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SUPPLY CHAIN ANALYTICS

Optimized inventory management to unlock working capital and maximize sales

Situation

  • Client: A U.S.-based retailer evaluating future supply chain requirements to adapt to evolving business demands

  • Need: Analyze inventory data from 50+ warehouses and 500+ SKUs to develop a streamlined approach for optimizing stock levels, improving inventory productivity, and reducing stockouts

Approach

  • Scope definition & data standardization:

  1. Designed a data request template to guide data cleaning and aggregation

  2. Processed and standardized inventory data using Alteryx and Python, filling missing values through collaboration with the client and vendors

  • Inventory metrics aggregation: Analyzed key inventory KPIs, including:

  1. Inventory turns at the sector/category level

  2. Distribution & warehousing costs to identify inefficiencies

  3. Stock availability (% of active articles) across warehouses vs. stores

  • Interactive Power BI dashboard: Developed a real-time Power BI dashboard to visualize inventory trends and enable dynamic decision-making

  • Strategic value-add: Delivered preliminary insights to the client, allowing for quick adjustments to inventory strategies and operational plans

Results & impact

  • Optimized inventory levels: Identified a 15% reduction potential in total inventory with no negative impact on sales

  • Increased cost efficiency: Achieved 6% cost savings through improved data handling and enhanced inventory planning

  • Improved stock availability: Reduced stock outs by 10%, leading to higher customer satisfaction

  • Lower logistics costs: Identified ~5% reduction in transportation costs, contributing to overall operational efficiency

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