Our client, CSK Bio Pte Ltd, receives ad hoc and project-based stochastic demand for its wide range of metal products. They currently places product reorders based on the director’s intuition. This project aims to reduce managerial complexity and produce cost-savings through the implementation of an Order-Pooling heuristic that balances shipment cost savings, and on-hand inventory levels, while achieving a high fill rate for each product. We came up with 2 possible heuristic models using knowledge such as Base-Stock Model from MSO and tested the significance of their savings using knowledge such as singlse factor ANOVA and Bonferroni Method from Statistics. We then plotted a trade-off between improving shipping cost savings and increasing mean inventory levels and picked an optimal solution using the Utopia Point method. Our final model provides a saving of $0.38/kg of shipment with low on-hand inventory. Additionally, this model is scalable to meet our client’s business needs.