Unified RPA Analytics Platform for Cross-Platform Evaluation
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Solution Overview
Problem
Current robotic process automation (RPA) platforms are disconnected, limiting the ability to perform end-to-end evaluation as they do not share data, resulting in separate measures of interest for each platform rather than a comprehensive evaluation across the suite.
Innovation Solution
A system and method for evaluating RPA by receiving data from multiple RPA sources, calculating measures of interest such as execution time, time saved, and robot hours, and displaying these metrics on a dashboard for a unified end-to-end evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If RPA data is collected from multiple disconnected platforms, then comprehensive evaluation capability is improved, but system complexity increases due to data format differences and integration requirements
Solution Approach 1:
The patent introduces an intermediary component that acts as a data integration layer between multiple disconnected RPA platforms and the analytics engine. This intermediary standardizes data from different sources into a common format, enabling comprehensive evaluation without requiring direct complex connections between all platforms. The intermediary handles format conversion and data normalization, resolving the contradiction by mediating the information flow while maintaining system modularity.
Solution Approach 2:
The analytics platform is designed with universal data processing capabilities that can handle multiple RPA platform data formats through a single unified interface. The system incorporates multi-functional data adapters and standardized schemas that enable it to process diverse RPA data sources (automation platforms, process mining tools, task capture systems) through common evaluation metrics, thereby achieving comprehensive evaluation without proportionally increasing system complexity.
2Ease of manufacture
If separate measures of interest are calculated for each RPA platform, then calculation simplicity is improved, but evaluation comprehensiveness deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the evaluation process into independent modular components: data collection modules for each RPA platform, standardized data transformation layers, and separate calculation engines for different measures of interest (execution time, cost savings, robot hours). Each module maintains simplicity in its specific function while the integrated system achieves comprehensive evaluation. The segmented architecture allows independent calculation of metrics while preserving end-to-end evaluation capability through standardized data interfaces.
3Adaptability or versatility
If RPA platforms operate independently, then platform autonomy is improved, but data sharing capability deteriorates
Solution Approach 1:
The analytics platform serves as an intermediary that enables data sharing among independent RPA platforms without requiring the platforms themselves to change their autonomous operation. The intermediary collects standardized metrics from each platform independently, then integrates this data for comprehensive analysis. This approach preserves platform autonomy while establishing a mediation layer that enables cross-platform data sharing and end-to-end evaluation.
Data Source
AI summary
Systems and methods for evaluating robotic process automation (RPA) are provided. RPA data from a plurality of RPA related data sources is received. Each of the RPA related data sources is associated with a different RPA product. One or more measures of interest are calculated based on the RPA data. The one or more calculated measures of interest are output.