In the words of Gartner research vice-president Fabrizio Biscotti: “Hyperautomation has shifted from an option to a condition of survival. Organisations will require more IT and business process automation as they are forced to accelerate digital transformation plans in a post-COVID-19, digital-first world.”
Gartner has subsequently revealed that 85% of its clients say they will increase or sustain hyperautomation investment strategies during the coming year. Given such uptake, it is no surprise the company is also predicting the worldwide market for technology that enables hyperautomation will reach almost $600 billion in 2022, a leap from $481 billion in just two years.
Of course, not every business has yet joined the revolution and for those late to the party, it all starts with one question – what is hyperautomation?
Hyperautomation is the extension of traditional automation opportunities beyond the confines of individual processes, bringing together several components of process automation and integrating advanced tools and technologies to amplify the ability to automate work. Starting with robotic process automation (RPA) at its core, it expands a business’s automation capability via the likes of AI, machine learning, process mining, and analytics.
While the adoption of RPA has been a revolution of its own in the past couple of decades, there has been a dawning realisation that it can be a challenge to scale at the enterprise level and is limited in the types of automation it can achieve. Indeed, a 2019 assessment by Gartner found only about 13% of enterprises were able to scale early RPA initiatives, making it abundantly clear that businesses need more when it came to their automation needs.
Hyperautomation has been a response to that challenge. It has introduced a studied approach to automation that involves identifying what work to automate, choosing the right automation tools and extending RPA capabilities by introducing various AI and machine learning tools. In a world where automating complex business processes can save companies untold dollars and increase efficiencies, hyperautomation is enabling real digital transformation.
More collaboration: the seamless connection between various teams, colleagues and departments is a key goal for any executive and hyperautomation ticks that box. The blend of RPA, intelligent tools and software robots can connect users across various arms of an organisation, from finance and HR teams to IT and customer service agents. Hyperautomation is not just a tool – it’s a transformation.
More productivity: nothing drains an employee’s morale and increase a manager’s frustration than seeing quality staff spending endless hours on repetitive, time-consuming tasks. Hyperautomation’s use of cutting-edge technology removes bottlenecks, finetunes processes and reduces manual tasks so a collective workforce not only delivers better productivity on more rewarding work but does so with more enthusiasm.
More insights: it is impossible for businesses to improve efficiencies and optimise processes if they do not where such inefficiencies lie. Enter advanced analytics, which delivers the data one needs to pinpoint areas of concern and show how automation may deliver a better return on investment. Hyperautomation is changing businesses for the better by providing them with data that not only allows them to understand trends but make predictions based on corrections and refinements.
Futureproofing: while RPA and traditional bots can execute simple steps to complete a task, hyperautomation takes things to a whole new level by creating machines that can study business processes, understand how they work and continually help improve them. Rather than seeing technology infrastructure grow stale and need to be replaced, organisations are future-ready and it is all because hyperautomation evolves and grows with a business.
Process mining and task mining tools identify and prioritise automation opportunities.
Automation development tools such as RPA, no-code/low-code development tools, iPaaS for integrations and workload automation tools reduce the effort and cost of building automation.
Business logic tools make it easier to adapt and reuse automation, with key examples including intelligent business process management, decision management and business rules management.
AI and machine learning tools are great for extending the capabilities of automation. Look no further than natural language processing (NLP), optical character recognition, machine vision, virtual agents and chatbots.
For anyone needing further proof why their business should join the list of ‘hyperautomation companies’, consider Gartner’s finding that the combination of hyperautomation technologies and redesigned processes will see organisations cut their operation costs by 30% by 2024. As Gartner’s Cathy Tornbohm said: “The shift towards hyperautomation will be a key factor enabling enterprises to achieve operational excellence and subsequently cost savings, in a digital-first world.”
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