Understanding how hyperautomation augments existing automation processes, and why is it important?

Hyperautomation has been mentioned as trend number one on Gartner's list of  Top 10 Strategic Technology Trends for 2020. Also dubbed as Digital Process Automation by Forrester, this technology equates to enhancing the capability of current modern machines. It is a mixture of various primary technologies ranging from robotic process automation (RPA), intelligent business management software (iBPMS), machine learning (ML), and artificial intelligence (AI). It impels the maximal usage of rational processes that can be automated by hardware or software robots.

As implied by its' name, it takes automation a step further. Here it prioritizes eliminating the dependence of the input of human assistance. Though conventional automation aids in the optimization of task processes, hyper-automation adds an extra layer of robotic intelligence that makes the process even faster, error-free and end-end automation. This is what makes it an inevitable trend in the race for digital transformation. Further, it can be thought of as a discipline that augments human capabilities instead of replacing them.

By leveraging this technology, businesses can upskill RPA with intelligence and create Digital Workers who can work on rote organizational activities to augment employee performance. Apart from that, they can connect to various business applications, operate with structured and unstructured data, analyze data and make decisions, and discover processes and new automation opportunities. All of these were not possible earlier from conventional automation techniques. In layman's context, hyperautomation not only validates the importance of automation it also augments it to show how the combination of RPA and AI, ML, process mining, decision management, and Natural Language Processing (NLP) can be used together in an end-to-end automation solution.

Along with that, hyperautomation helps in building a digital twin of the organization (DTO). DTO is a group of software models that make up an organization, and it allows companies to model any number of scenarios that could impact their digital business. While considered to be at the forefront of the 4th Industrial Revolution, it also promises to enhance customer experience (CX), intensify recommendation system, accelerate logistics, and employee engagement. It can help businesses to unlock new cost savings and develop new revenue streams through analytical insights. It empowers both people and robots to automate together, from basic processes to more complex, long-running, end-to-end business processes

Currently, hyperautomation is attracting companies mainly in oil and gas industries, mining sector, and utilities. Gartner projects that by 2024, a minimum of 30 percent of operational costs will be lowered if companies adopt hyper-automation technologies.  To build a hyperautomation network, companies need to have a workforce comprising up of tech talent and non-tech talent working in different fields. This workforce team can include data scientists, RPA developers, and testers, SMEs, business analysts, and operational executives.