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Related Experiment Video

Updated: Jun 10, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

Reducing understaffing and shift work with Temporal Profile Optimization (TPO).

Karin Boonstra-Hörwein¹, Dieter Punzengruber, Johannes Gärtner

¹XIMES GmbH, Vienna, Austria. hoerwein@ximes.com

Applied Ergonomics

|August 17, 2010

Summary

This summary is machine-generated.

Temporal Profile Optimization (TPO) improves shift schedules by enhancing workforce forecasts and reengineering work processes. This approach reduces understaffing and undesirable shift work, leading to better ergonomics and operational efficiency.

Related Experiment Videos

Last Updated: Jun 10, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

Area of Science:

Operations Research
Human Factors Engineering
Workforce Management

Background:

Shift work and understaffing negatively impact employee well-being and operational quality.
Current workforce planning often lacks accurate demand forecasting and efficient work process integration.
Optimizing shift schedules is crucial for improving ergonomic quality and reducing work pressure.

Purpose of the Study:

To introduce Temporal Profile Optimization (TPO) as a systematic method for improving shift schedules.
To develop advanced forecasting methods (Temporal Profile Forecasts) for workforce requirements.
To apply business process reengineering principles (Temporal Profile Reengineering) for work redistribution and load balancing.

Main Methods:

Temporal Profile Optimization (TPO) integrates demand forecasting and workforce planning.
Temporal Profile Forecasts utilize time-stamped historical data, supplementing traditional time series models.
Temporal Profile Reengineering employs systematic methods to identify and redistribute movable work, streamlining load lines.

Main Results:

TP-Forecasts for air traffic controllers improved accuracy, enabling shift designs with 3-4% less shift work.
In a logistics warehouse, TP-Forecast and TP-Reengineering created a more even workforce requirement curve.
The warehouse case study resulted in shorter shifts and decreased overtime due to optimized work processes.

Conclusions:

Temporal Profile Optimization (TPO) offers a promising approach to enhance the ergonomic quality of shift schedules.
Improved forecasting accuracy and work process reengineering are key to reducing understaffing and optimizing workforce deployment.
The practical application of TPO demonstrates significant potential for operational improvements and employee well-being.