Next-generation computing solutions, such as cyber-physical systems or Industry 4.0, are focused on increasing efficiency in process execution as much as possible. Removing unproductive delays or keeping infrastructures operating at their total capacity are typical objectives in these future systems. Decoupling infrastructure providers and service providers using Anything-as-a-Service (XaaS) paradigms is one of the most common approaches to address this challenge. However, many real scenarios not only include machines or controllers but also people and workers. In this case, deploying process execution algorithms and XaaS solutions degenerates in a People-as-a-Service scenario, which poses a critical dilemma: Can highly efficient production scenarios guarantee people’s wellbeing? In this paper, we address this problem and propose a new process execution algorithm based on a novel understanding of efficiency. In this case, a humanized efficiency definition combining traditional efficiency ratios and wellbeing indicators is used to allocate tasks and assign them to different existing workers. In order to evaluate the proposed solution, a simulation scenario including social and physical elements was built. Using this scenario, a first experimental validation was carried out.