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          Smart Inventory Management

          Smart Inventory Management

          After six months of operation, the solution successfully reduced dead inventory by 67% and increased product availability to 96%, eliminating the reliance on outdated historical reports. Thanks to this total visibility, the company decreased lost sales due to stockouts by 41%, freeing up trapped capital and transforming its operational efficiency.

          Identified Problem

          A clothing retail chain with 45 branches nationwide faced one of the most costly problems in retail: inventory imbalance. While some stores accumulated unsold products, others lost sales due to a lack of stock. The purchasing team made decisions based on historical reports that arrived weeks late, and projection errors generated annual losses in discontinued merchandise.

          Solution

          An AI-powered inventory management system was implemented, capable of analyzing over 40 simultaneous variables in real-time. The system evaluates:

          • Sales history per SKU.
          • Search trends on social media.
          • Weather conditions by region.
          • Holidays and local events.
          • Competitor behavior.
          • Purchasing patterns by customer type.

          Based on this data, the system generates automatic replenishment orders, suggests inventory transfers between stores, and alerts the purchasing team whenever it detects anomalies in a product’s behavior.

          Results

          After six months of operation, the chain reduced its dead inventory by 67%, increased its in-store product availability rate to 96%, and freed up capital that was previously trapped in slow-moving merchandise. Lost sales due to stockouts dropped by 41%.

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          for Mexico and Latin America

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