ABCD-RPA: A framework for automatable bot candidate detection for robotic process automation

As organizations strive for increased efficiency and agility in their business processes, the intersection of Robotic Process Automation (RPA) and business process modeling is crucial. Integrating RPA into existing business process modeling frameworks harnesses the synergies between human-driven and automated processes, which can bring great benefits to various business organizations. This research investigates the impact of RPA on business process optimization, scalability, and adaptability. It provides insights into the strategic advantages and challenges of integrating RPA into business process modeling, exploring the relationship between automated robotic processes and human-driven models to take full advantage of them. Through an in-depth examination of implementation frameworks and technological interfaces, this research sheds light on the potential of incorporating RPA into traditional business process modeling structures. This paper proposes a framework that integrates robotic process automation into business process modeling. This serves as a foundation for the effective deployment of RPA, providing insights into the requirements necessary for successful automation. We aim to minimize the need for manual RPA development. Thus, software bots can automatically implement repetitive manual tasks performed by RPA developers. In the proposed framework, repetitive, deterministic, and medium-to-long duration activities are the prime targets for automation. Finally, we evaluate the proposed framework’s modules across various real-life data sets to generate automated tasks with minimal human intervention. The results are cross-examined with a state-of-the-art benchmark with similar processing settings.