Upgrading Traditional Automation With Robotic Process Automation In Digital Transformation
LI, Yijie (2024-11-18)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2024111894721
https://urn.fi/URN:NBN:fi-fe2024111894721
Tiivistelmä
ABSTRACT:
The digital transformation of enterprises is a comprehensive process in which Robotic Process Automation (RPA) is a significant factor in enhancing efficiency and competitiveness. This thesis studies the integration of RPA in upgrading traditional automation systems within a global com-pany's Master Data Management (MDM) department, examining the consequences on sustain-able competitive advantage and departmental operations. The empirical research, drawing on the Manufacturing Strategy Index (MSI) and the Sense and Respond (S&R) frameworks, evalu-ates the alignment of RPA implementation with corporate strategies focused on cost, quality, delivery, and flexibility. The study provides a comprehensive analysis of resource allocation, op-erational risks, and strategic positioning through a combination of qualitative and quantitative methods—particularly AHP, CFI, BCFI, and NSCFI models. The findings reveal that RPA, particu-larly through UiPath's platform, not only reduces operational costs but also enhances accuracy and speed, resulting in a shift in departmental strategy towards more agile and proactive pro-cesses. Through a comprehensive analysis underpinned by models of strategic coherence and effectiveness, this thesis plans and presents a roadmap for integrating RPA into corporate pro-cesses, offering insights into the broader discourse on digital evolution in organizational environ-ments.
The digital transformation of enterprises is a comprehensive process in which Robotic Process Automation (RPA) is a significant factor in enhancing efficiency and competitiveness. This thesis studies the integration of RPA in upgrading traditional automation systems within a global com-pany's Master Data Management (MDM) department, examining the consequences on sustain-able competitive advantage and departmental operations. The empirical research, drawing on the Manufacturing Strategy Index (MSI) and the Sense and Respond (S&R) frameworks, evalu-ates the alignment of RPA implementation with corporate strategies focused on cost, quality, delivery, and flexibility. The study provides a comprehensive analysis of resource allocation, op-erational risks, and strategic positioning through a combination of qualitative and quantitative methods—particularly AHP, CFI, BCFI, and NSCFI models. The findings reveal that RPA, particu-larly through UiPath's platform, not only reduces operational costs but also enhances accuracy and speed, resulting in a shift in departmental strategy towards more agile and proactive pro-cesses. Through a comprehensive analysis underpinned by models of strategic coherence and effectiveness, this thesis plans and presents a roadmap for integrating RPA into corporate pro-cesses, offering insights into the broader discourse on digital evolution in organizational environ-ments.