Algorithmic Management (AM), which refers to technologies that use algorithms to oversee and direct workers, is increasingly being introduced across various sectors and workplaces. While previous research has focused on AM's impact on job quality in platform work, its effects on worker well-being in non-platform workplaces remain underexplored. This study seeks to deepen our understanding of the impact of AM on occupational health within non-platform workplaces. Drawing on the socio-technical lens and the Pressure, Disorganization and Regulatory Failure (PDR) model (Quinlan et al., 2001), it aims to identify organizational practices that shape the interplay between AM and employees' work experiences, health, and overall well-being. We conducted a comparative case study with two Swedish logistics companies and collected data from observations and semi-structured interviews. Our analysis focused on the interplay between organizational practices, AM technology, and worker experiences to understand key differences between the cases. Workers at both sites reported a low sense of autonomy and task significance. However, physical and psychological strain from AM was more pronounced in the e-commerce company, a disparity potentially explained by factors of the PDR model. We identified organizational practices that appear to positively influence workers' AM experiences: i) involving workers with the AM technology; ii) integrating AM considerations into occupational safety and health management; iii) designing AM applications that allow worker control; and iv) managerial practices that add qualitative assessments to AM's quantitative evaluations. Our research highlights the critical importance of designing organizational practices that incorporate AM in ways that promote occupational health alongside operational efficiency.