Enhancing Efficiency in Multi-Stage Pharmaceutical Manufacturing: A Process-Based Network DEA Approach

<ns3:p>Background Manufacturing inefficiencies result in substantial financial losses for global industries. The present study introduces a robust Performance Measurement System (PMS) incorporating Network Data Envelopment Analysis (NDEA) to address efficiency challenges in multi-stage manufacturing systems. Methods The study employs a case study approach within the pharmaceutical industry to reveal the pragmatic application of NDEA, which serves as the primary analytical instrument for evaluating performance across diverse production stages. Focusing on the production processes of intravenous (IV) sets, the research aims to highlight how NDEA disaggregates interconnected processes and quantify efficiency measures to pinpoint sources of inefficiencies in particular production stages and actionable insights for operational improvement. Results First, the NDEA-based PMS provides insights to address specific process inefficiencies on the shop floor, providing strategic insights for process improvement. Second, despite its power in pinpointing the source of inefficiency, modelling a process-based PMS faces a challenge as increasing the number of stages in the model presents a trade-off between the accuracy and discrimination power of the NDEA model. Conclusions This investigation contributes to the literature by proposing a data-driven, process-based PMS framework combining methodological rigor and practical applicability. The proposed framework provides managers with actionable guidance to optimize performance and enhance operational efficiency in complex manufacturing settings. The novel framework establishes a pivotal resource for strategic decision-making and fosters process innovation.</ns3:p>