It is important to maintain a healthy and fulfilling life while achieving high work performance. The factors and levels that influence work performance and well-being depend on the person; consequently, generalized models are less accurate than personalized models, which aim to predict individual outcomes. Longitudinal data collection is required to characterize personal preferences and develop personal models that can be used to maintain and enhance work performance and well-being. In this longitudinal study, we aimed to elucidate the effects of environmental, mental, and physical states on work performance. We monitored the environment using sensors while physiological data, sleep, and participants’ perceptions were gathered using a smartwatch application. We conducted a 6-week survey of 10 university students and a 7-week survey of 21 office workers. Participants answered questionnaires about subjective performance scores, physical and mental state, and perceptions of the environment 5–10 times a day. We analyzed the relationships among psychological states, environmental factors, and physiological data for each person. Additionally, cluster analysis was conducted using the Big Five personality traits and Highly Sensitive Person (HSP) scales. The findings revealed correlations between sleep and work performance, as well as between sleep and psychological states, and the trends were participant-dependent. Furthermore, the data enabled individualized evaluations of work performance. The factors influencing work performance varied among participants. However, some common trends were observable at the group level. Future research should explore the potential to predict environments that enhance work performance and well-being across different groups.