RPA Bot Performance Tracking with Real-Time Cost Comparison
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Solution Overview
Problem
Existing robotic process automation (RPA) systems face challenges in accurately and consistently tracking bot performance, making it difficult to quantify benefits such as cost reduction and time savings.
Innovation Solution
A computing platform that receives a work queue of items, assigns value metrics based on metadata, calculates RPA costs, compares them to alternative processing costs, and dynamically generates performance metrics for RPA bots, allowing real-time evaluation and optimization of bot performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If bot performance is captured manually through spreadsheets, then implementation simplicity is maintained, but measurement precision and reliability of performance tracking deteriorate
Solution Approach 1:
The patent replaces manual spreadsheet-based performance tracking with an automated computing platform that programmatically collects, processes, and analyzes bot performance data. This substitution eliminates manual errors and inconsistencies while maintaining ease of implementation through software automation rather than complex manual procedures.
2Productivity
If real-time performance tracking is implemented, then productivity and decision-making speed improve, but device complexity and implementation cost increase
Solution Approach 1:
The computing platform performs multiple functions including data collection, metadata processing, value metric assignment, cost identification, performance metric determination, and real-time reporting within a single integrated system. This multi-functionality reduces the need for separate specialized systems while delivering comprehensive real-time performance tracking capabilities.
3Measurement precision
If comprehensive performance metrics are calculated, then measurement precision and decision quality improve, but loss of time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-defining value metrics for different work queue items and establishing cost models before performance evaluation begins. This pre-processing allows the system to quickly calculate comprehensive performance metrics during runtime without extensive real-time computation, reducing processing time while maintaining measurement precision.
Data Source
AI summary
Aspects of the disclosure relate to intelligent bot performance tracking and analysis. A computing platform may receive a work queue of items to be processed using a bot. The computing platform may receive, in real-time with processing of the work queue using the bot, metadata associated with the work queue. Based on the metadata, the computing platform may assign, in real-time, a value metric associated with completion of each item in the work queue. Based on the assigned value metric, the computing platform may identify a robotic process automation cost associated with processing the work queue via the bot. The computing platform may compare, the robotic process automation cost to a cost to process the work queue via another operation, and determine a performance metric for the bot based on the comparison. The computing platform may dynamically generate and transmit, in real-time, an indication of the determined bot performance metric.