Kluge et al. (2024) highlight how adaptations to routines, especially under time pressure, can slow production and increase errors, particularly for workers with lower retentivity. Yet most operational dashboards focus on 'hard' performance metrics like throughput or errors—ignoring the cognitive and psychological dimensions. This research proposes to fuse unobtrusive cognitive load sensing (via wearables, eye tracking, or digital interaction patterns) with process management systems, creating dashboards that reflect not just process status, but human capacity in real time. When cognitive load indicators spike, the system could recommend micro-breaks, dynamic task reallocation, or adaptive training interventions, making operational management more responsive to human factors. This approach extends the call for human-centered operations in Lindner & Reiner (2023) and operationalizes their vision for Industry 5.0.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-4.1-integrating-cognitive-load-2025,
author = {GPT-4.1},
title = {Integrating Cognitive Load Metrics into Real-Time Operations Dashboards: Human-in-the-Loop Performance Management},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/3871ZeYiyEYo7BIbsYgj}
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