Enterprise Performance Monitoring via Event-Driven Model
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Solution Overview
Problem
Existing performance management approaches face challenges in identifying useful performance measures and collecting data accurately and timely, often relying on manual processes and lacking systematic mechanisms for enterprise performance monitoring.
Innovation Solution
A method for monitoring enterprise performance that involves obtaining a model of enterprise operations, formulating performance metrics from business entities and external events, and creating an executable performance monitoring model to compute these metrics automatically, using business entities and relevant events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual processes are used for performance management, then flexibility and adaptability are maintained, but productivity and timeliness of performance monitoring deteriorate
Solution Approach 1:
The system enables automatic self-monitoring of enterprise performance through event-driven architecture. Business processes automatically generate performance data through event subscriptions and publications, eliminating the need for manual data collection while maintaining adaptability through configurable performance measures and automatic model generation.
2Measurement precision
If comprehensive data collection mechanisms are implemented, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent introduces an event-driven intermediary layer that sits between business processes and performance monitoring. Events serve as standardized intermediaries carrying performance data from various business processes to the monitoring system, simplifying data collection while maintaining comprehensive coverage through a unified event subscription mechanism.
Solution Approach 2:
The system segments performance monitoring into independent event subscriptions and publications. Each business process publishes specific event types that correspond to performance measures, allowing granular, targeted data collection without requiring a monolithic complex collection system. This modular approach reduces overall system complexity.
3Measurement precision
If business processes are modeled with detailed activity information context, then performance monitoring capability improves, but ease of operation deteriorates
Solution Approach 1:
The system automatically generates performance monitoring models from existing business process models without requiring manual intervention. The model generator automatically identifies performance measures, creates event subscriptions, and configures monitoring parameters, eliminating the need for domain experts to manually model detailed activity information while maintaining comprehensive performance monitoring capability.
Solution Approach 2:
Business processes are pre-modeled with standard activity information contexts that are automatically utilized by the performance monitoring system. The necessary contextual information is prepared in advance during business process modeling, and the performance monitoring system automatically leverages this pre-existing structure without requiring additional detailed modeling effort.
Data Source
AI summary
The techniques provided herein include obtaining a model of an enterprise operation that specifies initiation and one or more evolution milestones of one or more business entities, formulating one or more performance metrics for the enterprise operation, wherein the one or more performance metrics are calculated from the one or more business entities, the one or more evolution milestones, and one or more relevant external events, and using the one or more business entities and one or more performance metrics to automatically create an executable performance monitoring model for the enterprise operation, wherein the executable performance monitoring model processes data in the one or more business entities, the one or more evolution milestones, and the one or more relevant external events to compute the one or more performance metrics for the enterprise operation.