Job Allocation System for Agent Skill Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Business process outsourcing faces challenges in allocating jobs to agents to maximize the probability of meeting service level agreements (SLAs) while ensuring optimal throughput, quality, and cost efficiency, due to variations in job types and agent skill sets, and the need for human intervention which can lead to inefficiencies and errors.
Innovation Solution
A system and method for allocating jobs to agents based on eligibility criteria, using a user-defined interface to determine the most optimal allocation of sub-steps to agents, calculating supply and demand side factors, and generating a transportation matrix to maximize the objective function of assigning high-priority jobs to highly efficient agents, ensuring no agent remains idle and no job is unprocessed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If human intervention is used in work allocation, then flexibility and adaptability are maintained, but inefficiencies and errors increase
Solution Approach 1:
The system enables self-service through automated algorithms that independently perform job allocation without human intervention. The algorithm automatically evaluates agent skills, job requirements, and allocation criteria to make decisions, eliminating manual processing errors while maintaining adaptability through configurable allocation rules.
Solution Approach 2:
The patent replaces the mechanical human decision-making system with an automated computational algorithm. The system uses data processing and algorithmic logic to substitute for manual evaluation and assignment processes, improving efficiency while maintaining the flexibility to handle complex allocation scenarios through programmable rules.
2Reliability
If jobs are allocated manually to match skill sets, then quality levels can be maintained, but throughput is reduced
Solution Approach 1:
The system changes the parameters of allocation decision-making by introducing multiple evaluatable criteria such as skill matching scores, agent availability, job priority levels, and historical performance metrics. The algorithm processes these parameters simultaneously to make optimized allocations that balance quality requirements with throughput maximization.
Solution Approach 2:
The system performs preliminary actions by pre-evaluating and ranking agents based on their skill sets and pre-assessing job requirements before actual allocation occurs. This preliminary sorting and categorization enables the system to rapidly match jobs to appropriate agents without manual review, maintaining quality through pre-established matching criteria while increasing throughput.
3Productivity
If allocation algorithms are implemented, then throughput is maximized, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex allocation system into distinct functional modules: agent skill evaluation module, job requirement analysis module, allocation algorithm module, and performance monitoring module. This modular architecture reduces overall system complexity by allowing each component to be developed, tested, and maintained independently while working together to maximize throughput.
4Adaptability or versatility
If multiple job types are mapped to various agents, then service coverage is improved, but allocation difficulty increases
Solution Approach 1:
The system implements universality by creating a single allocation algorithm that can handle multiple job types and agent combinations through a unified decision-making framework. The algorithm universally applies the same evaluation criteria and optimization logic across different job categories, eliminating the need for separate allocation procedures for each job type while maintaining comprehensive service coverage.
Data Source
AI summary
A system and method for allocating jobs to an agent is disclosed. In one embodiment, a method for allocating jobs to an agent includes defining, for each job of the jobs, a job type associated with at least one job and at least one sub-step associated with the at least one job, determining eligibility to perform the at least one sub-step by an agent of agents, determining a number of jobs of each job type to be performed by the agent based on the eligibility determination, and automatically generating agent-specific job queues based on the number of jobs.