Sharper Supply Chains with Smart AI Modeling

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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