Increasingly scholars have access to dynamic data on employees matched to employers, in some cases for entire economies. This is the administrative side of the big data revolution. I have a current project funded by the NSF Building Data Capacity program to form a network of scholars to develop a metadata and source data archive for the rich organizational data collected by the US Equal Employment Opportunity Commission. I am also developing two-mode network models of organizational dynamics based on mobility of people (edges) between jobs (mode 1) and workplaces (mode 2). Conceptualizing labor markets as the network of transitions among employers may help us understand classic questions of, wage setting, innovation, and local economic development. Initial models focus on all employer-employee matches in the Stockholm labor market from 2001 to 2007. A third project employees administrative longitudinal employer-employee data to describe and model workplace income inequality dynamics in Sweden, Germany, France, and Slovenia. In my work the core assumption is that it is the relationships among actors, rather than the actors themselves, that drive organizational outcomes.