The Min-Max Inventory analysis model developed for our client used a data-driven approach to determine optimal inventory levels. The main inputs into the model were the historical shipment data, the previous 13 weeks of fore- cast data, the expected demand for the next 13 weeks, the expected service level defined at 99%, and the inventory on hand at warehouses. By incorporating these parameters, the model calculates the minimum and maximum inventory thresholds for each SKU-Plant combination. This gave our client’s demand planners much-needed insight to maintain efficient stock levels, thereby reducing excess inventory carrying costs. The model is automated, facilitating real-time adjustments and enabling responsive inventory management to navi- gate demand fluctuations effectively. What we provided: A Finely Chopped Inventory Analysis Model
STRATEGY
AIM
RESULTS
Have a data-driven approach
To reduce inventory carrying costs
46% reduction in inventory levels
Solve demand variability management
To improve service level to 99%
Enhanced customer satisfaction
Real-time inventory control
To minimize stockouts or stock overflow To cater to different-sized retailers and distributors To lower operational inefficiency
Optimized inventory management
Higher percentage of satisfied customers
Scalable solution
Balancing costs effectively
Increased profit margins
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