Gartner cited hyperautomation in their report Strategic Technology Trends for 2020. Since then, the phrase has gained a lot of attention, and many companies are looking into how they may begin utilising hyperautomation to reap its benefits. However, many organisations are in a dilemma as to what separates hyperautomation from (regular) automation. We’ll shed some light on the key differences between regular automation and hyperautomation.
With regular automation, you could make a machine do any task, any step of the operational process. It was limited to the automation of physical repetitive tasks. Hyperautomation, on the other hand, is invasive and flexible enough to automate numerous routine tasks by utilizing cutting-edge technologies such as AI, ML, IoT, and others that support every stage of process automation.
To further establish the difference, we must understand the key components of hyperautomation.
Key components of Hyperautomation
Artificial intelligence capabilities: Machine Learning (ML), Natural Language Processing (NLP), intelligent Optical Character Recognition (OCR), and Artificial Intelligence (AI) computer vision are all examples that allow robots to read, see, and process more work.
Advanced process mining tools: Platforms that can examine how your teams work in detail to show you what you can and should automate.
Workforce engagement: Ability to engage grassroots workforce and executives across the organisation, including both functional and technical workers, to recognise the value of automation and contribute to hyperautomation.
Advanced analytics: To enable continuous growth, track, measure, and prove the business outcomes delivered by automation.
At Neebal, we identified this trend at its inception and have developed advanced solutions that not only meet organisational needs for hyperautomation but are also flexible enough to align with specific business goals.
Using Hyperautomation, we digitised multiple processes and provided actionable insights on sales projections for one of the largest agrochemical companies in India, resulting in an astounding 80% reduction in time required to achieve similar results manually. Read the full case study.