“How AI digital twins help weather the world’s supply chain nightmare”
MIT Technology Review, February 21, 2019
by Sean Dorrance Kelly
“Just-in-time shipping is dead. Long live supply chains stress-tested with AI digital twins.”
With the supply-chain disruptions of the past two years showing no signs of easing anytime soon, businesses are turning to a new generation of AI-powered simulations called digital twins to help them get goods and services to customers on time. These tools not only predict disruptions down the line, but suggest what to do about it. Desperate companies struggling with the collapse of just-in-time shipping are using them to find a crucial balance between efficiency and resilience.
The list of things that have been hard to get hold of at one time or another in the last few months is as varied as it is long: new cars, new phones, contact lenses, cleaning products, fresh produce, garden furniture, books, the color blue. “It’s not like when everyone ran out of toilet paper in March 2020,” says Chris Nicholson, founder of Pathmind, a company that applies AI to logistics problems. “This time the missing items feel personalized.”
Covid-19 has shined a spotlight on many of the world’s networks, from the internet to international air travel. But the supply chains that crisscross the world—the ships and trucks and trains that link factories to ports and warehouses, bringing almost everything we buy many thousands of miles from where it’s produced to where it’s consumed—are facing more scrutiny than they ever have.
“It’s fair to say that whatever you’re selling, you’ve got a problem right now,” says Jason Boyce, founder and CEO of Avenue7Media, a consulting firm that advises top Amazon sellers. Boyce says he has clients who would be turning over tens of millions of dollars a year if they could stay in stock. “We’re having talks with clients every day where they’re just crying,” he says. “For months, they haven’t been fully in stock for one 30-day period in a row.”
Digital twins seek to solve breakages in the supply chain by anticipating them before they happen and then using AI to figure out a workaround. The name captures the key idea of simulating a complex system in a computer, creating a kind of twin that mirrors real-world objects—from ports to products—and the processes they are a part of. Simulations have been a part of decision-making in industry for some years, helping people explore different product designs or streamline the layout of a warehouse. But the availability of large amounts of real-time data and computing power means that more complex processes can be simulated for the first time, including the chaos of global supply chains that often rely on numerous vendors and transportation networks.
This kind of technology has given Amazon, which already has the advantage of controlling its own trucks and warehouses, an extra edge for years. Now others are embracing it as well. Google is developing supply-chain digital twins that the car maker Renault announced it had started using in September. International shipping giants like FedEx and DHL are building their own simulation software. And AI firms like Pathmind are creating bespoke tools for anyone who can pay for them. Yet not everyone will benefit. In fact, the powerful new technology could widen a growing digital divide in the global economy.
About the Author:
Will Douglas Heaven: I am the senior editor for AI at MIT Technology Review, where I cover new research, emerging trends and the people behind them. Previously, I was founding editor at the BBC tech-meets-geopolitics website Future Now and chief technology editor at New Scientist magazine. I have a PhD in computer science from Imperial College London and know what it’s like to work with robots.