Electronic Task Assignment System Using Workpoint Capacity Metrics
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Solution Overview
Problem
Current human resource management systems face inefficiencies in assigning tasks to employees due to lack of visibility into the actual effort and time required for each task, leading to inefficient task allocation and wastage of computer resources, and challenges in objectively determining skill levels and capacity.
Innovation Solution
A system and method for electronic assignment of tasks based on measured and forecasted capacity of human resources, using workpoints to quantify task complexity, skill levels, and machine learning models to track and update employee capacities, enabling efficient task allocation and capacity planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual task assignment by managers is used, then human judgment and flexibility are maintained, but task allocation efficiency decreases and computer resources are wasted
Solution Approach 1:
The patent introduces an electronic assignment system that acts as an intermediary between managers and employees. The system automatically determines task assignments by matching task requirements with employee capacity and skill levels, eliminating the need for manual manager intervention in the assignment process while maintaining optimal allocation efficiency.
Solution Approach 2:
The system enables self-service by automatically calculating and updating employee capacity metrics, tracking skill levels, and performing task-employee matching without requiring manual input from managers. The system serves itself by continuously monitoring and adjusting assignments based on measured capacity data, reducing both time and computational resource waste.
2Measurement precision
If manual tracking of employee capacity is used, then flexibility in assessment is maintained, but measurement precision and objectivity decrease
Solution Approach 1:
The patent replaces manual mechanical tracking methods with an automated electronic system that objectively measures employee capacity through standardized metrics. The system substitutes human judgment with algorithm-based calculations that track workpoints, skill levels, and capacity utilization, achieving precise and consistent measurements while managing system complexity through structured data collection.
Solution Approach 2:
The system transforms subjective capacity assessment into objective parameter-based measurement by defining specific metrics such as workpoints per task, skill level ratings, and capacity percentages. These quantified parameters enable precise measurement of employee capacity and facilitate automated comparison and matching with task requirements.
3Productivity
If traditional task assignment methods are used, then simplicity in process is maintained, but task completion timeliness and efficiency worsen
Solution Approach 1:
The system performs preliminary actions by pre-calculating employee capacity metrics, skill profiles, and availability status before tasks are assigned. This advance preparation enables rapid matching when tasks need assignment, improving completion speed without adding complexity to the actual assignment moment, as the system has already processed and stored relevant capacity data.
Data Source
AI summary
A method for determining current capacity allocation and available capacity of an assignee may include determining an individual resource capacity for each open issue assigned to the assignee. The individual resource capacity is based on a workpoint assigned to each open issue and a skill level of the assignee. The workpoint represents an amount of effort required to complete each open issue. The method may also include determining the current capacity allocation by summing individual resource capacities for the assignee, determining a capacity hours by identifying a number of hours in a certain work period, determining the available capacity of the assignee by subtracting the current capacity allocation for the assignee from the capacity hours, and outputting the current capacity allocation and the available capacity of the assignee.