Multi-Dimensional Worker-Type Efficiency Ranking for Task Allocation
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Solution Overview
Problem
Existing methods for evaluating task completion efficiency across diverse worker types, including human, automated, outsourced, and remote workers, lack a comprehensive, quantitative framework that considers speed, accuracy, cost, and interaction dynamics, hindering informed decision-making on task allocation and workforce optimization.
Innovation Solution
A computer-implemented system and method that quantifies task completion efficiency by acquiring performance indicators, calculating cost efficiency indexes, task completion rates, and accuracy ratings, and ranking worker types, with real-time dashboard displays and infrastructure-as-code file generation for workflow adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional qualitative measures or basic quantitative metrics are used to assess task execution efficiency, then the assessment process is simple, but the view of efficiency gains is incomplete and lacks comprehensiveness
Solution Approach 1:
The patent segments the efficiency assessment into multiple distinct dimensions including speed metrics, accuracy metrics, cost metrics, and interaction dynamics. Each dimension is measured and evaluated separately through specific indicators, allowing comprehensive analysis without overwhelming complexity. This segmentation enables organizations to understand efficiency gains across multiple facets rather than relying on a single aggregate measure.
Solution Approach 2:
The patent transitions from traditional one-dimensional efficiency measurement (e.g., time or output volume) to a multi-dimensional framework that incorporates speed, accuracy, cost, and interaction dynamics. This dimensional expansion provides a holistic view of task execution efficiency by evaluating performance across multiple axes simultaneously, enabling more nuanced comparisons between different worker types.
2Loss of information
If comprehensive multi-dimensional performance tracking is implemented, then the insight quality improves, but the data processing complexity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual data collection, processing, and analysis methods with an automated computer-implemented system. The system automatically tracks performance indicators across multiple dimensions, processes large volumes of data, and generates insights without requiring significant human time investment. This substitution of mechanical human analysis with automated computational processing maintains comprehensive multi-dimensional tracking while dramatically reducing time consumption.
3Measurement precision
If detailed performance indicators are collected and analyzed manually, then the analysis depth increases, but the scalability and applicability across different organizations are limited
Solution Approach 1:
The patent creates a universal framework that can be applied across different organizations, industries, and worker types (human, automated, outsourced, gig, remote). The system collects and analyzes the same core performance indicators across diverse contexts, enabling consistent efficiency comparisons. This universal approach maintains detailed analysis depth while ensuring scalability and broad applicability through standardized measurement protocols that adapt to various organizational structures.
Data Source
AI summary
A computer-implemented method includes acquiring performance indicators associated with a first and second worker type for completing a task, wherein the performance indicators include task duration metrics, expense metrics and accuracy metrics, inputting the performance indicators to a computing module, determining a cost efficiency index, a task completion rate and an accuracy rating associated with each of the first and second worker type, determining a difference between each of the cost efficiency index, the task completion rate and the accuracy rating of the first and second worker type, for each of the cost efficiency index, the task completion rate and the accuracy rating, ranking each of the first and second worker type relative to one another based on the difference, and, for each of the cost efficiency index, the task completion rate and the accuracy rating, forwarding a result of the ranking to a dashboard.