Abhi Ghadge, associate professor of supply chain management at Cranfield University in the UK, said climate resilience is already “a general negligence”, although that is beginning to change.
However, a detailed understanding of the supply chain can be very difficult, especially for smaller companies. Who provides suppliers? Which key raw materials are about to become a shortage? Beatriz Royo, associate professor at the Spanish MIT-Zaragoza program, said tracking such details requires long-term commitment and investment.
With that in mind, professional services company Marsh McLennan launched a system last year called Sentrisk, which claims to automatically analyze company shipping lists and customs clearance records to build pictures of its supply chain. Sentrisk relies on large language models to read potential billions of PDF documents, depending on the relevant customers and automatically tracks the source of individual materials and parts. “Of course, this could misunderstand something. It doesn’t have the chance to hallucinate the network of vendors that doesn’t exist.”
Sentrisk combines this supply chain analysis with data on climate risks in specific locations. “If you are investing in building a new manufacturing plant, maybe you can choose a location that is unlikely to be affected by a water shortage,” Davis said.
Dmitry Ivanov, professor of supply chain and operations management at the Berlin School of Economics and Law, said the digital twins need to be updated continuously. “It’s not like the house you build, which has been around for 100 years in this form,” he said. “The supply chain changes every day.”
While we have a pretty good idea of how climate change will affect the entire planet in the coming years, the exact location, timing and size of a particular disaster is tricky. This is a new tool for climate risk modeling and extreme weather forecasting. Semiconductor and AI giant NVIDIA has a platform called Earth-2 that hopes to address this challenge with the help of other organizations, including the National Oceanic and Atmospheric Management.
The idea is to use AI to provide early warnings about droughts or floods, or to more accurately predict how storms will develop. There are only relatively high information about current weather patterns in some parts of the world; Earth-2 uses the same type of AI that sharpens pictures in a smartphone camera application to simulate high-resolution data. “This is really useful, especially for small areas,” said Dion Harris, senior director of high-performance computing and AI factory solutions at NVIDIA.
Companies can feed their own data into Earth-2 to further improve forecasts. They may use the platform to model climate and weather effects in a specific geographical location, but the overall scope of the project is large. “We are building the basic elements to create the digital twins of the planet,” Harris said.
