Supply chain efficiency and resiliency: Two sides of the same coin

John DeSarbo
4 min readNov 21, 2022

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Companies have long sought to build efficient supply chains that fulfill customer demand with minimal operational expense. Over the last decade, supply chain strategists innovated to achieve this goal through aggressive network design, process reengineering and adoption of new technologies. Supply chain strategists centralized production in geographies with low labor costs and rationalized supplier networks to gain economies of scale. Quick response inventory management and just-in-time production reduced inventory carrying costs and working capital requirements. Sophisticated warehouse management and transportation management systems enabled optimization of logistics and distribution operations. The upside of these improvements was record corporate profits in good times. The downside was brittle supply chains that failed in the face of the disruptions we experienced over the last three years. Anyone who struggled to find household products at the outbreak of Covid or experienced sticker shock shopping for a car this year felt the pain.

To quote Bob Dylan, “the times they are a-changing”. Given the extreme disruptions to the global supply chain in recent years — the COVID-19 pandemic, the war in Ukraine, the Suez Canal blockage and more — companies are refocusing on supply chain resiliency in anticipation of future disruptions. In corporate boardrooms, there is renewed interest in supply chain risk management. Leadership teams are more willing to take on higher costs in exchange for a cushion to absorb sudden changes in supply and demand. Consequently, supply chain strategists are refocusing on stability and responsiveness, adopting new performance measures, such as two key metrics promoted by MIT Professor David Simchi-Levi to help companies evaluate supply chain resiliency: time to recover (TTR), which is the time it would take to fully recover after a disruption, and time to survive (TTS), which is the maximum time that supply can keep pace with demand after a disruption.

This renewed focus on resiliency will undoubtedly lead to changes in supply chain strategy. Production will be decentralized and moved onshore. Companies will adopt redundant supply sources. Inventory levels will increase as safety stock guidelines are adjusted. Goods will flow to customers through a more balanced mix of transportation modes. The result will be more resilient supply chains better able to weather the inevitable future disruptions. And of course, higher operational costs, which, considering recent inflationary pressures and a slowdown in global demand, may not be the most appetizing outcome for the CFOs in the room.

So, are supply chain managers doomed to making coin flip decisions when setting strategic priorities — “heads” efficiency or “tails” resiliency? Or is it possible to prepare for future disruptions without adding excessive operational costs?

Achieving both efficiency and resiliency in the real world

Industry leaders are proving it is possible to improve supply chain efficiency and resiliency simultaneously. These companies utilize advanced analytics to identify and mitigate operational risk and proactively prepare for inevitable disruptions.

One manufacturer who is ahead of the curve in managing supply chain risk is Procter & Gamble (P&G). Over a decade ago, P&G centralized disaster preparation for more than 300 facilities around the world. By creating a central “decision-making clearinghouse”, P&G coordinated response to major disruptions that severely impact one facility and have ripple effects across the supply chain. To enable this central function, P&G partnered with Kinaxis to develop a digital representation of its supply chain that simulates potential disruptions and plans the most cost-effective response. When disaster strikes, P&G has predetermined the most cost-effective corrective action. This capability enables P&G to respond to major disruptions faster than competitors without adding unnecessary redundant costs. For example, when Hurricane Harvey devastated Texas and Louisiana in 2017, P&G proactively transferred resources and people from its Louisiana Tide plant to other locations ahead of the storm in order to maintain uninterrupted flow of product to customers.

BP has similarly invested in advanced analytics to improve supply chain efficiency and resiliency. BP developed a simulation and surveillance system called APEX that enables optimization of production operations across the world. Apex provides a digital twin (i.e., virtual copy) of each BP production facility. The system integrates real time data gathered from sensors and utilizes machine learning to determine the optimal flow of raw material through production to maximize efficiency, quality, and yield. APEX also simulates potential disruptions and determines the ideal corrective actions, enabling BP engineers to evaluate “what if” scenarios and respond quickly to production irregularities. APEX has not only improved efficiency — during the first year of implementation, BP produced an extra 30,000 barrels of oil and gas a day — but has helped BP predict where problems are likely to occur before they have major impacts on production.

Best practices: Building a resilient supply chain…efficiently

For too long, supply chain professionals have viewed efficiency and resiliency as zero-sum objectives. Advanced analytics are increasingly enabling industry leaders to pursue both goals simultaneously. By gathering data from sensors across the supply chain, synthesizing this information with external data to help predict disruption and using AI/ML to better anticipate and proactively mitigate risks, supply chain leaders are achieving resiliency efficiently. These leaders are redesigning their supply chains to increase agility and restructuring operations to minimize costs and respond more quickly to disruptions. To learn more about the best practices companies are utilizing to achieve these goals, read this ZS article about building resilient supply chains.

This post contains contributions from Mark Spencer.

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