Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F24%3A00010288" target="_blank" >RIV/46747885:24310/24:00010288 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/article/10.1007/s10257-024-00686-y" target="_blank" >https://link.springer.com/article/10.1007/s10257-024-00686-y</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10257-024-00686-y" target="_blank" >10.1007/s10257-024-00686-y</a>

Result language

angličtina

Original language name

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Original language description

Companies that use robotic process automation very often deal with problems maintaining the bots in their RPA portfolio. Current key performance indicators do not track the behavior of RPA bots or processes. For better maintainability of RPA bots, it is crucial to easily identify problematic behavior in RPA bots. Therefore, we propose a strategy that tracks and measures the behavior of processes to increase the maintainability of RPA bots. We selected indicators of statistical dispersion for measuring variability to analyze the behavior of RPA bots. We analyzed how well statistical dispersion can describe the behavior of RPA bots on 12 processes. The results provide evidence that, by using statistical dispersion for behavioral analysis, the unwanted behavior of RPA bots can be described. Our results showed that statistical dispersion can describe the success rate with a correlation of -0.91 and outliers in the data with a correlation of 0.42. This research implies that we can describe the behavior of RPA bots with variable analysis. Furthermore, with high probability, it can also be used for analyzing other processes, as a tool for gaining insights into performance and as a benchmark tool for comparing or selecting a process to rework.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Information Systems and e-Business Management

ISSN

1617-9846

e-ISSN

—

Volume of the periodical

22

Issue of the periodical within the volume

4

Country of publishing house

DE - GERMANY

Number of pages

18

Pages from-to

741-758

UT code for WoS article

001302270100001

EID of the result in the Scopus database

2-s2.0-85202747335