Due to the high volatility of market demand and an increasing individualization, traditional textile manufacturing companies are required to carry out efficient production planning and scheduling (PPS). Highly complex manufacturing operations and a heterogeneous landscape of production equipment in terms of age, technology and automation level as well as a low level of digitalization hamper transparency in PPS, even though the demands on delivery reliability, lead times and flexibility are continuously increasing. Therefore, decision-making is typically based on fragmented production data and practical knowledge of individual workers in daily production that makes overall production opaque. To overcome this, the authors conducted a detailed process analysis of a medium-sized textile manufacturer and carried out a simulation study to improve daily production routines on the shop floor. This included the analysis of the heterogeneous production data, the management of missing data and the decision to implement a discrete-event simulation model. The simulation study focused on testing isolated production strategies, identifying potential improvements in terms of organizational processes, detecting data leaks as well as designing a model for discrete-event simulation (DES). As a result, a roadmap to establish a seamlessly integrated hardware and software infrastructure was derived. This consists of a catalogue of best practices for lean production as well as an increased level of digitalization on the shop floor and considers the current state of digitalization of the company.