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Target leans on data science to solve ‘extremely large’ retail problems

December 18, 2019

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Winners in the retail market are putting data to work. In the case of a national chain the size of Target, that means keeping tabs on an inventory of around 1 million products, then using data to ensure their availability.

In 2017, Target began testing algorithms to increase fulfillment velocity in its supply chain. By the following year, it saw its out-of-stock levels decrease 40%.

In its approach to modernization, Target has learned to lean on the physicality of retail to achieve better results.

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