Goods Received Bot Case Study for Office Depot

CampTek Software’s case study showcases the UiPath Robot built to improve the process of matching Office Depot invoice and purchase order line items. Robotic Process Automation (RPA) will significantly impact the supply chain in terms of productivity, efficiency and accuracy within the business processes industry. By automating the majority of the tasks in the supply chain, organizations can now eliminate the possibility of errors and make their operations lean, efficient and smart. A study by Information Services Group highlighted that by automating tasks with RPA it’s not replacing people’s jobs. Instead it’s freeing their employees from redundant, mundane tasks and allowing them to focus on higher-value activities.

Challenges: Invoice processing & goods procurement with Basware

CampTek Software recently worked with a Basware client that was manually processing their invoices. Due to a lack of integration between the system that produces the invoice and the Basware system, where it’s ultimately stored, the process was tedious and frequently invoices were processed with errors. Invoice processing is crucial to their operation and it’s very problematic when the invoice data is captured inaccurately and inefficiently.

As part of their supply chain process, a Full Time Employee (FTE) had to manually pull purchase orders from Basware and then log into another disparate Office Depot system to search the order delivery status and then return updates back into Basware. The manual process had the FTE processing 439 invoices over a 13 week period with 4.5 minutes/invoice. This is time consuming as well as an error prone matching process.

RPA Solution: 

CampTek Software worked with the Basware client to analyze and develop RPA workflows. These address the company’s process inefficiencies and pain points. We’ve built the RPA prodution solution on the UiPath platform. The bot’s able to process the goods procurement workflow in 25 seconds versus the 5 minutes it took an FTE. The robot ultimately saved an average of 4 hours/ week or a total time of 52 hours/ 13 weeks. Moreover it reduced the amount of errors below 3%.  It also afforded the FTEs more time to focus on higher-value activities.