External risk monitoring and inventory sizing in supply chain disruption mitigation

Abstract

As AstraZeneca's product portfolio becomes increasingly complex, its supply chains must evolve in parallel. These supply chains operate in an environment of ever-present external risks such as factory fires, geopolitical disruptions and natural disasters. Such risks might manifest as disruptions which could jeopardize the health of those who depend upon AstraZeneca's life-saving medicines. Accordingly, there is a need to improve proactive planning and reactive risk decisions to maintain service levels in such an environment. This thesis presents an approach which enhances both risk planning decisions and reaction to disruptive events. The approach consists of a third party software solution to provide better supply chain visibility, increased risk awareness, and faster disruptive event notification, as well as a stochastic nonlinear optimization model to support inventory reductions. Both approaches improve risk planning decisions, while the software approach also supports reactive decision-making as disruptive events unfold. For a single brand, this thesis model shows that current risk mitigation inventory sizes across its supply chain can be reduced by over 50% while maintaining the target service level. The cost savings estimated for a reduction of this magnitude are at least $20M for one brand alone. Simultaneously, the software uncovers previously unknown sub-tier suppliers and highlights tier one dependencies. Adoption of this thesis' recommendations can improve risk planning and decisionmaking within AstraZeneca's supply chains while greatly reducing mitigation inventory costs.