Hurricane Helene devastated the Baxter manufacturing facility in Marion, North Carolina, taking offline its capacity to manufacture saline and other medical materials. As of November 1, the facility is recovering capacity. This unexpected loss of capacity once again calls attention to the importance of geographic diversification in supply chain management. It is not so long ago that supply chain and logistics operations worldwide were caught off-guard as the pandemic swept, first through China, then through the rest of the world, with manufacturing plants clustered in China grinding to a halt. Ports struggled to operate at normal throughput, most notably the lengthy queues outside the ports of Los Angeles and Long Beach in Southern California. Now, Helene’s damage to the Baxter International plant has significantly worsened already existing hospital shortages of saline, along with other solutions used in treating patients with kidney failure.

The Hidden Cost of Geographic Concentration

Organizations that build their manufacturing or distribution capacity concentrated in one area will often justify their decision based on economies of scale, simplified logistics, reduced inventory, and easier management oversight. This view is somewhat short-sighted, given that a localized event – whether it’s a natural disaster, political unrest, or even a prolonged power outage – can bring production to a complete halt, potentially disrupting the entire supply chain.

Consider the devastating effects of the recent hurricane Helene in, of all places, the mountainous area of western North Carolina, curtailing the capacity of one major manufacturer of hospital supplies. This event demonstrates how geographic concentration can transform a local disaster into a global supply crisis. Sudden loss of production capacity can have lasting consequences for any manufacturer, including:

 

Network Modeling: A Data-Driven Approach to Geographic Diversification

Supply chain practitioners know there is a real benefit in geographically dispersing an organization’s production capacity and/or suppliers. They can (and should) use network modeling to determine the best locations for plants, including the potential impact of shutdowns on inventory levels and customer service, and considering variables such as:

 

The modeling process involves doing a baseline analysis of current network performance and risks. Various scenarios are generated to create potential network configurations with a cost-benefit analysis of the associated risks for each. The modeling process is designed to arrive at an optimized manufacturing structure that balances costs, service, and risks. Once a future-state network scenario is aligned upon, simulations can be used to understand the implications of shutdowns to finished-goods inventory levels throughout the network, and how long a manufacturer can supply its customers with its manufacturing capacity offline.

The Data Driven Supply Chain team has experience using modeling to assist clients in examining potential dangers associated with concentrated manufacturing and distribution capacities. One example involved helping an agricultural segment leader that had been using the Port of Houston for a substantial portion of their Gulf Coast and East Coast imports. Our consulting team identified this as a vulnerability, since a major hurricane was predicted to strike Houston within the next ten years, exposing our client to network disruption. As a result of the analysis, changes were made to their first-mile import network, incorporating the use of additional East Coast ports.

Conclusion – Balancing Cost and Risks

Geographic diversification of manufacturing capacity is no longer optional in today’s volatile business environment. While diversification may result in higher operational costs, these should be considered insurance premiums against catastrophic disruption. The key is to approach diversification strategically, using network modeling and simulation to more closely evaluate the future-state network.

In manufacturing, geographic diversification is an imperative, and network modeling can help.