Challenges and Strategies in Robotic Process Automation Integration: Crafting Success Framework within Business Process Management

Abstract

RPA has become extensively implemented for efficiency enhancement in BPM. However, there are some common issues such as implementation failures, integration problems, and scalability constraints experienced by most companies, which can be attributed to technical, organizational, and governance concerns. The current research conducted an empirical investigation aimed at developing a validated evidence-based framework for forecasting and enhancing the successful integration of RPA into BPM environments. For this purpose, a sequential explanatory mixed-methods approach was employed. In the first stage, quantitative survey of 309 BPM/RPA practitioners was conducted. The results revealed satisfactory reliability of the measuring instrument (Cronbach's Alpha = 0.612 – 0.879). Moreover, exploratory factor analysis provided strong evidence on the presence of construct validity (KMO = 0.829; Bartlett’s Test, p<0.001). Quantitative data were analysed using descriptive statistics, Spearman correlation, ordinal regression, multiple regression, and Kruskal–Wallis tests. Phase II was a set of semi-structured interviews with eight experienced RPA practitioners and automation leaders, analysed through thematic analysis. The findings indicated that technical integration challenges are widespread and do not differ significantly by organisational size. Process Selection Maturity (ρ = 0.314, p< 0.001), Executive Sponsorship Quality (ρ = 0.277, p < 0.001), and Governance Structure and Centre of Excellence Effectiveness (ρ = 0.270, p < 0.001) were significantly and positively related to RPA implementation success. Digital Maturity was the strongest predictor: the ordinal regression model fitted the data well (χ² = 44.509, p < 0.001; Nagelkerke R² = 0.171) and showed a significant positive effect (β = 1.466, p < 0.001). The change management model was significant overall (R² = 0.148, F = 17.614, p < 0.001) but change management effectiveness and organisational change readiness did not have significant direct effects on implementation outcomes. The qualitative results highlighted the role of user acceptance, organizational readiness, process standardization, API-integration, and Centres of Excellence governed from the center in enabling sustainability of automation. The study resulted in development of the SUCCESS framework that provides organizations with practical guidance to evaluate their automation readiness and reduce risks associated with automation adoption.
Keywords: Robotic Process Automation, Business Process Management, Digital Transformation, Process Selection Maturity, SUCCESS Framework