Human Capital Value Evaluation System for Organizational Efficiency
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Solution Overview
Problem
Conventional methods for evaluating organizational unit performance are limited to financial metrics and do not consider influential human capital factors, leading to a lack of holistic assessment and subjective measurement errors.
Innovation Solution
A system and method using Human Capital Value (HCV) analysis, which processes employee, project, and organizational data to generate HCV variables, segregate them into input and output variables, and apply Multi Criteria Decision Analysis (MCDA) techniques to compute efficiency and rank organizational units based on MCDA models like DEA, TOPSIS, and AHP.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional financial metrics are used for evaluation, then the evaluation process is simple, but the assessment lacks comprehensiveness and accuracy
Solution Approach 1:
The evaluation system segments performance measurement into multiple dimensions including financial metrics, human capital metrics, and operational metrics. Each dimension is evaluated separately using appropriate indicators, then aggregated to provide a comprehensive assessment. This segmentation allows the system to maintain simplicity in individual metric collection while achieving comprehensiveness through structured integration of multiple evaluation layers.
2Adaptability or versatility
If different performance indicators are used for different organizational units, then the evaluation is tailored to specific units, but comparability across units is reduced
Solution Approach 1:
The system implements a universal evaluation framework that can adapt to different organizational unit types. The framework uses a standardized set of core indicators applicable across all units, while allowing supplementary unit-specific indicators to be added. This multi-functional approach enables the same evaluation system to serve diverse organizational units (departments, teams, projects) with both customized and comparable measurements, maintaining scientific rigor through consistent methodology across all units.
Data Source
AI summary
To evaluate performance of organizational units using Human Capital Value (HCV), the input data spread across an enterprise may be received from a user. The input data includes employee data, project related data, and organizational unit data for performance evaluation. The input data is analyzed for generating HCV variables. The HCV variables are stored in a repository (108). Further, the HCV variables may be parsed to determine an optimal set of variables. Based on the parsing, an efficiency of each organizational unit is computed. The computing is based on a Multi Criteria Decision Analysis (MCDA) technique. Based on the computing, the organizational units are ranked in a decreasing order of efficiency.