Trustworthy and Explainable Decision-Making for Workforce allocation

TL;DR

This paper introduces a decision-making tool for workforce allocation that emphasizes explainability and human-in-the-loop mechanisms to improve trust and operational efficiency in industrial settings.

Contribution

It presents a novel, explainable decision-support system with human-in-the-loop features for workforce allocation in industrial environments.

Findings

Prototype demonstrates effective performance in real scenarios.

Enhanced user trust through explainability and interactive conflict resolution.

Improved operational efficiency in workforce management.

Abstract

In industrial contexts, effective workforce allocation is crucial for operational efficiency. This paper presents an ongoing project focused on developing a decision-making tool designed for workforce allocation, emphasising the explainability to enhance its trustworthiness. Our objective is to create a system that not only optimises the allocation of teams to scheduled tasks but also provides clear, understandable explanations for its decisions, particularly in cases where the problem is infeasible. By incorporating human-in-the-loop mechanisms, the tool aims to enhance user trust and facilitate interactive conflict resolution. We implemented our approach on a prototype tool/digital demonstrator intended to be evaluated on a real industrial scenario both in terms of performance and user acceptability.