Automated Predictive Analysis Engine for Case Management Systems
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Solution Overview
Problem
The development of predictive models is costly in terms of time, energy, and money, requiring highly educated experts and significant raw data preparation, making it inaccessible to many enterprises despite offering clear benefits.
Innovation Solution
An automated predictive analysis engine integrated with a case management system that automatically extracts and analyzes data to determine correlations, generating and continuously updating prediction models to provide on-demand predictive capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional predictive model development is used, then prediction accuracy and reliability are improved, but development cost and time increase significantly
Solution Approach 1:
The system enables automated predictive model development where the computer system automatically performs data extraction, analysis, correlation determination, and model generation without requiring manual intervention by statistical experts. The system serves itself by automatically identifying patterns and generating predictions based on historical data, eliminating the need for lengthy manual model development processes while maintaining prediction accuracy.
2Reliability
If traditional predictive model development is used, then prediction accuracy is improved, but resource consumption and cost increase
Solution Approach 1:
The invention replaces the mechanical process of manual predictive model development by statistical experts with an automated computer-based system. The computer system automatically extracts data from case management systems, analyzes correlations, and generates predictive models, substituting human expert labor with automated computational processes. This reduces resource consumption including human time, computational resources, and overall development costs while maintaining prediction accuracy.
3Ease of operation
If automated predictive analysis is implemented, then ease of operation and accessibility are improved, but device complexity increases
Solution Approach 1:
The system integrates multiple functions into a single automated predictive analysis platform that can handle various case management systems and generate different types of predictive models. The computer system is designed to universally extract data from different sources, automatically analyze various types of case attributes, and generate predictions for multiple outcomes. This multi-functionality simplifies the user experience while the backend complexity is managed through standardized automated processes.
4Measurement precision
If extensive data preparation is performed, then measurement precision and model quality are improved, but loss of time and resource consumption increase
Solution Approach 1:
The system performs preliminary automated data extraction and preparation directly from case management systems before analysis begins. The computer system automatically retrieves historical case data, structures it appropriately, and prepares it for correlation analysis without requiring manual data cleaning or preparation. This preliminary automated action ensures data quality while eliminating the time-consuming manual data preparation process that traditionally preceded predictive model development.
Data Source
AI summary
A method for providing automated predictive analysis for a case management system is disclosed and includes providing, by a server, a case management system comprising configuration information defining a plurality of case attributes and performance criteria comprising at least one performance criterion, and comprising case management data associated with the plurality of case attributes and a plurality of cases, and automatically determining a projected outcome associated with a performance criterion included in the configuration information. The method also includes identifying a correlation between a case attribute and the projected outcome based on case management data associated with the case attribute and/or case management data associated with the performance criterion, generating a prediction model based on the correlation and providing a prediction relating to the projected outcome based on the correlation.