Part of the “Intelligent RPA” series about the evolution of robotic process automation and its potential impact on digital transformation.
RPA is the acronym for the Rugby Players Association in England, but also for robotic process automation – and that is presumably the reason you have heard a lot about it during the last year.
Indeed, IT analysts such as Gartner, Forrester, IDC, HFS Research, Everest Group, and Aragon Research; major consulting firms such as Accenture, Deloitte, EY, and McKinsey; and IT integrators such as Avanade, Capgemini, DXC Technology, HP, IBM, SopraSteria, and many others agree: RPA is a pragmatic approach for organizations to engage or foster digital transformation.
That’s why this topic deserves a closer look to clearly understand it.
Defining robotic process automation
In large organizations, people spend a lot of time interacting with the different applications in their business systems. To carry out their mission, they frequently have to re-enter or copy and paste data from one application to another or compare and verify information from two applications. Robotic process automation uses “software robots” to automate – as much as possible – tedious, mundane tasks like these.
This “automation of white-collar jobs” can free up 15% to 30% of an employee’s time, which can be used more effectively for actions bringing real value to the organization and improving the quality of customer service.
As a corollary, this automation improves employees’ comfort, and this is not the least of its advantages. The employee who spends the workday in front of computer tools will adhere better to the strategic vision of management who want to accelerate the company’s digital transformation.
Attended RPA, software assistants, or robotic desktop automation
An enterprise’s business processes involve many components in the information system. These range from database servers where data is stored, to employees’ desktops that provide access (via various applications and software solutions) to large transactional systems, client-server applications, intranet/extranet, cloud applications, CRM, ERP, ECM, and so on.
Automation can happen on the desktop, where a “software robot” executes interactions just like a human being. The robots read an application window’s contents, identify the fields containing useful data, copy them into another window, launch a transaction, and so on. While performing these tasks, the robot may, if needed, “hand over” to the person in front of the PC to make a decision based on his or her intelligence and experience. The robot can also carry out some checks on the data it handles. This gives the company additional guarantees regarding compliance with regulatory requirements and the quality of processes’ results.
This aspect of RPA, where the robot acts a software assistant for a human being and interacts with a PC while respecting the business logic, is called attended RPA or sometimes robotic desktop automation (RDA).
Its deployment is very fast, and it has no impact on the information system. It does not require modifications on applications, which continue to function without any change. As a result, RDA projects are short and their ROI is fast. It takes only a few weeks to set up an RPA robot that can save 20% of the time of tens or even hundreds of employees. And considering that the desktop will not be simplified by magic in the short term, attended RPA solutions will benefit the company for many years.
Unattended RPA or autonomous software robots
Some processes can be automated from end to end by robots installed in server farms and running without any interaction from a human being. A software robot can autonomously connect to databases to retrieve information, apply business rules, perform processes that produce new data, and inject them into other applications using their own programming interfaces (APIs). This aspect of RPA, where the robot works at the heart of the information system or in the cloud, is called unattended RPA.
However, this autonomous robot remains under the supervision of human beings. It is necessary for people to monitor the processes to ensure they are executed properly. In case of an anomaly, a human expert, a “robot supervisor,” will be able to understand the cause of the problem, correct it, and restart the robots so the processes resume where they had stopped.
Because they are installed on servers (and therefore inside the information system), unattended RPA robots require some infrastructure. And because they act directly on application data, they need to use APIs, which requires programming work. As a result, unattended RPA projects are likely to be more complex, and therefore take a little longer, especially when it comes to going live.
Clearly, organizations should consider RPA globally, taking advantage of complementary approaches. It can start on the desktops with attended RPA, focusing first on the most repetitive and time-consuming processes. These initial benefits are quick and help employees embrace the organization’s digital transformation. Then the RPA journey can be extended by implementing unattended RPA on servers to handle complex processes.
Some business processes can even benefit from a hybrid RPA approach, mixing attended and unattended robots to maximize the benefits.
RPA fosters digital transformation, and its main benefits include:
- Reduced risk thanks to better compliance
- Improved comfort at work for employees through contextual guidance
- Increased operational excellence with business process efficiency
- Reduced time to market for new offers thanks to greater agility
Artificial intelligence + RPA = Intelligent RPA?
We’ll see RPA evolve further with AI technologies. But how will RPA and AI work together? What will be the best use cases for intelligent RPA, and what are the major benefits it will provide? We will explore those questions in the next post in this series.
For more information, visit our SAP Intelligent Robotic Process Automation web page.
And please listen to the replay of our “Pathways to the Intelligent Enterprise” Webinar, featuring Phil Carter, chief analyst at IDC, and SAP’s Dan Kearnan and Ginger Gatling.
This article originally appeared on the SAP Analytics blog and is republished by permission.