In recent history, the fragility of the global supply chain has perhaps never been more apparent. COVID-19, the grounding of the Ever Given in the Suez Canal, widespread global port congestion, the ongoing shipping container shortage, and increasingly disruptive climate events have demonstrated that the thread by which global trade is connected seems increasingly thin.
Yes, it’s been a big year for black swans: not the avian variety, but rather those consequential events which are both impossible to predict and play outsized roles in history compared to regular occurrences.
The very nature of black swan events means logistics professionals and manufacturers cannot prepare for them. So how can the supply chain be fortified to create greater stability when the next event lands?
AI and Black Swan Events
“Black swan theory” was developed in theorist Nassim Nicholas Taleb’s work “The Black Swan: The Impact of the Highly Improbable”. Taleb classifies black swan events as completely unpredictable points of societal or technological inflection with untold, intractable consequences.1
Hindsight, they say, is 20/20. We tend to use that clear backward vision to rationalize black swan events away. In logistics, for example, perhaps the recent closure of CN Rail tracks due to North America’s debilitating heat wave could have been foreseen by available data.2 With black swans, we look back and say “I should have seen that coming.”
Rationalizing these events away gives the false impression that they can ultimately be predicted and managed—if only we recognize the signs and act before it’s too late. But after millennia of events we’d now classify as “black swans”, it’s clear that humans don’t have the ability to consistently assess the risk of a black swan before it happens.
Artificial intelligence, however, may be able to predict and help humans respond to black swan events and logistics professionals and supply chain managers are increasingly embracing such a possibility.
Expecting The Unexpected
Technically speaking, COVID-19 isn’t a black swan event because scientists have long predicted a global pandemic would occur eventually. But for the logistics industry, the pandemic landed like a grenade. While some supply chains bounced back with remarkable resilience, others continue to suffer today.
In a 2020 report, McKinsey & Co reported that “averaging across industries, companies can now expect supply chain disruptions lasting a month or longer to occur every 3.7 years, and the most severe events take a major financial toll.”3
This trend appears to be accelerating.
“Changes in the environment and in the global economy are increasing the frequency and magnitude of shocks,” reports McKinsey. “Forty weather disasters in 2019 caused damages exceeding $1 billion each—and in recent years, the economic toll caused by the most extreme events has been escalating.”3
In order to predict, react to, and mitigate the effects of these events, logistics stakeholders must be aware of their unique “exposure, vulnerabilities, and potential losses” in a multitude of scenarios.3 Luckily, as artificial intelligence sees wider uptake across various levels of the supply chain, this blue sky dream is becoming more attainable.
Digital Twin Technology
Artificial intelligence can help logistics companies fortify their segments of the supply chain by using available data to create simulations that model specific events and outcomes. This strategy typically involves “digital twin” technology, which is a virtual simulation of a real life supply chain. Accounting for everything from inventory levels to shipping routes and weather patterns, this type of AI can run thousands of scenarios to help decision makers plan for the next black swan event.
That’s the good news. Realistically speaking, the technology we need to react to and mitigate the effects of black swan events already exists.
The bad news? Many supply chain stakeholders aren’t poised to make use of it yet.
According to Nishith Rastogi, CEO at Locus Robotics, shippers and cargo owners currently only have vehicle- or ship-level visibility and AI simulations are only as precise as the data you provide. To make the most of digital twin tech, stakeholders need package-level visibility. To properly model the plausible outcomes of a black swan event, entire inventories must be accounted for.4
What’s more: this technology is strongest when it is widely used across industries and stakeholders as more data points create a richer and potentially more accurate simulation. Dan Gamota at Forbes calls this the “connective tissue,” and “the ability to put together the connective tissue is what continues to drive innovation and advancement across the [manufacturing and supply chain] sector.”5
Black swan events are, by nature, unpredictable and therefore unavoidable. Using the right technology, this could change if simulations begin to predict otherwise unforeseeable events. It’s more likely, though, that the use of AI digital twin simulations will, instead, inform decision makers how best to react to black swan events, helping keep the supply chain intact. As nations become more dependent on the global movement of goods, this technology could be critical to keeping shelves stocked, cars running, and medical goods available when the next black swan makes its appearance.
“When intelligence, speed, data and technology all come together, typically anchored by sophisticated data analytics, the result provides end-to-end visibility across global supply chains,” wrote Gamota. “As digital supply chains continue to evolve, we will get smarter, faster and more flexible in response to chaotic events. We have the mindset and the methodologies — and because of the pandemic, we now have valuable lessons to inform future decisions.”5