Hyperautomation came in at number one on Gartner’s ranking of the Top 10 Strategic Technology Trends for 2020. The publication has also purported that businesses could lower their costs by roughly 30% by the year 2024 through the use of this new technology. In this short guide, we’re going to explore hyperautomation and why it has the “significant potential for disruption” that everyone is talking about. First, let’s talk about the official definition of hyperautomation.
There are several definitions that can be found across the web but the simplest one comes from Leapwork, which defines hyperautomation as “the mix of automation technologies and artificial intelligence that, when combined, augment humans’ capabilities, allowing them to complete processes faster, more efficiently, and with fewer errors.” It is the convergence of automation tools, packaged software, machine learning, and artificial intelligence that is set to revolutionize the way that businesses automate their processes on an incredible scale. As automation becomes increasingly popular across all industries, the technology businesses use to make that happen is evolving. The increased demand is driving innovation and hyperautomation is the ultimate destination of it all.
Business process automation uses a variety of tools to optimize individual processes. One of the first innovations to emerge in this space was Robotic Process Automation. RPA is an automation process where software (in this case, robots) can be programmed to replicate tasks based on a set of rules. This type of tool is something that is easy to integrate into existing systems and it is highly scalable, which makes it supremely attractive to businesses that exist in the dynamic landscape we see today. It also greatly reduces the need for human intervention. Hyperautomation has evolved from that.
Sometimes you may see it referred to as Digital Process Automation or Intelligent Process Automation. The intelligence element is what sets hyperautomation apart entirely because it combines RPA with machine learning. Machine learning is a branch of artificial intelligence. Similar to RPA, it doesn’t rely very heavily on human intervention because these systems use pattern recognition to determine the next course of action. Once a system is trained, its algorithm is able to determine patterns and learn from them, then carry out processes in an optimized way based on the patterns it has detected. Instead of just focusing on rules-based tasks, they can carry out critical knowledge work as well. Machine learning takes RPA and transforms it into an adaptive and intelligent tool. There are several other technologies that come together to create hyperautomation. These additional tools are:
- AI and Business Rules
- Case Management
- Intelligent Business Process Management Systems (iBPMS)
- Process Management
When all of these different tools are put together, they function in tandem to go far beyond the capabilities they hold individually. This allows businesses to harness this trend to go beyond simple business process automation and simply do more, better. One thing to keep in mind, which is part of what makes hyperautomation such a unique innovation, is that it is not simply a tool to replicate tasks and replace a human workforce. Instead, it is a means of allowing technology to work collaboratively with humans to maximize the capabilities of both. It is an innovation that allows for deeper engagement with an existing workforce and sets the stage for significant evolution in the automation of knowledge work in the future. Hyperautomation allows previously inaccessible data and strictly-human processes to be fully integrated, automated, and optimized.
Even the simple steps of business process automation get significantly more sophisticated in the process of hyperautomation. Artificial Intelligence can be used to discover processes, analyze them, design a process for automation, create the bot that automates the process, and then monitor its functionality to continually optimize the process. Intelligent bots can use other AI technologies such as Optical Characters Recognition (OCR), or Natural Language Processing (NLP) to transform the way that businesses store, analyze, and apply their unstructured data. Typically, when forming a strategy for adopting hyperautomation, businesses will use a combination of Robotic Process Automation and iBPMS to automate complete sets of tasks or processes.
These processes are typically augmented through the integration of AI and Machine Learning. All of these bots are designed to complete tasks quickly, without error, and they have the adaptability to continually optimize based on the data that they collect as they work. Advanced insight through deeper analytics is another key benefit that hyperautomation provides. The AI element allows bots to self-monitor and measure their outputs to see what is working and what can be improved.
They are also able to provide deeper analytical insight into how the business is functioning as a whole. There are automation tools that have been creating detailed reports that are already readable so that data does not need to be filtered through to create meaningful reports. This allows leaders in a business to take immediate action on the data presented to them, allowing the business to continue to grow, achieve its goals, and innovate the way it operates. Hyperautomation can take that a step further and take a lot more information into account so that business outcomes are easier to forecast, and the decision-making process can be simplified through recommendations based on up-to-the-minute metrics.
The Benefits of Hyperautomation
Automation was created to help relieve some of the burdens that used to lay completely on the human workforce. Historically, automation has been shown to provide a laundry list of benefits to businesses across all industries. As you can imagine, hyperautomation can take all of that to the next level. One of the benefits that we’ve already touched on is that hyperautomation is predicted to drastically reduce costs for businesses that adapt to this trend.
Because of the advanced tools that are used in hyperautomation, businesses will be able to make better decisions, workflows and entire processes can be streamlined for maximum efficiency, and ROI will be easier to track than ever before. Another source of cost reduction is the seamless integration of multiple systems and tools. Instead of reaping the benefits of individual technologies and tools, they can all work closely together and provide the digital agility that is becoming increasingly necessary in the tech-driven world of business. In addition, fewer resources will need to be dedicated to IT services because hyperautomation tools are designed for effortless integration and interoperability.
Employees will also be able to automate processes within their individual roles, alleviating the need for IT intervention at that level as well. This allows the workforce to be more educated with the entire process and they will be able to easily take advantage of the hyperautomation tools available to them so that they can do their most important work instead of getting caught up in lower-level tasks. Hyperautomation helps to create a deeply integrated network of tools that can streamline business processes and reduce the need for human intervention, allowing the workforce to do their most impactful work. It provides greater opportunities for collaboration, more detailed insights, and enhances the decision-making process. It helps to create an environment that is data-driven, efficient, and constantly innovating to propel a business towards its goals. In short, hyperautomation provides businesses everything they need to engage their team, effectively use their resources, and actively create value on a consistent basis.