Data-Driven inventory management and lean logistics integration: A case study in the Peruvian household cleaning products sector

This study focused on optimizing inventory management in a multinational household cleaning products company, particularly in its detergent line. The central issue was the high number of inventory days, which initially stood at 65 days, well above the optimal range of 20 to 30 days. The challenges included inefficient planning, outdated demand forecasting methods, and high storage costs, which urgently needed to be addressed to improve operational efficiency. The research proposed a solution by integrating Simple Exponential Smoothing and the Economic Order Quantity (EOQ) model with Lean logistics principles. These tools enabled a reduction in inventory days to 36, improved forecasting accuracy, and increased inventory turnover. Key results included a 27.99% reduction in annual storage costs. The impact of this research was significant, as it not only improved operational efficiency but also generated substantial financial savings for the company. The study offers a replicable framework for other industries and sectors. Future research should explore the application of these methodologies in different contexts to enhance competitiveness.