Robotic process automation – or RPA in short – involves the production of automation with the help of software. Robotic process automation differs from artificial intelligence in the sense that software robots must always be provided with instructions, because they themselves are not intelligent — at least, not yet.
Robotic process automation is ideal for, for example, entering purchase invoices in an ERP system or the establishment of a new customer account in a number of systems simultaneously, and the routines related to the hiring of a new employee and the start of employment relationships. The common denominator in all of these cases is the creation of various user IDs and the importation of the same data into more than one system, meaning that automation reduces mistakes and may generate a lot of savings in terms of work that has formerly been carried out manually.
The creation of automation requires a human to switch on the robot assistant when first taking it into use and provide it with instructions. The rest is taken care of by the robot, autonomously. This ensures that all of the necessary user IDs and access rights are generated at the same time without errors and that the quality remains good as the number of mistakes declines.
What distinguishes RPA from traditional IT automation is RPA software’s ability to be aware and adapt to changing circumstances, exceptions and new situations. Once RPA software has been trained to to capture and interpret the actions of specific processes in existing software applications, it can then manipulate data, trigger responses, initiate new actions and communicate with other systems autonomously. Large and small companies will be able to reap the benefits of RPA by expediting back-office and middle-office tasks in a wide range of industries, including insurance, finance, procurement, supply chain management (SCM), accounting, customer relationship management (CRM) and human resource management (HRM).
Below is an example of how Robotic Process Automation works in an Order Management Process.
When a job gets monotonous people lose interest but not robots!, then why do humans have to do those monotonous, low value adding, repetitive jobs?
Humans can do much better interesting jobs!
When something is delivered without interest, chance more for errors. In case of robots there is no such complications as robots doesn’t have interests unlike humans.
Industrial experts substantiate the automation for below reasons:
1. To avoid human errors and to reduce human efforts.
2. To saves time and improve productivity, accuracy and consistency.
3. Enhance the business analytics and easy standardization of workflow.
4. To have a frictionless delivery of tasks.
5. Complete Audit trail for any kind of compliance purposes.
6. Cost reduction.
Blue Prism’s Robotic Automation
The term Robotic Process Automation was invented by Blue Prism, that itself proves they are the pioneers in Robotic Process Automation software development. Blue Prism has been recognized by the American IT research and advisory company Gartner, Inc.
Robotic Automation refers to process automations where computer software drives existing enterprise application software in the same way that a user does. This means that unlike traditional application software, Robotic Automation is a tool or platform that operates and orchestrates other application software through the existing application’s user interface and in this sense is not “integrated”.
Blue Prism’s Robotic Automation software enables business operations to be agile and cost-effective through rapid automation of manual, rules-based, back office administrative processes, reducing cost and improving accuracy by creating a “virtual workforce”.
The virtual workforce is built by the operational teams or accredited Blue Prism partners using our robotic automation technology to rapidly build and deploy automations through leveraging the presentation layer of existing enterprise applications. The automations are configured and managed within an IT-governed framework and operating model which has been iteratively developed through numerous large scale and complex deployments.