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AI Flexes To Manage Supply Chain Volatility

AI Flexes To Manage Supply Chain Volatility

The emergence of automated technologies in the supply chain has introduced a host of unique and unfamiliar challenges to the supply chain management space. Much of the technology that aims to mitigate risk can add to the workload of supply chain professionals and limit their visibility into what’s happening down an organization’s supply chain, says Gaurav Palta, vice president of enterprise services at Noodle.ai.

Indeed, he told PYMNTS in a recent interview, the supply chain technology space has become “overpopulated” with solutions that can overwhelm supply chain officials – including planners and risk specialists – with alerts and data, ultimately backfiring and limiting these professionals’ ability to act on that information.

Noodle.ai is in an interesting position in the supply chain technology space. With its VP admitting to technology overload in the sector, and acknowledging an overabundance of artificial intelligence-powered solutions that may be running off the hype of AI instead of its actual capabilities, the company aims to address these pain points with an AI-powered tool recently launched in partnership with Dell. The trick, Palta explained, is to deploy a solution that can adapt to the near-constant changes of a supply chain.

“Everyone is talking about the fundamental problem [in supply chains], and that’s high volatility,” he said. “Especially if you look at the consumer goods space, there is a tremendously high volume of volatility both on the supply and the demand side.”

Software that deploys a rules-based algorithm to address this supply chain volatility can be too rigid to help supply chain professionals, said Palta. Technologies that provide alerts to team members can overwhelm in terms of volume, because as supply chains remain in constant flux, the particular scenarios that may set off an alert will almost inevitably change from moment to moment.

Palta described this as “noise,” adding that it can be an inaccurate way to react to changes in supply chains, forcing the end users of these tools – inventory planners, demand planners, production teams and beyond – to “figure out what’s real, and what’s not.”

Artificial intelligence is a malleable technology, and its ability to learn over time enables it to add greater value and accuracy to actionable insights.

But that’s not enough for an AI solution to have a positive impact on this space, Palta warned. Professionals don’t only need an “alert” telling them what they should do; rather, they need to know why a solution made that recommendation. He described this as turning the “black box” into a “glass box,” providing visibility into the factors that led a machine to make its decision and recommendation.

This is instrumental in promoting adoption of artificial intelligence in the supply chain, particularly as professionals get comfortable with the idea that an AI solution will not replace their jobs.

“It is about augmentation. It is not about elimination,” Palta said, noting that any solution used by this industry must show tangible benefits by reducing the amount of working capital tied up in inventory, reducing lost sales and lowering the amount of money companies spend on expedited shipping only to have products sit idle on the shelves.

But the biggest opportunity for AI to tackle what Noodle.ai describes as “monetary waste” in supply chain management is in the area of human capital. These technologies must be able to augment a professional’s ability to do his or her job with efficiency, he said. So while an AI-powered supply chain management solution may be accurate in its predictions and recommendations, if it doesn’t support the human end user, adoption will be limited.

“With an AI technology, the first thing you have to deal with is trust,” said Palta. “Is this going to take my job? There must be an emphasis on user-centricity.”

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