Overview
A manufacturing company needed AI-powered inventory forecasting to reduce overstock and prevent stockouts across their supply chain.
The Challenge
Traditional forecasting methods were leading to 25% overstock and frequent stockouts, costing the company millions annually. They needed predictive analytics that account for seasonality, trends, and supply chain disruptions.
Our Solution
We developed a predictive analytics system using scikit-learn and time series analysis, integrated into a React dashboard. The system provides daily forecasts, automated reorder recommendations, and anomaly detection for supply chain disruptions.
Development Process
Historical data analysis and cleansing
Time series model development
Dashboard design and development
Integration with ERP system
Validation and deployment
Results
30% reduction in overstock
55% reduction in stockouts
Estimated annual savings of $2.1M
Daily automated forecasts for 5,000+ SKUs
Early warning system for supply chain disruptions
Technologies Used
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