The goal of this paper is to develop an empirically-grounded framework to analyze how new technologies, particularly those used in the realm of datafication, alter or expand traditional organizational control configurations. Datafication technologies for employee-related data-gathering, analysis, interpretation and learning are increasingly applied in the workplace. Yet there remains a lack of detailed insight regarding the effects of these technologies on traditional control. To convey a better understanding of such datafication technologies in employee management and control, we employed a three-step, exploratory, multi-method morphological analysis. In step 1, we developed a framework based on twenty-six semi-structured interviews with technological experts. In step 2, we refined and redefined the framework in four workshops, conducted with scholars specializing in topics that emerged in step 1. In step 3, we evaluated and validated the framework using potential and actual users of datafication technology controls. As a result, our refined and validated "Datafication Technology Control Configurations" (DTCC) framework comprises eleven technology control dimensions and thirty-six technology control elements, offering the first insights into how datafication technologies can change our understanding of traditional control configurations.