Browsing by Author "Tew, Mark"

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    Investigating the factors driving adoption of RPA in South African banking: a qualitative analysis
    (2020) Tew, Mark; Budree, Adheesh
    Background: Studies have shown that the traditional banking sector is under threat from digital banks and financial technology (fintech) organisations that can operate with a lower cost base and respond to the market faster. In response to this threat, leading banks have implemented Robotic Process Automation (RPA) to reduce costs and simplify operations. The adoption of RPA has, however, proven to be challenging as in many cases the impact of automation technology implementations is perceived to affect the livelihoods of staff who work in banks. Within the South African banking context, there is a particular sensitivity to factors that impede employment and labour unions are deeply involved in protecting workers. Objective: While there is research on RPA implementations, it is limited in the banking context. Further, there is currently little to no RPA adoption research specifically in the South African banking context. This study seeks to investigate the factors that drive RPA adoption in South African banks. Method: This study has used the Technology-Organisation-Environment (TOE) framework, extended with Institution Theory, as a lens to structure an approach in organising RPA adoption factors in an extensive literature review on the phenomenon. Thematic analysis was used to analyse the interview data that was collected. Themes were aggregated and organised by the TOE perspectives to create structure throughout the study. Results: The findings were that the adoption of RPA in South African banks is driven by the expected benefits of RPA which are achieved when well-suited processes are targeted, an effective operating model for the program including business and IT personnel, with the right skills. A well-designed change program is critical for RPA adoption in banks. South African banks are also working closely with the trade unions and are, on the whole, following best practices when automating parts of their workforce's roles by ensuring that they are given the opportunity to work on more engaging tasks.