Applying advanced analytics to improve a complex inventory management system

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A Fortune 100 retailer applied advanced analytics modeling techniques to streamline its inventory management system and achieve impressive results.

Client’s Challenge

To improve sales and cut costs by:

  • Using data science to refine appropriate inventory replenishment models
  • Addressing the issues that were leading to stock outs and overstock problems
  • Creating a better in-stock customer experience

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PwC’s Solution

Improve inventory management system by:

  • Analyzing historical and current data in search of a new data-driven approach
  • Creating a new strategy and algorithms based on historical demand patterns and science that can be used within the current technology

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Impact on client's business

  • The company is on track to increase sales by ten percent.
  • At the same time, it can reduce inventory by ten percent, enjoying significant cost savings.
  • The company is able to apply advanced analytics techniques without needing to purchase new hardware or software

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"Getting inventory right by tapping into sophisticated analytics techniques— and making the necessary replenishment decisions – was challenging."

Contact us

Dan  DiFilippo

Dan DiFilippo

Global and US Data and Analytics Leader, PwC US