RPA cannot be used on data that is non-electronic and is unstructured, as for example- a paper correspondence. It can be used in combination with other technologies like scanning and OCR after we convert the non-digital data into digital data to extract information from it.
RPA is best used on mature processes. If processes are not mature it is better to standardize the process using other methodologies like Six Sigma and Lean. RPA can neither fix a broken process nor be implemented on a broken process as well.
It can log on to applications and systems, move files and folders, extract, copy and insert data. It can also fill forms and provide routine analyses and reports. With the power to combine with hundreds of open APIs to extract data, it can also have integration features that will allow it the flexibility to easily work with any third-party applications.
Intelligent RPA when combined with AI and ML can perform complex tasks like interpreting text, understand unstructured data, code chats and make complex decisions as well.
Many Enterprise RPA tools also feature a core capability like a control panel/dashboard functionality which helps in work allocation & monitoring. These control panels are used for multiple processes and multiple bot orchestration & application sign-ins, thereby providing control over the process. Many however, have exceptions handling flow for which human intervention is needed.
RPA dashboards show real-time data and analytics to businesses so that they can monitor resource usage, process completion time, and transaction success rates. ly three to six months. High on efficiency they ensure: