About Us

The Shift Data

The American service sector is characterized by financial and temporal insecurity. Many retail and food-service employers around the country rely on on-demand scheduling practices to closely align staffing with consumer demand, representing a substantial transfer of risk from firms to workers and their families. These practices may undermine the health of workers, but scholars, policymakers, and businesses have historically lacked the data to understand the effects of workplace scheduling practices on worker health and wellbeing.

Thanks to newly available data from The Shift Project, researchers are now expanding the evidence base. Since 2016, The Shift Project has fielded surveys asking workers at specific firms about their job quality, financial security, personal health, and the health and wellbeing of their children. The data show that the vast majority of service sector workers experience instability in their weekly work schedules. Workers who experience more predictable scheduling report less stress and better overall health, compared to workers who experience less predictable and stable scheduling. In fact, the Shift data reveal that while low wages are negatively associated with poor health outcomes, unstable and unpredictable schedules are a much more significant determinant.

Project Components & Analysis

National Monitoring

The Shift Project data allow us to describe workplace-scheduling practices and to characterize the health and wellbeing of retail and food-service workers at some of the nation’s largest firms. We use these data to monitor changes over time in scheduling practices and worker outcomes, both nationally and for particular firms. We also use these data to estimate the associations between schedule instability and worker and family financial security, health, and wellbeing.


We use Shift data to rigorously estimate the effects of secure scheduling laws on work scheduling practices and on the health and wellbeing of workers and their families, focusing on laws passed in Seattle, New York City, and the state of Oregon. We collect baseline data from workers covered by each of the ordinances and from comparison samples, and then collect follow-up data following implementation of the law. We use these data in a difference-in-differences framework to identify the effects of unstable and unpredictable schedules on health.

Who Takes the High Road?

While service jobs are often thought of as uniformly “bad jobs,” existing research in economics, sociology, and labor studies in fact suggests substantial heterogeneity in workers’ experiences of precarious labor practices within this sector. We exploit Shift’s unique worker-firm matched dataset to understand whether low-wage service-sector jobs are uniformly precarious across employers, or if job quality varies across firms. We then examine if firm-level characteristics — including ownership structure, unionization, and exposure to public pressure — shape workers’ experiences of precarious scheduling and account for variation across companies.