Economic order quantity approach to optimizing inventory management: evidence from a Nigerian fertilizer company

Abstract

Inventory inefficiencies remain a major challenge for manufacturing firms in developing economies, often resulting in excessive holding costs, shortages, and production delays. This study applies the Economic Order Quantity (EOQ) and Reorder Point (ROP) models to optimize inventory management at Hamdala Fertilizer and Chemical Company Limited, Nigeria. The company currently employs a fixed-ordering schedule of 12 purchases annually, without adjustments for demand fluctuations, leading to stock imbalances and unnecessary costs. Using company data and EOQ analysis, optimal order quantities and safety stock levels were computed for nitrogen, phosphorus, and potassium, the main raw materials for fertilizer production. A comparative analysis between the existing system and EOQ-based inventory management shows significant potential cost reductions and efficiency improvements. Sensitivity analysis further demonstrates the robustness of EOQ under fluctuating demand and holding costs. The findings confirm that structured, data-driven inventory models can provide reliable, scalable, and cost saving solutions for resource-intensive industries in developing economies.