RPA Bot Performance Tracking With Real-Time Cost Comparison
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Solution Overview
Problem
Evaluating the effectiveness of robotic process automation (RPA) is challenging due to difficulties in accurately and consistently tracking bot performance, which hinders the quantification of cost savings and efficiency gains.
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 manual spreadsheet tracking is used to capture bot performance, then implementation simplicity is maintained, but measurement precision and consistency of bot performance tracking deteriorate
Solution Approach 1:
The patent introduces an automated performance tracking system that acts as an intermediary between the RPA bot and the performance metrics. This system automatically captures bot actions, assigns value metrics to work queue items, and calculates performance metrics, eliminating the need for manual spreadsheet tracking while ensuring consistent and accurate measurement of bot performance.
2Measurement precision
If automated performance tracking with real-time value metric assignment is implemented, then measurement precision and consistency improve, but device complexity increases
Solution Approach 1:
The performance tracking system is designed to be universal and multi-functional, capable of tracking multiple bot instances across different work queues simultaneously. It assigns value metrics to various types of work queue items and calculates different performance metrics (productivity, quality, cost savings) through a single integrated platform, reducing the need for separate tracking systems for different scenarios.
Solution Approach 2:
The system enables self-service performance tracking by automatically capturing bot actions and calculating performance metrics without requiring manual intervention. The bot itself generates the data needed for performance measurement through its automated actions, and the system automatically assigns value metrics and calculates results, reducing operational complexity.
3Productivity
If real-time dynamic performance metric generation is implemented, then productivity and responsiveness improve, but use of energy and computational resources increase
Solution Approach 1:
The system implements partial action by assigning value metrics selectively to work queue items based on their type and importance. Not all items require the same level of detailed tracking, and the system can adjust the granularity of performance measurement based on organizational needs, reducing unnecessary computational overhead while maintaining productivity benefits.
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.