A simulation-based logistics assessment framework in global pharmaceutical supply chain networks

Drug manufacturing firms that operate in a globalized ecosystem are subject to a myriad of complex and simultaneous uncertainties. Such uncertainties may have a detrimental impact on firms' operational performance if not appropriately addressed. A firm's ability to react to different degrees of risk can be enhanced by reconfiguring its logistics components. However, selecting the appropriate combination of logistics components that preserve service levels in an unpredictable environment is challenging for global pharmaceutical manufacturing firms. The effects of various levels of supply and demand uncertainties interacting concurrently in a multi-echelon capital-intensive supply chain environment restricted by different regulatory frameworks further exacerbate these factors' cumulative effects. In this paper, we develop a simulation framework capable of capturing these complexities and exploring various combinations of logistics levers to examine the impact of different policy variables on these firms' operational performance subject to varying volatility levels. The simulation framework developed in this paper considers standard logistic practices employed by one of the world's leading biopharmaceutical manufacturing companies. Guided by Subject Matter Expert theoretical information, we have structured experiment designs using the Taguchi Orthogonal methodology and analyzed the statistical significance of different policy variables using ANOVA tests.