Nevertheless, the actual innovation is the exponential increase in processing capacity and the decline of costs involved, which have enabled a quick implementation of robotic process automation (RPA) technology and at very reasonable price. In fact, RPA has become one of the most common cases of artificial intelligence (AI) used in companies recently, making the global market for RPA software grow 63% in 2018, according to Gartner. It became the fastest growing segment of the global corporate software market, although the investment is still quite modest compared to other categories of business software.
On other words RPA refers to the use of software robots to reduce the user’s intervention on the computer solutions, mainly in repeated tasks with little variation. The goal is to assure productivity and quality in companies digitalization context. RPA implementations allow a faster information process and connect computer systems to each other automatically – to transfer data between different applications, send email, update databases, and generate documents. In other words, process automation technology speeds up different tasks related to computer applications previously produced by bottlenecks. It eliminates or decreases workloads in different back office processes – customer service, purchasing, IT, human resources, accounting, finance, etc. – adding productivity to the workforce.
The RPA concept invites us to take the idea we have on robots to a new dimension, only referring to purely computational models – that is, robots that are not physical, but software. With these process automation implementations, you can solve specific performance problems. Furthermore, they are solutions that are quickly implemented, usually generated from external interfaces and do not require major changes in existing business systems. And the return on investment usually occurs within the first year.
Robotic process automation
This kind of implementation applies to structured processes while software must incorporate rules and workflows established by expert users, where human input is still needed since automation software is geared towards automating business and administrative processes based on very specific rules.
In this context, RPA software robots are capable of executing complete processes without requiring almost any intervention from a person, and can be adapted to all types of internal processes. As they have the ability to interact with multiple applications and platforms, their value is further enhanced in complex computing environments.
From automating specific and simple transactional tasks, to similar processes that go through several functions of a company – and even complete processes – software automation technology can release workers from multiple bulky and demanding tasks which do not add value, allowing them to focus on more attractive activities. In other words, with process automation technology you can automate individual tasks and complete entire processes, or just focus on parts of them. However, to get their full contribution, implementations should be considered as evolutionary processes.
Each industry will find different processes where it is appropriate to apply robotic process automation. There are more than 70% of organizations using or piloting RPA. In banks where this technology is already mainstream, it is applied to simplify the processing of different operations and transactions.
The manufacturing sector for example, use this technology for quality control. It is important to analyze what processes would be the most appropriate to automate, and in these cases cyclical activities are always the best candidates.
It does not necessarily have to be back office processes: today, for example, there are bots which work out the first level of customer service (helping making common questions or requirements in the self-service portals, for instance).
Among the advantages of RPA software, it should be noted that it helps to reduce costs, optimize times and allow the workforce to be directed towards improving the customer experience and the quality of service, which are ultimately the central focus of companies at this economy data era. It also reduces operational risk due to possible human errors and ultimately adds competitiveness, in a harsh business scenario where each differential makes the difference.