Examining the Effects of Robotic Process Automation on Operational Efficiency and Business Process Optimization (Literature Study)

Authors

  • Legito Sekolah Tinggi Teknologi Sinar Husni Deliserdang

DOI:

https://doi.org/10.58812/wsis.v1i2.91

Keywords:

Robotic Process Automation, Operational Efficiency, Business Process Optimization, Literature Study, Systematic Review

Abstract

This research study investigates the influence of Robotic Process Automation (RPA) on operational efficiency and business process optimization. The study adopted a systematic literature review approach to collect and analyze relevant academic articles, industry reports, and conference proceedings. Findings reveal that RPA implementation significantly improves operational efficiency by automating repetitive and rule-based tasks. This automation reduces manual effort, minimizes errors, and speeds up process execution, leading to increased productivity, faster response times, and cost savings for organizations. RPA also contributes to business process optimization by streamlining workflows, eliminating bottlenecks, and standardizing processes. Standardized execution of tasks through RPA improves process efficiency, quality, and visibility, allowing organizations to make data-driven decisions and continuously optimize their operations. However, challenges such as process complexity, employee resistance to change, integration issues, and data security concerns need to be addressed for a successful RPA implementation. Organizations must develop a comprehensive implementation plan, establish a governance framework, and foster a culture of collaboration to overcome these challenges. The practical implications derived from this research offer guidance for organizations that are considering or implementing RPA solutions. Recommendations include conducting a thorough process analysis, developing a comprehensive implementation plan, establishing governance mechanisms, encouraging collaboration, and continuously optimizing processes. While this study provides valuable insights into the impact of RPA on operational efficiency and business process optimization, it acknowledges the limitations of the research, such as the reliance on literature up to September 2021 and the subjectivity of the data analysis.

References

F. Quoquab and J. Mohammad, “Environment Dominant Logic: Concerning for Achieving the Sustainability Marketing,” Procedia Econ. Financ., vol. 37, no. April, pp. 234–238, 2016, doi: 10.1016/s2212-5671(16)30119-8.

C. (Abigail) Zhang, H. Issa, A. Rozario, and J. S. Soegaard, “Robotic Process Automation (RPA) Implementation Case Studies in Accounting: A Beginning to End Perspective,” Account. Horizons, vol. 37, no. 1, pp. 193–217, Mar. 2023, doi: 10.2308/HORIZONS-2021-084.

R. Šperka and M. Halaška, The performance assessment framework (PPAFR) for RPA implementation in a loan application process using process mining, vol. 21, no. 2. Springer Berlin Heidelberg, 2022. doi: 10.1007/s10257-022-00602-2.

D. M. Martin and J. W. Schouten, “The answer is sustainable marketing, when the question is: What can we do?,” Rech. Appl. en Mark. (English Ed., vol. 29, no. 3, pp. 107–109, 2014, doi: 10.1177/2051570714540497.

A. Inglis, “Assessing the need for a quality framework designed specifically for managing the provision of online distance education in developing countries,” 2010, [Online]. Available: https://www.semanticscholar.org/paper/5b4c963ee8c997d2a41f0329bb0aeff621950184

A. Susilo, H. Prabowo, W. Kosasih, R. Kartono, and V. Utami Tjhin, “The Implementation of Robotic Process Automation for Banking Sector Case Study of A Private Bank in Indonesia,” in Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City, in ICIT ’21. New York, NY, USA: Association for Computing Machinery, 2022, pp. 365–371. doi: 10.1145/3512576.3512641.

N. M. El-Gharib, “A Framework for Implementing Process Mining and Robotic Process Automation in Organizations (Extended Abstract),” CEUR Workshop Proc., vol. 3299, pp. 51–55, 2022.

Y. Qiu and G. Xiao, “Research on Cost Management Optimization of Financial Sharing Center Based on RPA,” Procedia Comput. Sci., vol. 166, pp. 115–119, Jan. 2020, doi: 10.1016/j.procs.2020.02.031.

N. Sumathi and A. Jeyalakshmi, “Implementing robotic process automation to improve operational efficiency in the health-care sector,” Int. J. Health Sci. (Qassim)., vol. 6, no. May, pp. 9666–9672, 2022, doi: 10.53730/ijhs.v6ns1.7256.

M. Thekkethil, V. Shukla, F. Beena, and D. A. Chopra, Robotic Process Automation in Banking and Finance Sector for Loan Processing and Fraud Detection. 2021. doi: 10.1109/ICRITO51393.2021.9596076.

D. Toman, “AIS Electronic Library ( AISeL ) AN EMPIRICALLY SUPPORTED CONCEPTUALISATION OF ROBOTIC PROCESS AUTOMATION ( RPA ) BENEFITS,” 2020.

A. Piyatilake, I. D. Vitharanage, M. M. De Silva, and A. Thibbotuwawa, “Benefits Realization of Robotic Process Automation (RPA) Initiatives in Supply Chains,” Res. Transp. Logist. Ind. Proc. 7th Int. Conf., vol. 11, no. March, pp. 57–59, 2022, doi: 10.1109/ACCESS.2023.3266293.

J. G. CALVA CARHUAMACA and E. A. ALFARO PAREDES, “About the Benefits of the Rpa System in Electronic Invoicing,” Dyna, vol. 94, no. 1, pp. 244–244, 2019, doi: 10.6036/9091.

M. N. Khan et al., “Faster and Profitable Production Optimization Decisions through Workflow Automation and Business Process Management - A Unique Concept,” Abu Dhabi International Petroleum Exhibition & Conference. p. D041S108R002, Nov. 12, 2018. doi: 10.2118/193343-MS.

G. Tsakalidis and K. Vergidis, “Towards a comprehensive business process optimization framework,” Proc. - 2017 IEEE 19th Conf. Bus. Informatics, CBI 2017, vol. 1, no. June, pp. 129–134, 2017, doi: 10.1109/CBI.2017.39.

J. Wang, Y.-P. Xu, and C. She, “Effect of cloud-based information systems on the agile development of industrial business process management,” J. Manag. Organ., pp. 1–18, 2022, doi: DOI: 10.1017/jmo.2022.49.

D. Kifokeris and C. Koch, “A conceptual digital business model for construction logistics consultants, featuring a sociomaterial blockchain solution for integrated economic, material and information flows,” J. Inf. Technol. Constr., vol. 25, pp. 500–521, 2020, doi: 10.36680/J.ITCON.2020.029.

S. Madakam, R. M. Holmukhe, and D. Kumar Jaiswal, “The Future Digital Work Force: Robotic Process Automation (RPA),” J. Inf. Syst. Technol. Manag., vol. 16, pp. 1–17, 2019, doi: 10.4301/s1807-1775201916001.

F. Xu, H. C. Ho, G. Chi, and Z. Wang, “Abandoned rural residential land: Using machine learning techniques to identify rural residential land vulnerable to be abandoned in mountainous areas,” Habitat Int., vol. 84, pp. 43–56, 2019, doi: 10.1016/j.habitatint.2018.12.006.

D. Liu et al., “A microfluidic-integrated lateral flow recombinase polymerase amplification (MI-IF-RPA) assay for rapid COVID-19 detection,” Lab Chip, vol. 21, no. 10, pp. 2019–2026, 2021, doi: 10.1039/d0lc01222j.

X. Fan et al., “Clinical Validation of Two Recombinase-Based Isothermal Amplification Assays (RPA/RAA) for the Rapid Detection of African Swine Fever Virus,” Front. Microbiol., vol. 11, no. July, pp. 1–12, 2020, doi: 10.3389/fmicb.2020.01696.

T. Chakraborti et al., “From Robotic Process Automation to Intelligent Process Automation: – Emerging Trends –,” Lect. Notes Bus. Inf. Process., vol. 393 LNBIP, pp. 215–228, 2020, doi: 10.1007/978-3-030-58779-6_15.

S. Zhou, “Research on Banking Process Optimization Based on RPA in Financial Sharing Mode,” J. Phys. Conf. Ser., vol. 1865, no. 2, 2021, doi: 10.1088/1742-6596/1865/2/022069.

A. Leshob, A. Bourgouin, and L. Renard, “Towards a Process Analysis Approach to Adopt Robotic Process Automation,” Proc. - 2018 IEEE 15th Int. Conf. E-bus. Eng. ICEBE 2018, no. October, pp. 46–53, 2018, doi: 10.1109/ICEBE.2018.00018.

T. Neifer, P. Bossauer, D. Lawo, R. Volkening, and A. Gadatsch, “The Role of Marketplaces for the Transformation from Robotic Process Automation to Intelligent Process Automation,” no. July, pp. 15–25, 2022, doi: 10.5220/0011146200003280.

F. C. M. Ortiz and C. J. Costa, “RPA in Finance: Supporting portfolio management : Software robot in a portfolio optimization problem,” Iber. Conf. Inf. Syst. Technol. Cist., vol. 2020-June, no. June, pp. 24–27, 2020, doi: 10.23919/CISTI49556.2020.9141155.

Downloads

Published

2023-02-28

How to Cite

Legito. (2023). Examining the Effects of Robotic Process Automation on Operational Efficiency and Business Process Optimization (Literature Study). West Science Interdisciplinary Studies, 1(02), 84–93. https://doi.org/10.58812/wsis.v1i2.91