IPA, Intelligent Process Automation (hyper automation), means complementing Robotic Process Automation with the technologies best suiting for the situation, such as Machine Learning, Artificial Intelligence, Information Extraction, or an interface that supports automation. When evaluating the benefits of Robotic Process Automation and Intelligent Process Automation, the focus should not only be in speeding up the work, reducing manual tasks and eliminating errors in end results.
Automations support the business also in the longer term by scaling effortlessly as the workload increases. Automations can be triggered or scheduled at desired times. Automations also provide valuable analytics for the business, which can be easily converted to the desired format and be delivered to the clients in almost real time. The need of analytics should be taken into account in the implementation of automation to ensure the access to the needed data.
Defining and implementing automation should not be a mechanization of the current process. Through the collaboration of the client and the Business Analyst, the whole process can be made smarter, more secure and more efficient. It is important to start with an analysis to identify and prioritize business needs to build a new, automation-supported process based on them to bring reliability and efficiency. Tools for analyzing processes of individual tasks (such as Process Mining or Task Capture) can be used to support the analysis. Automation implementers should also be involved at this stage.
The automated and streamlined process often differs from the current process and the interaction of the automation with the user can be implemented in several different ways with the help of assistive and background robots. The process carried out jointly by a human and a robot, in which the robot acts as an assistant and a fast information seeker, for example, must be carried out with error tolerance and logic in mind. The technical intelligence of automation plays an important role. The preconditions for the rational use of Machine Learning or Artificial Intelligence, for example, must be borne in mind.
The robot can support the user by performing the following functions, among others:
• entering data collected from multiple sources into the system or systems
• validating the data entered by the user and giving feedback or only correcting the data
• conducting a summary of data, for example to support preparations of a customer meeting, based on user-defined or entered data and data gathering from different systems.
To maximize the benefits of automation, important implementation considerations:
• prioritizing of the robot’s tasks in time-critical processes
• phasing of process automation from a technical and operational point of view
• handling exception and error situations of a process from a users’ point of view
• using the triggers of the bot from the point of view of a person working in the process
• using process-generated information while supporting other processes.
In addition to technical capabilities, the implementation of the best automations always requires seamless cooperation and expertise of the client, the analyst, the developers and the testers, as well as the vision of how to achieve the best possible result.