Saving Time & Money
MIL analysts on the Systems Coordination and Implementation (SCI) team were asked to analyze the emerging technology of robotic process automation (RPA) and determine if it could benefit the Bureau of the Comptrol-ler and Global Financial Services (CGFS) at the Department of State (DoS). Working with each office, MIL reviewed current processes in hopes of identifying optimal scenarios for future RPA projects. These reviews assessed RPA-related attributes including data inputs, decision points, business and processing rules, technical constraints, outputs, and many others. This effort identified over 30 scenarios that were deemed apt for RPA automation.
From these scenarios, MIL selected the statement of difference (SOD) reconciliation process conducted by disbursing for the proof-of-concept project. This selection was based on a few key factors. First, the SOD process relied on PDFs for data input. With no existing PDF scraping technology available to CGFS, users were forced to visually match values from PDF to PDF that ultimately increased the chance for human error. Second, the process as a whole was one that staff deemed undesirable to undertake. MIL knew that fixing this process would be an easy win for CGFS and create the buy-in needed for future RPA initiatives.
To automate this process, MIL developed a robot using UiPath that reads, selects, and filters unstructured data from several PDF reports. This data is stored into memory in a dictionary collection of key-value pairs for rapid record entry and retrieval. The robot then automatically calculates the totals before comparing the Treasury Central Accounting Reporting System (CARS) lines against RFMS/D (DoS’ Disbursing System) data and places the reconciliation results in a preformatted SOD Excel spreadsheet. In addition, the robot is capable of identifying specific values from the reports including header totals that are used to populate the final report.
The resulting bot was able to convert the legacy process estimated to take a week each month for one person to complete, into a fully automated bot that can now produce the final SOD report in less than 30 seconds. Total savings for this bot are estimated at 400 -500 hours annually. The bot also improved accuracy of the reconciliations, identifying historical differences that were missed by the manual reconciliations.
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