for the implementation of DPOTs to improve the intralogistics KPI. Its advantages include the structured assessment of the processes through the DPOTs’ autonomy level and the existing/ respective implementation technologies. This enables an improved process understanding with the aim to uncover weaknesses and to identify optimization potentials for DPOT.