Towards discovering erratic behavior in robotic process automation with statistical process control

Petr Průcha ()
Additional contact information
Petr Průcha: Technical University of Liberec

Information Systems and e-Business Management, 2024, vol. 22, issue 4, No 5, 758 pages

Abstract: Abstract Companies that frequently use robotic process automation often encounter difficulties in maintaining their RPA portfolio. To address these problems and reduce time spent investigating erratic behavior of RPA bots, developers can benefit from exploring methods from process sciences and applying them to RPA. After a selection process, we examine how variability and deviations impact robotic process automation. Indicators of statistical dispersion are chosen to assess variability and analyze RPA bot behavior. We evaluate the performance of RPA bots on 12 processes, using statistical dispersion as a measure. The results provide evidence that variability is an undesirable form of erratic behavior in RPA, as it strongly correlates with the success rate of the bots. Importantly, the results also show that outliers do not affect the success rate of RPA bots. This research suggests that variable analysis can help describe the behavior of RPA bots and assist developers in addressing erratic behavior. Additionally, by detecting variability, we can more effectively handle exceptions in RPA.

Keywords: Behavioral analysis of RPA; Robotic process automation; Benchmarking RPA processes; Robotic process automation KPI (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10257-024-00686-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infsem:v:22:y:2024:i:4:d:10.1007_s10257-024-00686-y

Ordering information: This journal article can be ordered from
http://www.springer. ... ystems/journal/10257

DOI: 10.1007/s10257-024-00686-y

Access Statistics for this article

Information Systems and e-Business Management is currently edited by Jörg Becker and Michael J. Shaw

More articles in Information Systems and e-Business Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().