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Improving Efficiency and Effectiveness of Robotic Process Automation in Human Resource Management

Author

Listed:
  • Syaiful Anwar Mohamed

    (College of Graduate Studies, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Moamin A. Mahmoud

    (Institute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Mohammed Najah Mahdi

    (Institute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Salama A. Mostafa

    (Faculty of Computer Science and Information Technology, Universiti Tun Hussin Onn, Batu Pahat 86400, Johor, Malaysia)

Abstract

Automation technology is changing and transforming innovation into the industrial landscape and Human Resources (HR) should ensure to adapt and practice its deployment to realise its benefits in time and for cost savings. The implementation of Robotic Process Automation (RPA) in HR can help to offer better service to ensure compliance of the processes with standards and regulations. RPA is a software technology that manages software robots to emulate human actions when interacting with digital platforms. RPA is a solution that could perform repetitions to take over activities carried out by humans. However, a robot is not thought to be able to replace the HR but is, instead, useful to support driven processes. The purpose of the study is to prove the efficiency and effectiveness of RPA in the Human Resource Management System (HRMS) compared to the manual process performed by a human. Different types of components and characteristics were identified to adopt RPA in HRMS based on the data measurement in the implementation process. This study designs and develops an HRMS model using RPA tools to achieve the target process. The model was developed based on a case study of an existing model of RPA in HRMS from an IT consultancy industry. In the HR process, the project uses an application focusing on the parameters of gathering, storing and accessing employees’ information from other modules. Lastly, the gaps in the HRMS to improve productivity are evaluated and explained.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:3920-:d:780109
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    References listed on IDEAS

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    1. Huang, Feiqi & Vasarhelyi, Miklos A., 2019. "Applying robotic process automation (RPA) in auditing: A framework," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
    2. Lacity, Mary C. & Willcocks, Leslie P., 2016. "A new approach to automating services," LSE Research Online Documents on Economics 68135, London School of Economics and Political Science, LSE Library.
    3. Kokina, Julia & Blanchette, Shay, 2019. "Early evidence of digital labor in accounting: Innovation with Robotic Process Automation," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
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    Cited by:

    1. Xiaowei Yang & Shumin Yan & Jiang He & Junjie Dong, 2022. "Review and Prospects of Enterprise Human Resource Management Effectiveness: Bibliometric Analysis Based on Chinese-Language and English-Language Journals," Sustainability, MDPI, vol. 14(23), pages 1-16, December.
    2. Abdul Wali & Saipunidzam Mahamad & Suziah Sulaiman, 2023. "Task Automation Intelligent Agents: A Review," Future Internet, MDPI, vol. 15(6), pages 1-20, May.
    3. 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.
    4. Hui Zhang, 2023. "Fuzzy comprehensive evaluation and quantitative weight analysis in structure management of human resources," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-18, July.
    5. Mahmoud Abdulhadi Alabdali & Sami A. Khan & Muhammad Zafar Yaqub & Mohammed Awad Alshahrani, 2024. "Harnessing the Power of Algorithmic Human Resource Management and Human Resource Strategic Decision-Making for Achieving Organizational Success: An Empirical Analysis," Sustainability, MDPI, vol. 16(11), pages 1-30, June.
    6. Yue Chen & Yisong Li, 2024. "Storage Location Assignment for Improving Human–Robot Collaborative Order-Picking Efficiency in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 16(5), pages 1-25, February.
    7. Roslyn Cameron & Heinz Herrmann & Alan Nankervis, 2024. "Mapping the evolution of algorithmic HRM (AHRM): a multidisciplinary synthesis," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
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