Warehouse Inventory Management

Challenge

‍A wholesale distributor was experiencing 15% inventory discrepancies and significant fulfillment delays. Their manual inventory tracking processes were error-prone, stock levels were often inaccurate, and they lacked visibility into inventory movement patterns. This resulted in stockouts of fast-moving items while capital was tied up in slow-moving inventory.

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Solution

‍An AI inventory forecasting and management system using Obviously AI and n8n that:

• Analyzed historical sales data to predict future demand patterns
• Identified seasonal trends and product correlations
• Automatically optimized stock levels based on predicted demand
• Highlighted slow-moving inventory for potential promotions
• Generated optimized replenishment orders with supplier-specific parameters
• Provided early warnings for potential stockouts or overstocks

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Implementation

‍The system was built over 7 weeks:

1. ERP and warehouse management system integration
2. Historical inventory and sales data analysis
3. Demand forecasting model development for different product categories
4. Inventory optimization algorithm creation with business-specific constraints
5. Reporting dashboard and alert system implementation

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Results

• Inventory accuracy improved from 85% to 99.2%
• Order fulfillment time reduced by 42% through better stock availability
• 1.3 FTE saved in inventory management and purchasing activities
• Working capital reduced by €240,000 through more efficient inventory levels

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‍Supplier Integration

The system eventually expanded to include supplier collaboration features, enabling more efficient just-in-time inventory management with key partners.

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