As the post-pandemic summer is welcomed in with barbecues, pool parties, and evenings on the porch, procurement pros must prepare for another summer ritual: the hurricanes that disrupt supply chains every year.
In a recent webinar, Resilinc’s Chief Product Officer, Sumit Vakil, and Director of Product, Sandeep Ramachandran, discussed best practices for hurricane preparedness, including how new uses of artificial intelligence and machine learning are helping to offset disruption.
The Atlantic hurricane season began June 1 and will run through November 30, while in the Pacific, typhoons (hurricanes by another name) can occur throughout the year but do so most frequently from May through October. Despite the seasonal nature of these storms, Vakil and Ramachandran emphasized that—like all types of supply chain risks— companies should prepare for hurricanes well before they occur.
Drawing on the experiences of Resilinc customers, Vakil outlined major steps to harden a supply chain against destructive hurricanes. “Ideally, supply chains should be mapped to the component level, with up-to-date data on every factory, warehouse, distribution center and other location that touches your parts and materials,” he said.
Another best practice is to analyze disruptions and impacts from past hurricanes and typhoons to identify the links in the supply chain that are most likely to break in a future weather event. “Then companies put in place strategies to mitigate the high-risk areas,” said Sumit.
While every Resilinc customer’s supply chain data is private and confidential, Vakil drew on Resilinc surveys to point out common reasons that suppliers are disabled by hurricanes. “Most of these are weaknesses in business continuity plans,” said Vakil. “Some of the statistics are frankly very scary.”
“Thirty seven percent had no backup power, yet power outages are one of the most common results of destructive hurricanes and typhoons,” said Vakil. “Seventy three percent were not equipped with a satellite phone, which is alarming because when electric grids fail, so do cell towers.”
For suppliers without satellite phones, Vakil suggested OEMs consider equipping them with satellite phones for the duration of hurricane season. “Think about the potential impact of a disruption compared to the cost of a satellite phone,” he said.
Suppliers with no backup power system are in many cases small firms “that can’t afford a generator,” said Vakil. For these firms, OEM customers can consider incentives to create backup power systems. “And make sure they have trained staff to operate the system and fuel replenishment contracts. Our surveys show that many suppliers with generators do not take these important measures.” (For more on collaborative risk management in supply chains, see this post: Why Supplier Collaboration is a Win-Win Strategy)
Some supply chain vulnerability will remain even after the best proactive work to manage risks. But according to Vakil and Ramachandran, AI and machine learning systems now enable supply chain staff to respond more nimbly and effectively to hurricanes when – and ahead of when – they occur. “Resilinc’s HyperAutomation system provides predictions for what could go wrong and what could be impacted during hurricane season, then it provides prescriptive guidance on what to do,” said Vakil.
For example, Resilinc’s Predictive Purchase Order (PO) On-Time-Delivery engine leverages AI to combine historical data, such as the on-time delivery history of specific suppliers, with real-time intel on a storm’s track and impacts provided by Resilinc’s EventWatch. It also queries suppliers in the hurricane track about their status and—if they’re impacted—their estimated time to recovery.
“The result is an automated prediction, displayed on the customer’s dashboard, about which suppliers are likely to delay PO deliveries of what parts and by how long,” said Ramachandran. “And this is all linked to the customer parts that are at risk, the products those parts are needed for and the revenue at risk from a disruption or delay in supply.”
Vakil added that by automating mundane tasks, the AI system frees up human experts to “focus on things like locking up shipping to reduce expediting freight costs.”
He also noted that well before hurricane season, “supply chain AI can be used to estimate—based on suppliers’ sites and logistics, the historic impacts of hurricanes in the region and other data—how to adjust safety stock intelligently to cover the most plausible scenarios.”
“This can result in lower inventory, more cost savings, better investment returns and even a healthier balance sheet,” concluded Vakil.