Hyperautomation – Simplify operational complexity
Hyperautomation – Simplify operational complexity
Singular task automation tends to build up over time into siloed mesh with low to no interconnectivity that tends to build operational complexity with time. The rise in demand for remote operations and process optimization is driving the need for Hyperautomation. It cuts through different process automation and in the process tends to simplify the operational complexity.
Hyperautomation, as an automation approach leads to a solution architecture comprising a range of tools and capabilities, including but not limited to Robotic Process Automation (RPA), Intelligent Document Processing (IDP), Intelligent Business Process Management Suites (iBPMS), Integration Platform-As-A-Service (iPaaS), process mining, and Artificial Intelligence (AI). Low-code and configuration-driven, intuitive development and citizen user-friendly user experience (UX) are other key attributes of the architectural components of Hyperautomation.
How does Hyperautomation work?
Hyperautomation orchestrates multiple technologies and drives common business outcomes. It includes intelligent document processing (IDP), robotic process automation (RPA), business process management (BPM) technologies, artificial intelligence/machine learning (AI/ML), and low code-no code platforms that deliver end-to-end automation. It involves multiple departments and stakeholders who bear shared accountability. This aggregation of people, processes, and technology is important for simplifying processes and operations.
HYPERAUTOMATION IMPLEMENTATION FRAMEWORK
Achieving success with process automation initiatives calls for synergies between People, Process, and Technology facets. RPA skills shortage, poor change management, lack of business-IT alignment, ill-defined success criteria, and disregard for infrastructure management considerations are frequently-cited factors leading to failure of automation initiatives. Our proprietary framework for Hyperautomation implementation, best practices, and implementation methodologies ensure scale and resiliency irrespective of the underlying tools and deployment model.
Hyperautomation drives enterprise agility
Hyperautomation looks beyond point automation to drive end-to-end automation, intelligent autonomous systems, and straight-through processing. It takes a modular approach such that as enterprise policies change over time, it is easy to adapt in an agile environment through a pre-defined architecture. It drives growth acceleration and operational excellence.
It synergizes the operations between different business units to drive automation at scale and builds enterprise resilience. It improves on the fragility and shortcomings of individual task automation to drive business value that is greater than the standalone processes. A center of excellence-driven approach allows monitoring the KPIs through the different stages.
Simply put
Hyperautomation allows enterprises to grow from a mesh of point automation to comprehensive end-to-end automation directed at simplifying operational complexity. It aggregates the strengths of individual technologies and processes to deliver value greater than the sum of parts.