Building up Resilience in a Pharmaceutical Supply Chain through Inventory, Dual Sourcing and Agility Capacity. (December 2017)

• Record Type: Journal Article
• Authors: Lücker, Florian; Seifert, Ralf W.
• Is Part Of: Omega. Volume 73(2017:Dec.)
• Page Start: 114
• Page End: 124
• Publication Date: 2017-12
• Subjects: Risk -- Operations management -- Inventory control -- Application; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2017.01.001
• Languages: English
• ISSNs: 0305-0483

Abstract

Abstract: This paper is inspired by a risk management problem faced by a leading pharmaceutical company. Key operational risk mitigation measures include Risk Mitigation Inventory (RMI), Dual Sourcing and Agility Capacity. We study the relationship between these three measures by modeling the drug manufacturing firm that is exposed to supply chain disruption risk. The firm determines optimal RMI levels for assumed Dual Sourcing and Agility Capacity. We quantify the decrease in RMI levels in the presence of Dual Sourcing and Agility Capacity. Furthermore, using an example, we analyze RMI, Dual Sourcing and Agility Capacity decisions jointly. It turns out that RMI and Agility Capacity can be substitutes as long as no Dual Source is available. Once the Dual Source is available, Agility Capacity and Dual Sourcing appear to be substitutes. We further show that for long disruption times, the optimal Dual Source production rate may decrease in the disruption time. Within our modeling framework, we introduce an operational metric that quantifies Supply Chain Resilience. Supply chain disruptions can have a severe business impact and need to be managed appropriately. Abstract : Highlights: We introduce a Resilience measure that allows for a holistic alignment of three mitigation measures. We quantify the decrease of inventory in the presence of a Dual Source and Agility Capacity. We find conditions when Agility Capacity can be substituted with either RMI or Dual Sourcing. We show that the production rate of the dual source may decrease in the disruption time for long disruption times.