Effect of Inventory Management Practices on the Operational Performance of Retail Pharmacies in Rwanda: A Case Study of Rite Pharmacy in Rwanda

Effect of Inventory Management Practices on the Operational Performance of Retail Pharmacies in Rwanda: A Case Study of Rite Pharmacy in Rwanda

Colombe Isingizwe and Nimpano Désiré
University of Kigali
Email: isicolombe@gmail.com

Abstract: This study examined the effect of Inventory Management Practices on the operational performance of RITE Pharmacy in Rwanda. Specifically, the study aimed at examining the effect of inventory planning and forecasting on operational performance of Rite Pharmacy in Rwanda. The study adopted a quantitative approach using explanatory and correlational research designs. The target population comprised 72 employees, and a census approach was used. Data were collected using structured questionnaires and analyzed using SPSS. Descriptive statistics, Pearson correlation, and simple linear regression were used for data analysis. The findings revealed that inventory planning and forecasting were positively associated with operational performance. Pearson correlation established a very strong positive and statistically significant relationship between inventory planning and forecasting and operational performance (r = 0.938, p = 0.000). Regression analysis showed that inventory planning and forecasting significantly predicted operational performance, explaining 88.0% of the variation inoperational performance (R² = 0.880, F = 461.915, p = 0.000). The regression coefficient further indicated a positive and significant effect of inventory planning and forecasting on operational performance (β = 0.938, p = 0.000). The study concluded that effective inventory planning and forecasting, including the use of historical sales information, demand forecasting, consideration of seasonal variations, and accurate prediction of future stock requirements, contribute to improved operational performance. The study recommends strengthening the use of historical sales data, regularly updating demand forecasts, and improving the accuracy of information used for inventory planning.

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