This viewpoint article addresses an approach to understanding the impact of physical workload variation using fatigue-recovery type models. Seven examples are presented in which fatigue-recovery models, including a range of fatigue types, are used to interpret the effects of time-series workload patterns without necessarily quantifying workload variation directly. These examples of fatigue-recovery model analysis approaches have been risk-validated to MSDs, validated against worker’s subjective performance, and linked to manufacturing quality deficit outcomes. While these fatigue-recovery modeling approaches aimed to understand the effects of variable workload show promise, a number of challenges remain before they can be more widely deployed in practice. This includes the need for better underlying models using data from a broader range of participants, and the application supports needed to use the approach proactively in work system design. The authors argue that resulting ‘fatigue’ indicators can be more easily understood, and therefore more readily used and more meaningful in decision making, than more complex biomechanical variables currently used in occupational workload studies.