Levi’s: AI Forecasting Improves Supply Chain Accuracy

By Elise Leise
Predictive analytics and digital twins offer methods to mitigate supply chain disruptions

Over the past quarter, supply chain disruptions have cost Levi’s in the range of US$7mn to US$8mn. This comes as no shock: global container shortages and port congestion have left few companies fully on their feet. What makes Levi’s different is how the company has responded. Faced with these issues, it negotiated limits to cost increases, opened a new Nevada distribution centre, and launched AI forecasting. 

‘Results from our first wave test showed that AI-driven demand forecasting improved accuracy’, said Levi’s CEO Chip Bergh. ‘So, scaling it should enable more precise inventory investment, lead to fewer markdowns and clearance, prevent waste, and enhance sustainability’. 

How Can AI Help? 

By collecting and analysing more data than a single human sorts alone, AI and ML can catch patterns, risks, and opportunities. If a certain port is at risk of becoming a choke point, for example, predictive analytics can act as a heads-up. What’s more, your team can track and manage your inventory stocks, anticipate delays, and handle customer complaints before situations spiral out of control. 

According to Nishith Rastogi, the CEO of Locus, AI applications such as digital twins can also improve your supply chain. Digital twins are essentially computerised versions of physical objects. For a simple visualisation, picture a pair of Levi’s jeans. With the technology we now have, you could create a digital copy, right down to the tan stitches, and receive real-time information about how the jeans react to stress, tear, and wear. 

Now make that image more complicated. You could technically use a digital twin to monitor entire segments of your on-ground supply chain, make better strategic decisions, and track choke points and bottlenecks. ‘This will take supply chain visibility a step further’, Rastogi explained. ‘It’ll help brands make their supply chains proactive’. 

What Happened During the Pandemic? 

Determining how much inventory to stock became almost impossible. But Levi’s Strategy and AI team rebuilt their predictive models almost overnight, focusing on e-commerce and disaster forecasting. With epidemiological modelling, they predicted infection rates, which helped the company determine when and where to re-open its outlet stores. Overall, these tactics helped Levi’s survive 2021—saving our best source of American denim. 

But that’s not all. Recently, Levi’s launched a machine learning and coding bootcamp to accelerate employee tech knowledge—hinting at more supply-chain-focused analytics in the future. ‘We’re so proud of the collaboration and selflessness of the team’, said Louis DiCesari, Levi’s Global Commercial Head of Data, Analytics, and AI. ‘Rarely have I seen people come together like this during such a difficult time’. 

By the end of this year, Levi’s will have trained more than 100 of its employees in this pilot programme. Excellent! According to McKinsey’s, developing this internal expertise is one of the hallmarks of AI high-performing companies. If Levi’s can continue to pivot and pay attention to the latest AI applications, therefore, it looks set to make great jeans and great business decisions.


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