Digitalización y automatización del proceso de gestión de inventario en la sucursal Quito de importadora Aguilar Ocho

Abstract

This degree project addresses the problem of inefficient inventory management at the Quito branch of Importadora Aguilar Ochoa, characterized by reliance on manual processes and an information latency of up to 72 hours. The main objective was to optimize operational management through the implementation of a lightweight digital system specifically designed for the branch's needs. The methodology employed was based on the Scrum agile framework, structured in four Sprints that integrated diagnosis, architectural design, and Artificial Intelligence-assisted development. The technological solution was built using the Flask microframework, the Python programming language, and the SQLite relational database engine, ensuring the data integrity of MIKEN brand machinery and spare parts. The results obtained after the implementation of the Minimum Viable Product (MVP) demonstrate a 70% reduction in transaction recording times, decreasing from an average of five minutes to ninety seconds. Additionally, the error margin in inventory consistency was reduced from 15% to 2%, eliminating information latency and providing the company with a strategic tool for real-time decision-making.