Automated Compensation Analysis System Using Machine Learning
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Solution Overview
Problem
Organizations face difficulties in analyzing and comparing compensation across their entire workforce, leading to potential overpayment or underpayment of employees, which can result in increased attrition and decreased productivity, as well as challenges in attracting top talent due to misaligned compensation strategies.
Innovation Solution
A system and method that utilize a computer program product to obtain compensation benchmarks, compare employee compensation to market standards, and provide recommendations for ensuring competitiveness, using machine learning and neural network computing to analyze data from disparate systems and provide actionable insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual compensation analysis methods are used, then implementation simplicity is maintained, but analysis speed and comprehensiveness deteriorate
Solution Approach 1:
The patent replaces manual compensation analysis with an automated computer-based system that retrieves compensation data from multiple sources, performs comparisons, and generates reports automatically. This substitution of mechanical/manual processes with automated computing systems directly resolves the contradiction by dramatically increasing analysis speed while managing system complexity through software automation.
Solution Approach 2:
The system enables organizations to perform their own compensation analysis by providing automated tools that retrieve data, perform comparisons against benchmarks, and generate insights without requiring external consulting services. This self-service capability increases productivity by making compensation analysis readily available while keeping the system complexity contained within the automated platform.
2Measurement precision
If comprehensive compensation data collection across the organization is implemented, then measurement precision improves, but data processing complexity increases
Solution Approach 1:
The patent segments the compensation analysis process into distinct components: data retrieval from multiple sources, data normalization, benchmark comparison, and report generation. This segmentation allows comprehensive data collection while managing complexity by processing different data types through specialized modules rather than a monolithic system.
Solution Approach 2:
The system employs a universal data processing framework that handles multiple data types (compensation data, benchmark data, employee information) through standardized processes. This multi-functional approach enables precise comparisons across the entire organization while avoiding the need for separate complex processing systems for each data type.
3Measurement precision
If detailed employee information is collected for analysis, then compensation comparison accuracy improves, but information processing time increases
Solution Approach 1:
The system performs preliminary data retrieval and normalization before the actual compensation comparison analysis. By pre-processing the data from multiple sources and organizing it in advance, the system reduces the time required for the core comparison operation while maintaining high accuracy through comprehensive employee information.
Solution Approach 2:
The system implements continuous data processing where compensation data is retrieved, normalized, and compared in an ongoing manner rather than in discrete batches. This continuous processing maintains measurement precision through detailed employee information while minimizing time loss by keeping the analysis pipeline constantly active and efficient.
Data Source
AI summary
The present disclosure relates generally to tools to determine compensation and, more particularly, to a system, method and computer program product to determine workforce compensation.