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Three Ways AI Can Help Companies De-Risk Supply Chains And Capture New Opportunities During Hurricane Season

Meredith Mejia • June 20th, 2023.

Ai in shipping logistics

Hurricanes can pose significant challenges to companies — disrupting suppliers, upending logistics, damaging infrastructure, and causing delays or even complete shutdowns.

Extreme weather has always incurred extreme costs. In 2022 alone, the U.S. sustained a staggering cost of $165 billion due to severe weather events, intensified by climate change. Among these events, Hurricane Ian struck South Florida, resulting in over 150 fatalities and a massive economic loss of $112.9 billion — making it the most expensive climate-related disaster in the nation last year, according to NOAA.

Companies can take action to safeguard their operations by proactively preparing hurricane strategies. With the advent of artificial intelligence (AI), companies now have powerful tools at their disposal to not only de-risk their supply chains but also uncover new opportunities amid these challenges for weather-dependent supply chains and logistics.

In ClimateAi’s recent webinar, “Going Beyond Reporting: Using AI to Derisk Supply Chains Ahead of Hurricane Season,” climate and supply chain experts discussed how AI can help companies navigate hurricane season and emerge stronger than ever.

Three Use Cases for AI to Solve Supply Chain Management Challenges during Hurricane Season

Supply chain managers must determine how to get the right products, in the right places, at the right times, and in the right quantities, to meet consumer needs. And they must make these inventory decisions in the most profit-maximizing (and cost-minimizing) ways.

During hurricane season, that’s an especially difficult task. Here’s how AI can help.

1. Demand Planning and Inventory Optimization

Hurricanes can cause dramatic spikes in demand for certain products at short notice, complicating even the best-laid (demand) plans.

As ClimateAi’s head of product innovation, Vikram Srinivasan, noted on the webinar, companies face one of two options in times like these: either having too little inventory, or having too much.

Too little, and companies risk an opportunity cost, lost sales, and lost market share.

But companies can also fall into the trap of holding too much inventory, as Srinivasan said: “Sometimes, inventory is the lever that folks use to buffer against these sorts of disruptions — by holding way too much inventory. It’s usually in the wrong products at the wrong time, at the wrong places.”

“There’s a lot of cash locked into the supply chain that can be very expensive, both from a financial and an operating cost perspective,”  he continued. “So how do you get a better sense to build the right inventory? By monitoring some of these signals ahead of time.”

Artificial intelligence-enhanced forecasts can help supply chain managers not only better understand when and where a hurricane is likely to hit, but also what its business-specific impact will be. For example, a company selling generators would care about which regions would be likely to experience power outages. A bottled water company would care about which areas are most likely to have their water supplies affected.

This way, AI unlocks the actionability of hurricane forecasting. By combining hurricane forecasting with industry data, companies can better understand the expected demand for specific goods and effectively optimize inventory.

For example: At the start of September 2022, ClimateAi issued a forecast for a large building materials company, assessing the impacts of the upcoming hurricane season on the demand for building materials to inform better supply planning. Fast forward a few weeks — and Hurricane Ian became active and quickly made landfall. With ClimateAi’s early forecast, the company was prepared to move the right amount and the right type of building materials (Florida building code-approved) into the affected regions.

By capitalizing on this increased demand, the company captured an additional $15 million in sales. You can read the case study here.

2. On-time Delivery

It’s difficult for companies to proactively plan and allocate resources, reroute shipments, and make informed decisions well in advance of a hurricane’s arrival.

“We’ve become a lot more consumer-centric, and ensuring that service is a key aspect of everything we do in a supply chain,” Srinivasan said. “That means having the right amount of [inventory] buffer, but also shrinking lead times …On-time delivery has been a major struggle. We’re hearing that companies, in terms of mitigation strategies, are often reactive.”

“They’re either looking at past historical data to plan for what might be the cases in the future — but with recent changes, it’s often not exactly gonna replicate that,” he added. “And so having that sense of what the delta is critical.”

AI-based forecasting can similarly inform better decision-making for logistics amid hurricanes, both in terms of your company delivering its goods on time to making sure that suppliers are delivering their goods to you on time. By analyzing historical data, supply chain network structures, and external factors, AI algorithms can identify vulnerabilities and weak points in supply chains.

For example, even if a company’s operations won’t be affected directly during a hurricane, will a key supplier or a key port that they rely upon?

“If you knew ahead of time how the next few weeks or months are gonna look, thinking about the right modes and alternatives can help you reroute or redesign your route so that you can consider these factors before you start the process,” Srinivasan said.

Companies can then take proactive measures to strengthen these areas, such as diversifying suppliers, creating backup facilities, or implementing contingency plans. In the case of the building materials company, ClimateAi’s forecast showing the increased likelihood of a strong hurricane hitting Florida in September far ahead of time. This enabled the company to move the inputs needed to manufacture its Florida-specific building materials to a nearby factory. As the likelihood of Hurricane Ian hitting Florida increased, the company began manufacturing these products, and when they were finished, moved them into the local market so homeowners could buy them to rebuild after the hurricane — enabling a quicker recovery for the community and increased market share for the company.

That’s a lesson for companies, Srinivasan said. “Contingency plans are super important and being deployed very actively from a perspective of mitigating risks. Sometimes it’s not possible to get ahead of the event, but with better monitoring, you can align your contingency plans, and streamline them better.”

3. Controlling Costs

“Given the interconnected nature of the supply chain and lead times associated with them, along with the variabilities, sometimes it’s hard to know where these disruptions are going to occur,” Srinivasan said. “Which sites or suppliers are the most exposed, and what are the downstream implications of not having a supply for your key ingredients or raw materials, for a certain amount of time? And what could that be to revenue at impact or lost service?”

“Controlling the costs, whether it’s for the company or passed onto the consumer, is a critical area that can impact a lot of things, whether it’s the purchasing power of the consumer or the associated cost and margin impacts for the company. And, while it’s going to go up during a disruption, can there be ways to reduce that impact and soften that impact if there’s better planning and contingency in place?” he continued.

AI-based impact forecasts can look at the percentage of disrupted throughput by month, but then utilize the company’s information to translate it into a financial measure. They take the information of “what it costs us when our whether it’s raw materials or finished goods get delayed by a day” or “property damage from catastrophic climate hazards such as wildfires or floods.”

They provide companies with tangible information like, “You have a risk of 10% damage and there’s a value associated with those assets.” Companies can then use this information to make more data-driven strategic and operational decisions.

Hurricane season presents significant challenges for companies, particularly in terms of supply chain disruptions. However, by leveraging AI technologies, businesses can not only de-risk their supply chains but also uncover new opportunities amidst the chaos.

Through predictive analytics, real-time monitoring, optimization, risk assessment, and opportunity identification, AI empowers companies to navigate hurricane season with greater resilience and agility.

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