Developed an automated store replenishment system for a leading CPG manufacturer


The client wanted a solution that could provide automated recommendations for store replenishment for their products in retail stores across the US. A major cost reduction in the supply chain was achievable by eliminating the role of sales representatives in manually placing replenishment orders for each store.


We addressed the client’s challenge through a four-step process –

  • Integration, cleansing and structuring of data streams around inflow and outflow of products from retail stores
  • Analysis of ground-level operations and procurement of operational insights to identify variables such as SKU velocity, overall store performance and typical invoice intervals, that could indicate levels of demand in each store at a given time
  • Development of a statistical algorithm to approximate real-time inventory positions for each SKU followed by placing appropriate replenishment orders for each store
  • Generation of a weekly priority list of stores to further optimize the distribution routing system

Key Benefits

  • Improvement in operational efficiency was accomplished by eliminating manual effort to place replenishment orders
  • The overall solution provided the client ground-level insights into operational performance by tracking metrics such as routing and planogram adherence
  • Valuable insights at a granular level allowed the client to precisely identify and troubleshoot specific pain points at the last leg of the supply chain


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The automated replenishment system accurately captured upwards of 20% greater opportunity as compared to the manual replenishment process

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Our solution enabled the client’s distributors to reduce cost of distribution by eliminating a significant portion of weekly man-hours while providing accurate truck-loading recommendations

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The client could improve on-shelf availability of products by systematically capturing a greater portion of the opportunity for replenishment. The improvements were nearly 8%

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