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Performance Analysis Method for Robotic Process Automation

Author

Listed:
  • Rosa Virginia Encinas Quille

    (School of Arts, Sciences and Humanities, University of São Paulo, Rua Arlindo Béttio, 1000-Ermelino Matarazzo, São Paulo 03828-000, Brazil)

  • Felipe Valencia de Almeida

    (Polytechnic School, University of São Paulo, Av. Prof. Luciano Gualberto, 380-Butantã, São Paulo 05508-010, Brazil)

  • Joshua Borycz

    (Sarah Shannon Stevenson Science and Engineering Library, College of Arts and Sciences, Vanderbilt University, Nashville, TN 37212, USA)

  • Pedro Luiz Pizzigatti Corrêa

    (School of Arts, Sciences and Humanities, University of São Paulo, Rua Arlindo Béttio, 1000-Ermelino Matarazzo, São Paulo 03828-000, Brazil
    Polytechnic School, University of São Paulo, Av. Prof. Luciano Gualberto, 380-Butantã, São Paulo 05508-010, Brazil)

  • Lucia Vilela Leite Filgueiras

    (Polytechnic School, University of São Paulo, Av. Prof. Luciano Gualberto, 380-Butantã, São Paulo 05508-010, Brazil)

  • Jeaneth Machicao

    (Polytechnic School, University of São Paulo, Av. Prof. Luciano Gualberto, 380-Butantã, São Paulo 05508-010, Brazil)

  • Gustavo Matheus de Almeida

    (Department of Chemical Engineering, Federal University of Minas Gerais, Pampulha, Belo Horizonte 31270-901, Brazil)

  • Edson Toshimi Midorikawa

    (Polytechnic School, University of São Paulo, Av. Prof. Luciano Gualberto, 380-Butantã, São Paulo 05508-010, Brazil)

  • Vanessa Rafaela de Souza Demuner

    (EdP Brazil, Avenida Presidente Juscelino Kubitschek, São Paulo 04543-011, Brazil)

  • John Alexander Ramirez Bedoya

    (EdP Brazil, Avenida Presidente Juscelino Kubitschek, São Paulo 04543-011, Brazil)

  • Bruna Vajgel

    (Ernst & Young, Praia de Botafogo 370, 6 Andar, Botafogo, Rio de Janeiro 22250-040, Brazil)

Abstract

Recent studies show that decision making in Business Process Management (BPM) and incorporating sustainability in business is vital for service innovation within a company. Likewise, it is also possible to save time and money in an automated, intelligent and sustainable way. Robotic Process Automation (RPA) is one solution that can help businesses improve their BPM and sustainability practices through digital transformation. However, deciding which processes to automate with RPA technology can be complex. Consequently, this paper presents a model for selecting indicators to determine the profitability of shifting to RPA in selected business processes. The method used in this work is the Performance Analysis Method, which allows for predicting which processes could be replaced by RPA to save time and money in a service workflow. The Performance Analysis Method consists of collecting data on the speed and efficiency of a business process and then using that data to develop discrete event simulations to estimate the cost of automating parts of that process. A case study using this model is presented, using business process data from an international utility company as input to the discrete event simulation. The model used in this study predicts that this Electric Utility Company (EUC) will save a substantial amount of money if it implements RPA in its call center.

Suggested Citation

  • Rosa Virginia Encinas Quille & Felipe Valencia de Almeida & Joshua Borycz & Pedro Luiz Pizzigatti Corrêa & Lucia Vilela Leite Filgueiras & Jeaneth Machicao & Gustavo Matheus de Almeida & Edson Toshimi, 2023. "Performance Analysis Method for Robotic Process Automation," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3702-:d:1071541
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    References listed on IDEAS

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    1. Umair Akram & Melinda Timea Fülöp & Adriana Tiron-Tudor & Dan Ioan Topor & Sorinel Căpușneanu, 2021. "Impact of Digitalization on Customers’ Well-Being in the Pandemic Period: Challenges and Opportunities for the Retail Industry," IJERPH, MDPI, vol. 18(14), pages 1-21, July.
    2. Asatiani, Aleksandre & Copeland, Olli & Penttinen, Esko, 2023. "Deciding on the robotic process automation operating model: A checklist for RPA managers," Business Horizons, Elsevier, vol. 66(1), pages 109-121.
    3. Lawrence Brown & Noah Gans & Avishai Mandelbaum & Anat Sakov & Haipeng Shen & Sergey Zeltyn & Linda Zhao, 2005. "Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 36-50, March.
    4. Syaiful Anwar Mohamed & Moamin A. Mahmoud & Mohammed Najah Mahdi & Salama A. Mostafa, 2022. "Improving Efficiency and Effectiveness of Robotic Process Automation in Human Resource Management," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
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    Cited by:

    1. Marcello Cosa & Riccardo Torelli, 2024. "Digital Transformation and Flexible Performance Management: A Systematic Literature Review of the Evolution of Performance Measurement Systems," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(3), pages 445-466, September.
    2. Hari Lal Bhaskar & Mohammad Osama & Reeta, 2025. "Maximizing Business Process Efficiency in Industry 4.0: A Techno-Functional Exploration of Process Mining Tools," SN Operations Research Forum, Springer, vol. 6(1), pages 1-34, March.

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