Paper Number
1770
Paper Type
Complete Research Paper
Abstract
Robotic process automation (RPA) uses ‘software bots’ to replicate humans. This study examines an emerging organizational challenge associated with RPA---process knowledge loss (PKL) that surfaces when bots start substituting employees' repetitive and rule-based tasks. RPA-related PKL can negatively impact productivity, continuous process improvement, and intended benefits. Research in this field is in its early stages. To explore RPA-related PKL, a single revelatory case study with an apparel manufacturing company was conducted. Based on the qualitative analysis of case data, a conceptual model explaining factors that influence PKL categories (i.e., intentional or unintentional) is presented. Furthermore, three types of process knowledge (i.e., coordination, contextual, and experiential) are explained. The factors and interrelationships are explained using the knowledge-based view. The findings extend the RPA knowledge base by providing a detailed account of factors resulting in PKL. This study contributes to practice by assisting organizations in developing mitigation strategies to overcome RPA-related PKL.
Recommended Citation
Mirispelakotuwa, Ishadi Upeksha Meekotuwa; Syed, Rehan; and Wynn, Moe, "Is RPA-Related Process Knowledge Loss Real?" (2024). ECIS 2024 Proceedings. 10.
https://aisel.aisnet.org/ecis2024/track08_bpm_di/track08_bpm_di/10
Is RPA-Related Process Knowledge Loss Real?
Robotic process automation (RPA) uses ‘software bots’ to replicate humans. This study examines an emerging organizational challenge associated with RPA---process knowledge loss (PKL) that surfaces when bots start substituting employees' repetitive and rule-based tasks. RPA-related PKL can negatively impact productivity, continuous process improvement, and intended benefits. Research in this field is in its early stages. To explore RPA-related PKL, a single revelatory case study with an apparel manufacturing company was conducted. Based on the qualitative analysis of case data, a conceptual model explaining factors that influence PKL categories (i.e., intentional or unintentional) is presented. Furthermore, three types of process knowledge (i.e., coordination, contextual, and experiential) are explained. The factors and interrelationships are explained using the knowledge-based view. The findings extend the RPA knowledge base by providing a detailed account of factors resulting in PKL. This study contributes to practice by assisting organizations in developing mitigation strategies to overcome RPA-related PKL.
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