A SCOR-based analytical coordination model for an integrated supply chain in a pharmaceutical company

An analytical coordination model (ACM) for a pharmaceutical multinational corporation (MNC) supply chain is presented in this paper. To improve the supply chain performance, we study the coordination among the supply chain parties from the strategic to operational levels. The Supply Chain Operations Reference (SCOR) model is adopted to support the MNC to choose and refine the supply chain management strategies. An optimal integer-ratio inventory coordination (IIC) policy is devised to coordinate the inventory replenishment at the tactical and operational levels. By combining the SCOR model and IIC policy, a systematic approach is proposed. We focus on the derivation and analysis of the total operational cost (TOC) of the supply chain based on cost performance metrics across three levels of the SCOR model version 10. The TOC is proven to reach its global minimum after the integer constraint is relaxed. The findings reinforce the proposition that the adoption of an ACM based on the metrics of the SCOR model is promising to assist decision makers in improving the supply chain performance. Numerical experiments are conducted to show how to compute the optimal TOC in practice. The computational results demonstrated that the TOC savings through the SCOR-based ACM are significant. © 2019 University of Cincinnati. All rights reserved.