A process analysis framework to adopt Intelligent Robotic Process Automation (IRPA) in supply chains

Sandali Waduge, Ranil Sugathadasa, Ashani Piyatilake, Samudaya Nanayakkara

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
14 Downloads (Pure)

Abstract

Intelligent Robotic Process Automation (IRPA) combines Artificial Intelligence (AI) and Robotic Process Automation (RPA) to automate complex unstructured tasks, improve decision-making, and cope with changing scenarios. A process analysis framework for IRPA adoption was developed by identifying key factors through a literature review and semi-structured expert opinion survey. The employed experts in the survey comprised RPA/IRPA consultants, RPA/IRPA initiative team leaders, and RPA/IRPA developers with three years or more experience. For the initial factor collection phase, there were a total of eighteen (18) responses, and for the factor evaluation phase, a total of twenty-six (26) experts were used to collect responses. Identified factors were shortlisted and evaluated using a Relative Importance Index (RII) analysis. The study’s findings are presented through a Causal-Loop Diagram (CLD) to illustrate the relationships between factors. The framework provides practical guidance for organizations planning to adopt IRPA, informing decision-making, resource allocation, and strategy development. The final process analysis framework highlights the importance of accuracy, level of human involvement in a task, and standardization as the main three primary factors for successful IRPA adoption. Three major secondary factors were identified: digital data input, integration with existing systems, and the cost of adopting new technologies. This research contributes to the added value to existing knowledge and serves as a foundation for future research in IRPA adoption.

Original languageEnglish
Article number9753
Number of pages18
JournalSustainability (Switzerland)
Volume16
Issue number22
DOIs
Publication statusPublished - Nov 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

  • causal loop diagram
  • intelligent robotic process automation
  • process analysis framework
  • relative importance index
  • robotic process automation

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