“ RPA is a fundamental movement, which makes it possible to initiate the digital transformation of companies via short projects with rapid ROI.” This is the analysis on which IT specialists (Gartner, Forrester and HfS) as well as large consulting firms (Capgemini, Deloitte, EY, McKinsey) agree.
The objective of RPA (robotic process automation) is to reduce the time spent by users on boring tasks (re-entry/copy-paste, comparison/verification of information between 2 applications), by assigning them simply to robots in an automated manner.
15 to 30% is the average time saved by the user thanks to RPA, allowing them to devote themselves to tasks with greater added value, both for the company and for their personal development.
In this case, the robot is an assistant to the user while respecting business logic.
The robot carries out the tasks for the user (read the content of an application window, locate the fields containing useful data, copy them to another window, launch a transaction) then interrupts its process to ask the user to make a decision that can only be made with experience.
Once the option is chosen by the user, the automatic process resumes. An RDA project is very quick to implement because the automation takes place at the workstation level and not on application data; the return on investment is quite short (only a few months for a solution which provides affected users with a gain of around 20%) and beneficial in the long term.
In this case, the robot intervenes directly at the server level, without human interaction.
It automatically performs all tasks (extract files, check data, create new data, convert them according to the requirements of each information system application, etc.). It is important that these tasks are controlled by another robot to check that they are running smoothly and alert a user in the event of a problem;
the latter can then take control again to understand the cause and restart the process after resolution. RPA projects are longer than RDA projects because they act on application data, which requires preparation work, programming and extensive testing phases before going into production.
