on 09-10-23 11:26 AM - edited on 04-07-24 09:28 AM by Michael_S
The responsible area performed manual entry of purchasing data on a daily basis, meaning the process was done manually or was subject to filling errors, which could lead to discrepancies between the invoices received. Additionally, manual processing was time-consuming, causing delays.
Step 1: Discovery
We first focused on understanding the scope of the process and whether automation was viable. After that, we defined the scope of the process, as there could be different categories of payments, inputs and different ways of making payments, it was essential to refine the process.
Step 2: Design
The solution used Blue Prism and DIAPI (SAP Data Interface API) to process cases, carrying out all analysis, processing and sending in the background without the need for interface navigation, generating a much higher processing speed and generating greater security.
Step 3: Build
We automated the process and sub-processes using API and manipulation of SAP information. After analyzing the order, it was registered in the system and payment was processed. A detailed report was generated and forwarded to the finance team at the end of the process, maintaining traceability.
Step 4: QA
Unit tests were carried out during development, ensuring that the activities were occurring successfully, integrated testing and internal approval and with the client, in order to guarantee a higher quality of the project, in addition to being able to refine functionalities throughout the process.
Step 5: Delivery & ongoing management
We carried out the deployment smoothly, a robotic account was used for production, after the go-live sprints were carried out to monitor and monitor indicators, in order to evaluate delivery and improvements on a cyclical basis.
We needed to assure the finance team involved in the work saw that RPA would generate positive gains, enabling them to focus on other tasks that require greater creativity. We also needed to forecast business benefits using existing data.
We had a very positive impact. In addition to the area having traceability of all scenarios and processing, it also freed people up for other tasks, reduced the recurrence of errors and the process became safer and faster.
The importance of designing the solution can't be understated. In the project scenario we had at least 3 different ways that this process could have been automated. However, when evaluating the scenarios we found a gain of almost 200% more speed using the correct integration.
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Leonardo Soares
RPA Developer Tech Leader
Bridge Consulting
América/Brazil
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One question from me on this one @LeonardoSQueiroz - you mentioned that you avoided interface automation by using SAP's data interface API. How easy was that to set up? Were there any additional API costs involved?
Firstly, congratulations! I found your project very interesting.
Given this context, I would like to know how you addressed the issue of ensuring that the finance team involved perceived that RPA automation would generate positive gains. What was presented to them?