The term hyperautomation summarises the components of a company’s process automation and integrates tools such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Natural Language Process (NLP) and Intelligent Optical Character Recognition (OCR). Hyperautomation is a way of combining and integrating a wide variety of technologies to automate tasks. Not just repetitive tasks, but also research, analysis, design, metrication, monitoring and more. Gartner named hyperautomation as the top strategic technology trend in 2020 from the published “Top 10 Strategic Technology Trends for 2020”, since then it has been implemented by several companies in different industries.
What is Hyperautomation?
Hyperautomation requires a view of the business as a whole, of the existing processes and what can be improved, as well as what is already automated and what can be automated in an orchestrated way. It is necessary to capture all assets in order to create a roadmap for implementations that generate more business opportunities, improve productivity and reduce costs.
Hyperautomation refers not only to a set of tools, but also to the development of strategies and governance models to detect, analyse, design, automate, measure, monitor and re-evaluate. Understanding the range of automation mechanisms, how they relate to each other and how they can be combined and coordinated is a key focus for hyperautomation and radical business innovation.
There are various considerations for integrating the topic of hyperautomation into one’s own company processes. There is no right or wrong way – but five keywords should be mentioned in this context:
- Mindset: Without the belief that business automation leads to positive results, hyperautomation only wastes the company’s time;
- Roadmap: Identify, prioritise and tackle the company’s processes so that the hyperautomation journey can start;
- Effective: After the roadmap is created, it is a matter of practical application and the creation of automations;
- Administration: When everything is set up, it is important that the main users can understand the process in order to improve it through optimisation and curation or to correct it if necessary;
- Engagement: If employees are not engaged, the model cannot work – automation must therefore not be understood as a substitute for human resources.
The advantages of hyperautomation
While automation can be a pure optimisation of work processes, hyperautomation makes processes even smarter by adding an extra layer of robotic intelligence. As it aims to combine various tools, some with Robotic Process Automation (RPA) and intelligent business management systems, as well as AI approaches, to improve decision-making and agility in terms of assessing, interpreting and initiating an action, it enables the automation and synchronisation of processes across all departments in an organisation. Because multiple tasks can be completed simultaneously, the impact can be measured almost immediately. In addition, errors occur less frequently, making it easier to collaborate. In addition, companies can visualise how functions, processes and metrics work together to add value.
The difference between hyperautomation and intelligent process automation
Hyperautomation is an infrastructure of advanced technologies used to scale automation capabilities in an organisation. It further automates processes that are already automated so that business operations go beyond individual input. These automation technologies include Robotic Process Automation (RPA), artificial intelligence (AI), machine learning, process mining and other tools that identify time-consuming business processes and create the means to automate them.
Intelligent automation, meanwhile, includes tools such as optical character recognition (OCR), AI and machine learning algorithms, but with the goal of simulating human behaviour and intelligence. This type of automation enables companies to process complex operations that would otherwise require human input, analysis or decision-making.
Intelligent automation is just one aspect of hyper-automation technology, alongside others such as RPA, natural language processing (NLP), digital process automation, decision management frameworks and intelligent business process management infrastructures (IBPMS).
Conclusion: Hyperautomation fires the full potential of a company
Hyperautomation provides organisations with a framework to extend, integrate and optimise business automation. A hyperautomation initiative aims to improve a metric or process to achieve better results. It combines advanced technologies such as machine learning, intelligent business management software (iBPMS) and automation tools to fully automate complex business processes.
Hyperautomation brings together different components of process automation and integrates tools and technologies that extend the ability to automate work. It starts with robotic process automation (RPA) at its core and extends the automation capability with artificial intelligence (AI), process mining, analytics and other innovative tools. The idea is to automate more and more knowledge and involve everyone in the company to be part of the transformation.