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The goal of this article 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 used a three-step, exploratory, multi-method morphological analysis. In step 1, we developed a framework based on 26 semi-structured interviews with technological experts. In step 2, we refined and redefined the framework in ... and redefined the framework in four workshops 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 Configuration” (DTCC) framework comprises 11 technology control dimensions and 36 technology control elements, offering the first insights into how datafication technologies can change our understanding of traditional control configurations.
Schafheitle et al. (Fri,) studied this question.