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From Source to Shelf, a Round Up of Retail AI Innovation

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Natsu Optimizes Its Sales Planning and Reduces Leftover Stock by 20%

“Blue Yonder gives us accurate demand forecasts so that we can minimize our leftover stock.”

Jan Meier, CIO,
Natsu

Replenishment Optimization

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The Challenge

Natsu Foods delivers premium fresh foods to more than 2,500 supermarkets on a daily basis. The maker of sushi, wraps, and salads wanted more accurate demand planning to reduce its leftover stocks by as much as 20%.

The Solution

In order to avoid costly under- and overstocks, Natsu is using Blue Yonder Replenishment Optimization. To get more accurate demand forecasts, the machine learning algorithm includes external factors, such as holidays and weather forecasts, into its considerations.

The Results
  • Considerably more efficient replenishment
  • Leftover stock reduced by 20%
  • Better calculation of raw materials purchases
  • Optimized logistics processes
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Replenishment Optimization at Natsu

Natsu is one of the market-leading fresh food retailers in Germany. Its products are delivered to thousands of supermarkets on a daily basis. Accurate forecasts are essential to overcome such a logistical challenge. Jan Meier, IT Director at Natsu, explains how the company is taking on this challenge.

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Replenishment Optimization

Reduce out-of-stock rates by up to 80% without increasing waste or inventory

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  • 10x

    increased product availability

  • 80%

    out-of-stock rate reductions

  • 50x

    fewer manual interventions

Businesses Using Replenishment Optimization

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Kaiser’s Tengelmann Automates Replenishment

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Kaufland Optimizes Its Replenishment Process

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OTTO Uses Replenishment Optimization to Impress Its Customers and Increase Profits

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Successful Demand Forecasting at dm

Read the success story