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Why Linking Data to Responsiveness is Key to Solving Inventory Woes

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Join Theory, Google, H&M, McKinsey, Foot Locker, Lafayette 148, LL Bean, the Retail Prophet and more at Sourcing Journal’s Virtual Sourcing Summit, R/Evolution: Overhauling Fashion’s Outmoded Supply Chain, Oct 14 & 15.

Here’s an easy gamble for you: What are the chances that asking any apparel retailers about their No. 1 pain point will result in “inventory management” as the response?

It’s an easy bet for good reason. Historically hinged upon changing fashion trends, the ability to accurately predict inventory needs has been upended by e-commerce and social media, which have simultaneously kicked consumer expectations into overdrive. Pinned to a supply chain that’s unable to keep up, many retailers are relegated to inventory alignment via legacy forecasting software that’s saddled with uncertainty.

Ahmed Zaidi, co-founder and CTO of tech consultancy firm Catalyst AI, said in Sourcing Journal’s CGS-sponsored “Omnichannel Overload” webinar that leveraging data to identify trends can help. For instance, retailers can use social channels like Pinterest or Instagram to identify the most common color palette of interest to a particular customer base, and then accordingly identify and stock more of those colors in their own assortments, he said.

The real challenge arises when brands want to use data to determine not what’s hot now, but what will resonate with shoppers a year out. “That’s a much more intractable problem, and your model uncertainty will shoot through the roof,” he said. “If you’re building a model and you’re trying to predict 40 weeks in advance, the likelihood is that your model is going to fail because a lot of things can change in those 40 weeks. The only way to really be able to react to those trends and order accordingly is to reduce the size of your shipment orders or the time that it takes to get those products to market.”

That’s where tying data to your supply chain comes in, but you have to have the responsiveness to react, according to John Thorbeck, chairman of Chainge Capital, a supplier of supply chain analytics.

“The application of data analytics can’t just simply be related to demand. You need speed and flexibility to respond to demand insights,” Thorbeck said. “Applying AI to responsiveness is still a significant opportunity.”

That speed and flexibility could reduce lead times by 90 percent, Thorbeck said, with consequent reductions in inventory and working capital.

Of course, the ability to achieve all of this will require significant change management—not just new technology.

Listen to the “Omnichannel Overload” webinar to learn about the cultural change that must occur first, and why digitizing your current operations without this step can lead you to simply digitizing your mistakes.

 

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