Hyper automation is a concept that combines several automation resources to perform more complex tasks in companies. In this way, technology allows employees to perform activities that machines cannot function, ensuring more productivity and efficiency for organizations.
The concept of hyper-automation goes far beyond the simple automation that some processes already provide in the corporate world. And the consequences of its adoption are, without a doubt, a leap in technological development, productivity, cost reduction, and competitiveness. Follow our article and learn how hyper-automation will transform companies and how we deal with processes.
What Is Hyper-Automation?
Hyper automation is the intelligent evolution of process automation. In this new concept, a combination of advanced technologies is used to automate simple repetitive tasks, considering the company as a whole and orchestrating the automated processes as a single functioning organism.
Hyper automation processes today can rely on technologies such as Artificial Intelligence, Machine Learning, Robotic Process Automation, and Natural Language Processing, among others.
The goal of hyper-automation is to make as many automated processes as possible independent of human action. The idea is to automate the work of machines, making them think and execute the entire process before, during, and after without the need for human action.
Unlike simple automation, hyper-automation combines an ecosystem of advanced technological tools with a new way of working, adding sophistication and complexity to automated processes.
Thus, it is possible to dedicate human skills to more specialized tasks that depend on skills that machines cannot acquire, such as creativity, empathy, and leadership.
The consequences of hyper-automation are more agile processes, lower error rates, better use of data, and increased productivity. Sounds good.
What Are The Benefits Of Hyper-Automation?
The goal of hyper-automation is to make different advanced technologies work together to replace human presence whenever possible.
And the first advantage of adopting hyper-automation is the increase in the speed of processes. This acquired agility means productivity and production growth while costs are reduced.
Another significant reduction in the occurrence of human errors. After a specific time performing repetitive tasks, the human brain quickly disperses, allowing involuntary mistakes due to lack of attention. Machines do not get tired or distracted, maintaining performance throughout the execution of the task.
Another human limitation in various activities is physical or mental fatigue. Specific tasks must be interrupted periodically for the person to recover physically. Once again, machines can maintain the job without interruption and perform a more significant number of assignments in the same amount of time.
For sectors such as logistics, hyper-automation presents a vast potential for use. For example, some retail giants, such as Amazon, invest in increasingly automated product delivery logistics.
Improving the user experience is always the end goal—a quick purchase without barriers and effort, minimal human interaction, and increasingly fast deliveries.
The areas that work with big data can benefit significantly from hyper-automation. Intelligent machines, capable of learning user behavior and making decisions without human intervention, are used for fraud detection, customer profile design, targeting offers, etc.
What Are The Main Components Of Hyper-Automation?
Here are some of the critical technologies used when embracing hyper-automation. These resources are typically combined, creating the best solution for the process within the company’s routine.
Robotic Process Automation (RPA)
As Robotic Process Automation software is known, Bots perform a wide range of tasks, from triggering automatic emails to performing procedures in ERP systems.
This is the technology used in customer service chats, for example, directing users more quickly and efficiently to a solution to their demand.
Artificial Intelligence (AI)
Artificial intelligence can be integrated into RPA, making bots adapt to process differences and not just be limited to repetitive tasks. That’s because AI allows the program to make decisions autonomously without relying on human intervention.
Machine Learning (ML)
It is undoubtedly one of the technologies that transform the machine into the closest thing to human intelligence. That’s because machine learning simulates how we learn through observation, repetition, and execution of a process.
Thus, a machine can change how it performs a task based on the data exchanged with the external environment after a few occurrences of a new circumstance.
Natural Language Processing (NLP)
NLP is already widely used by all of us, whether in voice commands on mobile devices or intelligent assistants when talking to robots on the phone or in customer service channels. Its use in the corporate environment can increase the ease and agility of routine processes, contributing to greater productivity.
Intelligent Optical Character Recognition (ICR)
Just as NLP simulates human hearing, understanding, and processing of what we say, IRC simulates our vision. Thus, it is possible to process data much more quickly and efficiently, automatically reading information printed on a surface.
This technology still has a reading accuracy well below the accuracy of NLP, but it is already quite effective for many tasks, especially when combined with other technologies. Significant changes in the way we process registrations, forms, contracts, and documents, in general, will be observed in the coming years with the development of IRC.
How To Implement Hyper-Automation?
As with any investment in IT infrastructure, hyper-automation must be planned. Making a roadmap is the first step to analyzing the possibilities and mapping how and where the changes and automation will be implemented.
In addition to technical planning, it is always good to remember that the teams involved in the changes must be trained, aware and engaged. Hyper automation demands a new mindset geared toward this new technological model.
In addition, planning, execution, documentation, and evaluation are essential to keep track of implementation results and establish continuous improvements in automation.