Supply Chain Automation

Overview

A mid-size retailer was managing inventory across 12 locations using spreadsheets and gut feel. Stockouts were frequent, overstock tied up capital, and the 3-person procurement team couldn't keep up with 2,000+ SKUs. We built an AI supply chain management system that forecasts demand, automates purchasing, and continuously optimizes inventory levels.

The Challenge

Demand patterns varied by location, season, promotions, and external factors. Supplier lead times were inconsistent. The system needed to account for minimum order quantities, volume discounts, shelf life, and storage constraints while maintaining target service levels.

Our Approach

We built a demand forecasting model using historical sales data, seasonality patterns, promotional calendars, and external signals (weather, local events). The optimization engine balances service level targets against carrying costs to determine optimal reorder points and quantities per SKU per location. Purchase orders are auto-generated and sent to suppliers with the procurement team only reviewing exceptions.

Key Features

• AI demand forecasting with external signal integration
• Dynamic reorder point calculation per SKU per location
• Automated purchase order generation
• Supplier performance scoring and alternative sourcing
• Stockout and overstock alerts
• Promotion impact prediction
• Inventory valuation and reporting

Results

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