Document Process Automation in an International Logistics Company Using OCR, RPA, and Text Analytics

Authors

DOI:

https://doi.org/10.26439/ciii2025.8661

Keywords:

Data extraction, document processing, optical character recognition (OCR), robotic process automation (RPA), text analytics

Abstract

This study aims to optimize the document settlement process in a Peruvian foreign trade logistics company through the implementation of intelligent automation technologies, including robotic process automation (RPA), optical character recognition (OCR), and text analytics. This process, initially characterized by intensive manual tasks, typing errors, and excessive processing times, limited operational performance and generated bottlenecks in logistics operations. Among the main findings, a 49% reduction in average processing time for work orders was observed. During functional validation, the average number of work orders processed per shift was measured. An increase from 4.03 to 6.00 work orders per shift was reported, representing an improvement of 1.97 work orders per shift following the implementation of automation. It is concluded that document automation represents an effective and scalable strategy for improving logistics performance in document processing. As a future goal, automation is planned to be expanded to all administrative areas with repetitive and standardized operational processes.

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Author Biographies

  • Nayeli Marianela Soto Leiva, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Nayeli Marinale Soto Leiva holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima, Perú, and ranked in the top third of her class. Since 2022, she has created and managed her own business dedicated to event decoration, applying tools related to e-commerce, marketing, process improvement, customer-flow analysis, and input management, while integrating technical knowledge with a customer-experience approach. She currently works at Dirección Regional de Agricultura de Cajamarca, where she has performed duties in logistics and later in the administrative area of an investment project, while continuing to manage her business. She has been a member of the Innovation Circle at Universidad de Lima. Her main academic and professional areas of interest include process improvement, quality management, customer experience, service management, and logistics.

  • Yair Raul Cubas Pecho, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Yair Raul Cubas Pecho holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima. He currently works as a professional intern in Human Resources, where he participates in the digital transformation of administrative processes through the design and implementation of automation solutions for administrative control. He has developed internal web-based query systems that allow employees to access personalized employment information, contributing to operational efficiency and the modernization of talent management. His main areas of interest include finance, capital markets, process automation, and data analytics applied to business management.

  • José Antonio Taquía Gutiérrez, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    José Antonio Taquía Gutiérrez holds a PhD in Business Management from Universidad Nacional Mayor de San Marcos and a Master’s degree in Industrial Engineering from Universidad de Lima. In the private sector, he has participated in several technology project implementations applied to operations in supply chain processes and decision-support systems for leading retail companies. He has also developed projects for the Instituto de Investigación Científica of Universidad de Lima. His main research interests are process improvement, predictive analytics, and Industry 4.0.

  • Juan Carlos Quiroz Flores, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Juan Carlos Quiroz-Flores holds a PhD in Business Management from Universidad Nacional Mayor de San Marcos, a Master’s degree in Business Administration from ESAN Graduate School of Business, and a degree in Industrial Engineering from Universidad de Lima, with certifications in Lean Six Sigma and Lean Manufacturing. He is a Research Professor and Coordinator of Degrees and Diplomas at Universidad de Lima, with more than 140 articles indexed in Scopus and Web of Science. He is a full member of Sigma Xi, in recognition of his scientific output, and a member of Beta Gamma Sigma for academic excellence in his graduate studies. He specializes in lean supply chain, process improvement, and productivity, and has more than 20 years of experience in operations management in manufacturing, services, and retail companies.

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Published

2026-06-08

Issue

No. 004 (2025): IV Congreso Internacional de Ingeniería Industrial

Section

Ponencias

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