Crowd Worker Task Routing Based on Performance Scores
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Solution Overview
Problem
Crowdsourcing platforms inefficiently assign tasks to workers based on availability rather than skill level, leading to reduced efficiency and quality in task completion.
Innovation Solution
A computer-implemented method that routes tasks to crowd workers based on their performance scores and skill categories, using a scoring system to dynamically assign tasks to workers with the necessary skills and efficiency for specific tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If tasks are assigned to crowd workers based on availability (next worker in queue), then task assignment simplicity is improved, but task completion quality and efficiency deteriorate
Solution Approach 1:
The system changes the assignment parameter from simple availability status to a composite parameter including skill scores, task completion rates, and quality metrics. This allows the system to select workers based on multiple performance dimensions rather than just availability, thereby improving task completion quality while maintaining automated assignment simplicity
Solution Approach 2:
The system implements feedback loops where worker performance on completed tasks is continuously measured and used to update skill scores. These updated scores then feed into the task assignment algorithm, creating a dynamic system that automatically adapts to worker capabilities and improves assignment quality over time
2Speed
If tasks are assigned to crowd workers based on availability (next worker in queue), then assignment process speed is improved, but overall productivity deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing skill scores, task completion rates, and performance metrics for all workers before task assignment occurs. This pre-processing allows the assignment algorithm to quickly query and compare worker capabilities without performing complex calculations at assignment time, maintaining fast assignment speed while improving overall productivity through better worker-task matching
3Device complexity
If tasks are assigned without regard to worker skill level, then system complexity is reduced, but task completion efficiency deteriorates
Solution Approach 1:
The system implements self-service by automatically collecting performance data from task completions, calculating skill scores, and using these scores for assignment decisions without requiring manual intervention. The system serves itself by continuously updating worker profiles and making automated assignments based on accumulated performance data, reducing manual complexity while improving matching efficiency
Data Source
AI summary
One embodiment of the invention disclosed herein provides techniques for distributing tasks to skilled workers participating in a managed crowd-sourcing workforce. A crowd worker routing system receives a request for a task assignment from a first worker participating in the crowd-sourcing workforce. The crowd worker routing system retrieves one or more scores associated with the first worker, wherein each score is related to the performance of the first worker with respect to completing a prior set of task assignments. The crowd worker routing system determines that a first task assignment included in a first set of task assignments is related to a first score included in the one or more scores. The crowd worker routing system determines whether to route the first task assignment to the first worker for completion based on the first score and one or more routing rules.