Optimization of Inventory Management: Development of a Predictive Software Based on Advanced Analytics

Abstract

Inefficient inventory management in a veterinary clinic in Guayaquil has led to issues such as stock mismanagement, excess unsold products, shortages of high-demand items, and human errors. This project aims to develop specialized software that optimizes inventory administration through predictive tools and advanced data analysis. The methodology included interviews with inventory managers, historical data analysis, and the application of tools such as the Ishikawa Diagram, Pareto Analysis, and the 5 Whys to identify the root causes of the problem. Solution alternatives were also evaluated using priority and impact-difficulty matrices, ultimately selecting the design of software incorporating EOQ and Silver-Meal models. The resulting software enables the calculation of optimal inventory quantities and reorder points, adapting to demand fluctuations. Additionally, it features a secure and accessible web interface to simplify usage. The results demonstrate a reduction in errors, excess, and inventory shortages, as well as an improvement in operational efficiency. The conclusions highlight the importance of identifying root causes and proposing comprehensive technological solutions to optimize processes and enhance organizational performance.