Real-life look at SAP intelligent RPA uses, benefits, limitations

Top Three Advantages And Limitations Of SAP RPA that you need to be aware of

SAP rebranded the Contextor technology as SAP intelligent RPA, which is focused on improving automation of SAP-native processes. SAP intelligent RPA, sometimes referred to as iRPA, is meant to provide better integration into the SAP application stack than other platforms and easier implementation when companies have adopted SAP-prescribed best practices for enterprise processes such as procure-to-pay or quote-to-cash. Organizations can also use intelligent RPA technology as a complement to other RPA platforms that may provide better automation across non-SAP software applications.

Automating quickly

Intelligent RPA provides deep integration into the organization’s existing SAP backbone, said Chengbo Yu, CIO for the Asia-Pacific region of Rehau. The platform is transparent to business users who are already familiar with SAP. As a result, developing and testing new automations takes less work and requires less of IT’s involvement. RPA projects can move into production in under two weeks, which enables Yu’s team to adopt an agile, iterative approach in improving both the automations and the processes they automate.

Automating best practices

SAP’s current strategy lies in positioning intelligent RPA as a complement to other RPA products and the company is actively partnering with RPA leaders such as UiPath, said Oliver Betz, senior vice president and global head of product management for S/4HANA at SAP. The real strength is pre-building an RPA component into S/4HANA applications, he said. This can help automate the process of creating RPA automations — that is, bots — with less work. SAP launched a program in 2018 to support 10 pre-built automations and now offers about 100.

Embedding intelligence

Embedding intelligence into workflows enables them to get better over time, Betz said. SAP has already developed modules for procurement, sales, service and inventory management that can spot and automatically fix inconsistencies in data using historical data stored across systems. For example, a company name might be corrected to “Johnson & Johnson” from “Johnson and Johnson” to ensure consistency when a user realized that all previous purchases were bought from the first designation. The module can make corrections where a high level of confidence exists, or it can make an update and flag this for a double-check by a human.


“Transaction-based licensing requires internal governance and controls to avoid unexpected and unplanned costs,” he said. “On the other hand, it allows a small-budget entry into the world of digital workforce.”

Another limitation is that it only works via the cloud. Only being able to access the tools via a browser could limit the potential usage, Bartheidel said. This could be a bigger problem for areas with slow or even no internet connection.

Another concern is the pace and availability of trainings.

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