Robotic Process Automation in Latin American Organizations: Survey and Evaluation of the Current State of Technology Adoption
Resumo
Context: Business processes have long relied on two types of resources to perform work: humans and information systems (IS). Despite the high performance of IS, still, much of the repetitive work has been done by humans for reasons including implementation cost and technical debt, among others. Now, robots are joining offices as a possible third workforce. Robotic Process Automation (RPA) is already a reality in many organizations, performing much of the work previously dependent on manual labor. Problem: While RPA offers innovative ways to automate work, it is also limited in automating complex activities. To propose solutions, we must understand these limitations by evaluating how organizations are automating their processes with RPA and trying to overcome these problems. Solution: In this study, we seek answers about how organizations are dealing with the limitations of RPA and what technologies are being used to create smarter automation. IS Theory: Work systems theory. Method: Questionnaire survey with professionals regarding the application of RPA in their organizations and a descriptive evaluation of the current state of RPA adoption in the evaluated organizations in Latin America. Summary of Results: While some practitioners have not perceived limitations, others reported obstacles to process unstructured data and automate complex decisions, as well as preparing bots to learn and adapt. AI techniques and business automation technologies have been experimented with as ways to surpass some limitations. Contributions and Impact to IS: This paper provides an overview of the current state of RPA adoption in Latin American organizations and how it is evolving to create smarter, more sustainable automation.
Palavras-chave:
Robotic process automation, intelligent process automation, artificial intelligence, smart automation
Referências
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Mário Romao et al.2019. Robotic Process Automation: A Case Study in the Banking Industry. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). 1–6. https://doi.org/10.23919/CISTI.2019.8760733
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Nataliya Yatskiv et al.2020. Method of Robotic Process Automation in Software Testing Using Artificial Intelligence. In 2020 10th International Conference on Advanced Computer Information Technologies (ACIT). 501–504. https://doi.org/10.1109/ACIT49673.2020.9208806
Pedro Lohmann et al.2020. APRUMO (Agile Process Modeling) - A Method to Process Modeling Using Agile BPM. In Anais do XVI Simpósio Brasileiro de Sistemas de Informação (Evento Online). SBC, Porto Alegre, RS, Brasil. https://doi.org/10.5753/sbsi.2020.13766
Simone Agostinelli et al.2020. Towards Intelligent Robotic Process Automation for BPMers. arXiv:2001.00804 [cs] (2020). http://arxiv.org/abs/2001.00804
Sanket Parchande et al.2019. Contractual Employee Management System Using Machine Learning and Robotic Process Automation. In 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA). 1–5. https://doi.org/10.1109/ICCUBEA47591.2019.9128818
Stephanie Stoudt-Hansen et al.2019. Predicts 2020: RPA Renaissance Driven by Morphing Offerings and Zeal for Operation Excellence. https://www.gartner.com/en/documents/3976135
Ning Zhang and Bo Liu. 2018. The Key Factors Affecting RPA-Business Alignment. (2018). https://doi.org/10.1145/3265689.3265699
Abhishek Baidya. 2021. Document Analysis and Classification: A Robotic Process Automation (RPA) and Machine Learning Approach. In 2021 4th International Conference on Information and Computer Technologies (ICICT). https://doi.org/10.1109/ICICT52872.2021.00013
Ana Cláudia de Almeida Bordigon et al.2018. Processamento de Linguagem Natural na Identificação e Modelagem de Processos de Negócio: Uma Revisão Sistemática da Literatura. In Anais do XIV Simpósio Brasileiro de Sistemas de Informação (Caxias do Sul). SBC, Porto Alegre, RS, Brasil, 191–198. https://sol.sbc.org.br/index.php/sbsi/article/view/5087
Abdelkader Rhouati El Hassane Ettifouri, Walid Dahhane, and Georges Abou Haidar. 2021. Impact of robotic process automation in supply chain: A model for task selection. In RSAE 2021: 2021 the 3rd International Conference on Robotics Systems and Automation Engineering (RSAE). 17–20. https://doi.org/10.1145/3475851.3475865
Ruchi Issac, Riya Muni, and Kenali Desai. 2018. Delineated Analysis of Robotic Process Automation Tools. In 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC). 1–5. https://doi.org/10.1109/ICAECC.2018.8479511
Raquel Pillat, Renata Santos, and Toacy Oliveira. 2019. Revisão Sistemática da Literatura sobre Abordagens para Adaptação de Processos Baseadas em BPMN. In Anais do XV Simpósio Brasileiro de Sistemas de Informação (Aracajú). SBC, Porto Alegre, RS, Brasil. https://sol.sbc.org.br/index.php/sbsi/article/view/13914
Andres Jimenez-Ramirez et al.2019. A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle. In Advanced Information Systems Engineering, Paolo Giorgini and Barbara Weber (Eds.). 446–461. https://doi.org/10.1007/978-3-030-21290-2_28
André Pedretti et al.2021. Robotic Process Automation Extended with Artificial Intelligence Techniques in Power Distribution Utilities. In Brazilian Archives of Biology and Technology. https://doi.org/10.1590/1678-4324-75years-2021210217
Jean Carlo Hauck et al.2021. How has process assessment been automated by organizations? A systematic literature mapping. In Anais do XVII Simpósio Brasileiro de Sistemas de Informação (Uberlândia). SBC, Porto Alegre, RS, Brasil. https://sol.sbc.org.br/index.php/sbsi/article/view/17731
Mário Romao et al.2019. Robotic Process Automation: A Case Study in the Banking Industry. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). 1–6. https://doi.org/10.23919/CISTI.2019.8760733
Nirmala S. Patil et al.2021. Vehicle Insurance Fraud Detection System Using Robotic Process Automation and Machine Learning. In 2021 International Conference on Intelligent Technologies (CONIT). 1–5. https://doi.org/10.1109/CONIT51480.2021.9498507
Nataliya Yatskiv et al.2020. Method of Robotic Process Automation in Software Testing Using Artificial Intelligence. In 2020 10th International Conference on Advanced Computer Information Technologies (ACIT). 501–504. https://doi.org/10.1109/ACIT49673.2020.9208806
Pedro Lohmann et al.2020. APRUMO (Agile Process Modeling) - A Method to Process Modeling Using Agile BPM. In Anais do XVI Simpósio Brasileiro de Sistemas de Informação (Evento Online). SBC, Porto Alegre, RS, Brasil. https://doi.org/10.5753/sbsi.2020.13766
Simone Agostinelli et al.2020. Towards Intelligent Robotic Process Automation for BPMers. arXiv:2001.00804 [cs] (2020). http://arxiv.org/abs/2001.00804
Sanket Parchande et al.2019. Contractual Employee Management System Using Machine Learning and Robotic Process Automation. In 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA). 1–5. https://doi.org/10.1109/ICCUBEA47591.2019.9128818
Stephanie Stoudt-Hansen et al.2019. Predicts 2020: RPA Renaissance Driven by Morphing Offerings and Zeal for Operation Excellence. https://www.gartner.com/en/documents/3976135
Ning Zhang and Bo Liu. 2018. The Key Factors Affecting RPA-Business Alignment. (2018). https://doi.org/10.1145/3265689.3265699
Publicado
29/05/2023
Como Citar
SGANDERLA, Rachele Bianchi; FANTINATO, Marcelo; THOM, Lucineia Heloisa.
Robotic Process Automation in Latin American Organizations: Survey and Evaluation of the Current State of Technology Adoption. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 19. , 2023, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
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