Overview

Developed a comprehensive supply chain analytics platform that provides real-time visibility into inventory levels, supplier performance, and logistics operations across 200+ warehouses globally.

Key Achievements

• Cost Reduction: 30% decrease in inventory holding costs
• Efficiency: 40% improvement in order fulfillment time
• Accuracy: 99.5% inventory accuracy through real-time tracking
• Optimization: AI-driven demand forecasting with 85% accuracy

Technical Architecture

Data Pipeline

• Real-time data ingestion from SAP, WMS, and IoT sensors
• Apache Spark for large-scale data processing
• Azure Data Lake for centralized storage
• Tableau for interactive visualizations

Optimization Engine

def optimize_inventory_levels():
    # Demand forecasting
    forecast = prophet_model.predict(historical_data)
    
    # Safety stock calculation
    safety_stock = calculate_safety_stock(
        demand_variability,
        lead_time_variability,
        service_level
    )
    
    # Reorder point optimization
    reorder_point = forecast.mean() * lead_time + safety_stock
    
    return {
        'optimal_inventory': reorder_point,
        'order_quantity': economic_order_quantity,
        'reorder_schedule': generate_schedule()
    }

Business Value

The platform has transformed supply chain operations by providing actionable insights that drive strategic decisions. Key stakeholders now have real-time visibility into critical metrics, enabling proactive problem-solving and continuous optimization.