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Key takeaways from the blogIntelligent Automation is the more sophisticated form of the automation continuum. It delivers end-to-end automation in different functions and multi-variate processes. Yet, it simplifies the process architecture and the overall automation approach. Due to these traits, Intelligent Automation is touted as an important tool in the Business Process Automation and Business Process Management technology stacks.
During unplanned and widespread socio-economic disruptions, improving end-to-end process automation, sustainability, and resilience is as equally critical as improving productivity and efficiency. In such situations, automation, process simplification, scalable adoption, unification of siloes, straight-through processing, higher accuracy, and integration of enterprise frameworks assume a higher meaning and importance. These business asks in toto also mean higher productivity and efficiency. Nevertheless, Intelligent Automation drives these critical business requirements in almost all the process-intensive industry sectors, and CoE led championing of Intelligent Automation is the way forward.
A strategy to drive the long-term business goals is imperative. Depending on this strategizing, the CoE shortlists the technologies for the Intelligent Automation mashup to achieve significant results and envisage the bigger picture. Having key process indicators or KPIs to monitor and measure the deployment and results is a must; the paradigm goes, “what is monitored is better managed”.
Intelligent Automation usually mashes up technologies, such as intelligent document processing, robotic process automation, API connectors, workflows, low code-no code platforms, process mining, task mining, artificial intelligence/machine learning, and analytics towards building a self-learning, intelligent, and robust outcome. Intelligent document processing brings unstructured data and written text within the purview of automation. Whereas robotic process automation and APIs build end-to-end automation and process encryption towards a resilient process architecture. The workflows integrate the enterprise frameworks and simplify the processes. The AI/ML algorithms build a continuous-learning-by-exception mechanism. Here, the CoE approach performs an orchestrator role and manages the outcome through the use of analytics.
Intelligent Automation is rightly touted as a BPM technology. It involves definite aspects of business process management and business process automation that achieve a higher target through a CoE-led approach. These aspects are –
A CoE-led automation effort offers an opportunity to select the right tools and platforms to deliver the desired end-results, at scale, across the enterprise. It allows monitoring across all nodes at specified time intervals and ensures continuous evolution of the Intelligent Automation platform. The dashboard-monitoring and insights-led approach allows taking data-driven decisions at key milestones. The simplification achieved through end-to-end automation provides an edge even in a disrupted market and allows looking beyond productivity and efficiency improvements.
Intelligent Automation delivers to Service-Oriented Architecture. It simplifies the processes, builds systemic resilience as well as brings unstructured data within the ambit of automation. The AI/ML-enabled continuous learning ensures systemic evolution. The CoE-led approach creates measurable KPIs and performs an orchestrator role in the entire exercise.