Organisations that have embraced digital transformation have recognised the advantages that Robotic Process Automation (RPA) has to offer and many of them have implemented it in their key business areas. By enabling businesses to automate certain tasks, RPA has eliminated mundane manual tasks, enhanced cycle time thus ensuring predictability, accuracy, standardization, flexibility and better control. Further to this, businesses have experienced short pay back periods of their investment in RPA and achieved cost savings of 25-50%.
However the primary disadvantage of RPA is that while it has found acceptance for automating select simple and stable processes aimed at tactical quick wins, it has limited applicability and potential for scalability. RPA also has the inability to automate via unstructured data. In most businesses there are many continuous processes that require optimisation and human intervention for decision making and action. This is where hyperautomation could help large organisations in scaling their automation efforts and realise significant returns.
Hyperautomation has caught the imagination of businesses in the last couple of years as it holds the promise of automating the whole body of knowledge work instead of just the simple tasks and rules. Gartner defines hyperautomation as “an effective combination of complementary sets of tools that can integrate functional and process silos to automate and augment business processes.” This approach is also known as Digital Process Automation (Forrester) and Intelligence Process Automation (IDC).
Moving from simple automation of tasks to complex and sophisticated status of automation, hyperautomation has the potential to impact the processes and workflows across multiple stages such that processes are completed with speed, more efficiency and fewer errors. These outcomes are possible to be realised with a mix of automation technologies and artificial intelligence tools such as natural language processing (NLP), optical character recognition (OCR) and machine learning (ML) that not only simplify the processes but also empower and augment human capabilities for ensuing robust design, timely discovery and efficient management of work.
In order to consider an initiative around hyperautomation, firstly it is important to examine the current systems, reengineer the processes as required and eliminate unnecessary steps in tune with the business realities. Since hyperautomation is built around a combination of technologies to augment human productivity, a sound strategy is required to be put in place to support this goal. It would call for a new automation strategy that would be centered around the goal of end-to-end automation and optimisation of digital processes at scale such that business stakeholders are empowered with minimal dependance on technical expertise. Identifying the right complimentary tools for RPA platform based on the prioritised set of addressable problems is an essential step towards this goal. Finally, executive support would be crucial for success. Potential benefits such as customer retention, enhanced revenue, reduced cost, decreased risk or increase in customer satisfaction would make a strong case to win the business mandate for hyperautomation.
Originally appeared in Financial Express