Robotic Process Automation (RPA) is no longer a new technology – the first developments can already be seen in the early 2000s. Essentially, RPA evolved from screen scraping, artificial intelligence (AI) and workflow automation. With the help of software robots that automate numerous back and front office activities, RPA now supports many companies in dealing with repetitive tasks and processes.
But as the provocative thesis of HfS analyst Phil Fersht – RPA is dead – shows: RPA is no longer sufficient in many cases. The robots are able to take on shorter, repetitive tasks – which usually last a few minutes. For example, with B2B companies that have to continuously monitor and check multiple portals of suppliers in order to buy at the best possible conditions. For the automation of a complex process – such as handling a customer complaint – RPA is the wrong choice. In addition, companies usually limit the use of RPA to a few business processes. For more customer-oriented work, however, it is necessary to fully automate workflows throughout the company.
A new term has recently caused a stir in the world of automation – at least since Gartner named it one of the ten most important technology trends for 2020. The analyst firm defines hyper-automation as “the application of advanced technologies, including AI and machine learning (ML), to increasingly automate processes and support people.” Hyperautomation not only extends to tools that enable automation, but also refers to the entire process of automation (needs assessment, measurement, automation, monitoring, evaluation, decision-making). Many companies are under great pressure to be innovative in order to optimize their processes and customer contacts. Hyperautomation is therefore a valuable approach for many organizations – because it brings speed and agility and thus does what RPA cannot achieve on its own.
- Gero Decker, CEO of Signavio GmbH
“More and more companies are investing in Robotic Process Automation. But where does the use of software robots actually make sense? Where should a process first be improved before it is automated? How can RPA initiatives be planned, evaluated and controlled? Scalable RPA initiative is based on well-founded documentation, analysis and optimization of processes. This is the only way to gain confidence in action and achieve long-term success. “
- Roman Schäfer, partner at Blue Reply
“We are convinced that the use of process analysis, RPA and the implementation in innovative platforms make companies competitive in the long term. The aim is to enable companies to digitally transform their business model.”
- Walter Obermeier, Managing Director of UiPath GmbH
“What can I do quickly and agilely today to be fit for tomorrow? There is no better tool than Robotic Process Automation when it comes to getting the most out of just a few human resources. Of course, I will also have to use my old legacy Systems wait, but react quickly to changes and to be able to meet business requests quickly is the best way to do it with RPA. All of a sudden, IT and business can make friends again and act agile and successfully together. “
But how can hyperautomation support companies? To do this, it is important to understand that for a successful hyper-automation project, the right combination of the right technologies must be implemented in the right order at the right time. These include:
Process mining: Many companies know that automation is important in order to work more efficiently and, for example, improve customer satisfaction. But many do not know where exactly to start. With the help of process mining, patterns and tasks can be analyzed and automation potential discovered. Organizations can also consider future challenges – for example when it comes to complying with new or changed regulatory requirements.
Workflow orchestration: This function ensures that numerous processes can be mapped, optimized and executed in central digital workflows – taking into account employees and existing applications. Because companies use it to orchestrate several people, actions, software robots, guidelines and systems in a uniform manner, they can analyze, measure and optimize their business activities much better.
Robotic Process Automation (RPA): RPA has become significantly smarter and even automates complex, lengthy processes thanks to AI and ML functions. With RPA, companies can reliably and efficiently automate repetitive, manual tasks across the company. RPA can be executed directly via web interfaces or business applications. Intelligent automation functions such as cognitive capture, process orchestration and analysis enable employees to focus on their core competencies instead of laboriously copying data manually or retrieving it from portals.
Artificial intelligence (AI) and machine learning (ML): Using these technologies, data such as speech, text, chat or images can be understood, classified and extracted. Thanks to AI, companies can automatically recognize people, places, amounts and other relevant data points in documents and thus understand the content and context of the communication in order to use them to make business decisions, for example. NLP (Natural Language Processing), entity extraction and sentiment analysis automatically provide the most important information and also offer a better insight into customer communication across all channels. With ML, organizations can improve the accuracy of their automated document identification, classification, and segregation that RPA performs using Cognitive Capture.
intelligent Business Process Management Suite (iBPMS): Anyone who uses automation technology also wants to check what advantages it brings for the company. The analysis functions contained in iBPMS ensure that you can see exactly what effects automation has – for example, the return on investment (ROI) can also be calculated. The improved transparency, more process intelligence and detailed insights into all workflows that involve customers, employees and business partners give managers tools and information with which they can react promptly to changing market conditions and customer expectations.
The positive effects of hyper-automation can be felt throughout the company. For example, the costs are significantly lower because the automation reduces the time and resources required for manual tasks and the number of errors. Gartner predicts that companies can reduce their operating costs by 30 percent by 2024 if they combine hyper-automation with redesigned workflows. In addition, processes become scalable through hyper-automation, as this transforms a manual, complex task into a reliable, repeatable process. A collaborative ecosystem made up of technology and people working together leads to better business results.
As a further advantage, organizations
can react much faster to customer questions and needs through process automation – and thus create a personalized customer experience. This not only increases customer satisfaction, but the positive experience at best leads to higher loyalty and more income.
Hyperautomation also creates an efficient workforce (consisting of human and digital colleagues) so that flexibility and agility find their way into the organization. If people can concentrate on value-adding activities, the company creates an important competitive advantage. Ultimately, this also benefits the employees, who appreciate this work more – in contrast to the stupid copying of data from A to C via B. Instead, they concentrate on activities and projects that offer the company real added value and can do so for example contribute to optimizing the customer experience. This leads to happier employees, as they now see added value in their work. (mb)