The solution aim was to replicate the existing RFQ quote creation process outcomes via an efficient automation. Our solution achieved this via a sophisticated design including machine learning.
Our customer was a parts manufacturer in Queensland who had a very standard Request For Quote (RFQ) quote creation process. Like all manufacturers, this process was heavily standardised and infrequent.
The solution had to create a quote based on a received RFQ, with specific data accurately extracted and checked, before being entered into their ERP system. With this in mind, this process was a good candidate for automation, as it was a very standard business process that could be easily automated and would give staff back valuable time to focus on more important tasks.
After consulting with the business, we designed an automated process whereby RFQ forms could be retrieved, extracted, validated and entered into SAP entirely independently. A sophisticated machine learning model was trained to accurately interpret RFQ forms and produce usable data to cross-reference within the ERP. To maximise efficiency, the process was built entirely using SAP API integrations, meaning we avoided issues related to system instability in SAP. Using UiPath, we were able to quickly and reliably incorporate the above components into a single, seamless solution.
The solution aim was to replicate the existing RFQ quote creation process outcomes via an efficient automation. Our solution achieved this via a sophisticated design including machine learning components and API integrations that mimicked existing process logic.
By automating this process, the business was able to automate their RFQ quote creation process without disrupting existing business systems, or risking process integrity. Quotes were created in 3 minutes (down from 10 minutes manually) and without any human errors. This resulted in more efficient and accurate outputs, which was beneficial for risk purposes, but also freed up staff to focus on more valuable tasks.
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