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Inventory Optimization & Supply Chain Health
Dynamic reorder point modeling balancing stockout risk vs. carrying cost.
Optimized
Safety Stock Level
+22%
Turnover Rate
-35%
Stockouts
32 days
DIO (Days)
The Challenge
We're either overstocked or out of stock. What's the right balance between carrying costs and stockout risk? Manual reorder points left millions in excess inventory.
Technical & Strategic Approach
- Built demand forecasting model for each SKU incorporating seasonality and trends
- Developed dynamic safety stock calculation based on service level targets
- Created cost trade-off model balancing carrying costs vs. stockout penalties
- Implemented ABC analysis for differential inventory management by SKU value
- Built suggested reorder points dashboard showing forecast accuracy impact on safety stock
Results & Outcomes
18% reduction in total inventory value while improving fill rates. Stockouts decreased 35%. Freed $2.1M working capital. Carrying costs down $450K annually.
Tech Stack
Python
SQL
scikit-learn
Optuna
Tableau
Pandas
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