In December of 2020 we had a Hackathon with SAP partners that was focused on using SAP Intelligent RPA with SAP Ariba. You can view the summary of that Hackathon in this blogpost from the Co-Innovation Lab. This Hackathon challenged partners to design and develop a use case for automation with Ariba. I have been writing a series of spotlights for the use cases presented in that Hackathon, you can find links to the other blogposts at the bottom of this post.
In our fifth post we will spotlight the use case from Infosys. The team developed a bot that will help with content localization. Translating sourcing content can be very time consuming and frequently will be done by copying and pasting text from one text field to another. When it is done manually this is a very repetitive task that can be prone to errors, so it is an excellent candidate for RPA.
For the bot to translate the different fields from Ariba sourcing events, there will be 3 bots. One bot will orchestrate the process by launching the other 2 bots as necessary. The two bots that would be called on demand by the orchestrator would be a UI automation bot that is developed to work in Ariba, and a API based translation bot that will use an external translation engine to translate their input to another language. In the slide below you can see the organizational structure of these 3 bots:
This project allows a company to expand its sourcing to the global market, and with Ariba that means they can have access to over 4 million different suppliers. To do this translation the team was able to leverage an existing project they had created that can take an input and translate it to another language. This was a great way to accelerate development for a Hackathon where the team had limited time to complete their project.
For the team to integrate their existing code they created a file that when executed would run their python code to do the translation with the input it is given. To achieve this in Intelligent RPA the team captured the .bat file like an application and used the start application activity to launch their python code. If this project was deployed, the modular format of Intelligent RPA workflows would allow them to later revise that section of the project and use the API activities from Intelligent RPA to remove the section of python and streamline the workflow to be entirely in Intelligent RPA.
In the new Cloud Studio, sharing and reusing sections of another project has become even easier. You can now load a workflow from another project as a dependency for a new project. One example where this could be useful would be leveraging a login workflow from another process in order to accelerate developing additional bots. To learn more about the ways you can reuse workflows in the cloud studio check out this page on the help guide.
Infosys estimates that a company with 500 sourcing events that need to be translated into 3 languages could save $50,000 a year by implementing automation like this. This process is one that can be difficult to verify by the FTE due to the different languages, by automating this process a company can save money and reduce the risk of errors made when translating manually.
Have a great day and happy bot building!
This is the fifth use case spotlight in the series, you can check out the first four posts in the links below:
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