Inventory Management as a Tool for Effective Control in Listed Manufacturing Firms in Nigeria: a Case of Dangote Sugar Plc.

ABSTRACT

This study investigates the Inventory Management as a Tool for Effective Control in Listed Manufacturing Firms in Nigeria: A Case of Dangote Sugar Plc. The Dangote Sugar Refinery PLC was the studied population. The research employed an ex post facto research design to investigate the relationship between proxies for inventory management such as Inventory Turnover Ratio, Days Inventory Outstanding, and Inventory to Sales Ratio and the Cash Conversion Cycle, while firm size served as the control variable. secondary data was collected from Dangote Sugar Refinery Plc's annual reports from 2014-2023. Multiple regression and ANOVA was used to test for the significant and relationships amongst the variables. The research was motivated by the critical importance of efficient inventory management in manufacturing firms and its potential impact on organizational performance. The analysis revealed several significant findings regarding the relationship between inventory management metrics and working capital efficiency. The analysis revealed that Inventory Turnover Ratio had a negative but non-significant relationship with the Cash Conversion Cycle, suggesting that higher inventory turnover is associated with shorter cash conversion cycles. Days Inventory Outstanding showed a positive but non-significant relationship, indicating that longer inventory holding periods are associated with extended cash conversion cycles. The Inventory to Sales Ratio demonstrated a substantial negative but non-significant relationship with the Cash Conversion Cycle, suggesting a complex relationship between inventory levels and working capital efficiency. The control variable, Firm Size, emerged as the only statistically significant predictor, showing a negative relationship with the Cash Conversion Cycle. This finding suggests that larger firms tend to have more efficient working capital management. Investing in advanced forecasting technologies to better predict demand patterns and optimize production schedules, system should incorporate real-time tracking capabilities and automated reordering mechanisms, regular training programs were recommended.