Robotic Process Automation (RPA) in Accounting: Measuring ROI and Workforce Displacement
Keywords:
Robotic Process Automation, Accounting Automation, RPA, Return on Investment, Digital Labor, Workforce Displacement.Abstract
The paper examines how Robotic Process Automation (RPA) can be applied to the accounting field in terms of both workforce displacement and the payback (return on investment) or ROI. It applies the dual-lens methodology of incorporating the financial performance analysis and workforce impact assessment. The information is gathered from industry surveys and vendor reports on case studies of the early adopters like the large professional service firms. The findings demonstrate that RPA has high financial advantages. The accounting processes save up to 25 to 50% and ROI in high-volume processes up to 135%. The payback period is also very short ranging between 6-18 months. It decreases the error rates by up to 90% and decreases the process time by 60% to 80%, resulting in quicker financial reporting and higher decision-making. The research also concludes that RPA also has an impact on employment. Simple tasks like data entry are reduced by approximately 40%. This illustrates the fact that RPA leads to change and not retrenchment. The paper suggests that the RPA can enhance the efficiency and performance in the accounting area; however, organizations will need to adapt to changes in the workforce by training and reskilling.
Downloads
References
W. M. P. Van Der Aalst, M. Bichler, and A. Heinzl, “Robotic Process Automation,” Business & Information Systems Engineering, vol. 60, no. 4, pp. 269–272, May 2018, doi: 10.1007/s12599-018-0542-4.
S. Anagnoste, “Robotic Automation Process - The next major revolution in terms of back office operations improvement,” Proceedings of the ... International Conference on Business Excellence, vol. 11, no. 1, pp. 676–686, Jul. 2017, doi: 10.1515/picbe-2017-0072.
A.-M. Zaharia-Radulescu, C. Pricop, D. Shuleski, and A. C. Ioan, “RPA and the future of workforce,” Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, vol. 11, no. 1, pp. 384–392, Jan. 2017, [Online]. Available: https://ideas.repec.org/a/rom/mancon/v11y2017i1p384-392.html
S. Alexander, A. Haisermann, T. Schabicki, and S. Frank, “Robotic Process Automation (RPA) im Rechnungswesen und Controlling - welche Chancen ergeben sich?,” Controlling, vol. 30, no. 3, pp. 11–19, Jan. 2018, doi: 10.15358/0935-0381-2018-3-11.
B. Bygstad, “Generative Innovation: A comparison of lightweight and heavyweight IT,” Journal of Information Technology, vol. 32, no. 2, pp. 180–193, May 2016, doi: 10.1057/jit.2016.15.
R. Isaac, R. Muni, and K. Desai, “Delineated analysis of robotic process automation tools,” Zenodo (CERN European Organization for Nuclear Research), Dec. 2017, doi: 10.5281/zenodo.1134258.
D. Fernandez and A. Aman, “Impacts of robotic process automation on global accounting services,” Asian Journal of Accounting and Governance, vol. 9, pp. 123–132, Apr. 2018, doi: 10.17576/ajag-2018-09-11.
L. Willcocks, M. Lacity, and A. Craig, “Robotic Process Automation: Strategic Transformation lever for global business services?,” Journal of Information Technology Teaching Cases, vol. 7, no. 1, pp. 17–28, Mar. 2017, doi: 10.1057/s41266-016-0016-9.
A. Asatiani and E. Penttinen, “Turning robotic process automation into commercial success – Case OpusCapita,” Journal of Information Technology Teaching Cases, vol. 6, no. 2, pp. 67–74, May 2016, doi: 10.1057/jittc.2016.5.
S. Aguirre and A. Rodriguez, “Automation of a business process using Robotic Process Automation (RPA): a case study,” in Communications in computer and information science, 2017, pp. 65–71. doi: 10.1007/978-3-319-66963-2_7.
A. Kanellou and C. Spathis, “Accounting benefits and satisfaction in an ERP environment,” International Journal of Accounting Information Systems, vol. 14, no. 3, pp. 209–234, Jan. 2013, doi: 10.1016/j.accinf.2012.12.002.
A. F. Borthick and R. R. Pennington, “When data become ubiquitous, what becomes of accounting and assurance?,” Journal of Information Systems, vol. 31, no. 3, pp. 1–4, Sep. 2017, doi: 10.2308/isys-10554.
D. Appelbaum, A. Kogan, and M. A. Vasarhelyi, “Big data and analytics in the modern audit engagement: research needs,” Auditing a Journal of Practice & Theory, vol. 36, no. 4, pp. 1–27, Feb. 2017, doi: 10.2308/ajpt-51684.
D. Acemoglu and P. Restrepo, “Robots and Jobs: Evidence from US Labor Markets,” Mar. 2017. doi: 10.3386/w23285.
M. Arntz, T. Gregory, and U. Zierahn, “The risk of automation for jobs in OECD countries,” OECD Social Employment and Migration Working Papers, May 2016, doi: 10.1787/5jlz9h56dvq7-en.
J. Bessen, “How computer automation affects occupations: technology, jobs, and skills,” Scholarly Commons at Boston University School of Law, 2016. https://scholarship.law.bu.edu/faculty_scholarship/813
D. H. Autor, “Why are there still so many jobs? The history and future of workplace automation,” The Journal of Economic Perspectives, vol. 29, no. 3, pp. 3–30, Jul. 2015, doi: 10.1257/jep.29.3.3.
J. Mokyr, C. Vickers, and N. L. Ziebarth, “The history of technological anxiety and the future of economic growth: Is this time different?,” The Journal of Economic Perspectives, vol. 29, no. 3, pp. 31–50, Jul. 2015, doi: 10.1257/jep.29.3.31.
J. Dai and M. A. Vasarhelyi, “Toward Blockchain-Based accounting and assurance,” Journal of Information Systems, vol. 31, no. 3, pp. 5–21, Jun. 2017, doi: 10.2308/isys-51804.
A. Gepp, M. K. Linnenluecke, T. O’Neill, and T. Smith, “Big data techniques in auditing research and practice: Current trends and future opportunities,” SSRN Electronic Journal, Jun. 2018, doi: 10.2139/ssrn.2930767.
H. Brown-Liburd, H. Issa, and D. Lombardi, “Behavioral implications of big data’s impact on audit judgment and decision making and future research directions,” Accounting Horizons, vol. 29, no. 2, pp. 451–468, Jan. 2015, doi: 10.2308/acch-51023.
A. Kogan, M. G. Alles, M. A. Vasarhelyi, and J. Wu, “Design and evaluation of a continuous data level auditing system,” Auditing a Journal of Practice & Theory, vol. 33, no. 4, pp. 221–245, Jun. 2014, doi: 10.2308/ajpt-50844.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
