How smart can process automation be?
Imagine being able to track your business processes from anywhere in the world. In real time. You observe which activities the machines or systems involved in the process are carrying out at any given moment. As soon as risks or optimization potentials are identified, you are notified immediately. The system provides you with the optimal solution proposals – based on machine learning. You confirm the recommended measures and the system executes them. With just one click you create immediate efficiency increases.
Sounds too good to be true?
This scenario is possible when combining two advanced technologies: Robotic Process Automation (RPA) and Process Mining. A future scenario that is already being used today.
RPA – The first step towards automation
Successful implementation of Robotic Process Automation usually means higher productivity and less resource consumption for companies. Repetitive tasks are automated by software robots and thus minimize manual effort. Software robots are applications that imitate the human operation of programs.
However, simple RPA systems are limited to standard processes. Before implementation, the robot needs the exact sequence of activities, often in the form of flowcharts. As soon as a process is more complex and the activities to be performed depend on different influencing variables, simple RPA systems reach their limits.
When Process Automation gets smart – Intelligent Robotic Process Automation
In such cases, artificial intelligence is required so that the robot can reproduce user behavior error-free. These AI-based programs are also known as cognitive RPA systems. If the system also has learning capabilities, we speak of an intelligent RPA system. Intelligent RPA systems are based on cognitive computing, in which AI technologies are used to simulate human cognition. The software robots use machine learning to learn from historical data and live data by understanding the behavior patterns of employees. During the learning process, the robots interpret employee activities and proactively ask employees for decisions on task completion. With sufficient understanding, the robots are then able to perform the tasks autonomously and make independent decisions in new situations. With the various RPA systems, business processes can be fully automated: from the unstructured activities of so-called engagement tools such as e-mail, multifunctional products or smartphones to the structured activities of recording systems such as ERP, ECM or CRM.
With RPA programs, employees can focus on core areas of their work. According to the ISG Automation Index, companies with RPA systems can implement their business processes five to ten times as quickly with an average reduction in resource requirements of 37 percent. However, the resulting productivity gains do not result in job cuts but enable employees to concentrate on higher-value tasks while at the same time achieving a higher volume of work.
Implementing RPA correctly – with LANA Process Mining
With AI technologies, process automation can be implemented more progressively along the entire value chain. Companies benefit enormously from productivity increases and new resource capacities. At the same time, however, they need to manage and control more IT systems. This is where LANA Process Mining comes into play: LANA enables cross-system process transparency based on real process data. LANA is thus suitable as a controlling tool for the entire business process and becomes a success-critical enabler for process automation.
How RPA systems are implemented and continuously monitored with LANA is explained in our next article. Because as it turns out: With LANA, the described future scenario can actually be realized today.