Detecting Job Promotion in Information Workers Using Mobile Sensing

Abstract

Most people desire promotions in the workplace. Typically, rising through the ranks comes with increased demands, better salary and higher status among peers. However, promoted workers have to deal with new challenges, such as, adjusting to new roles and responsibilities, which can in turn impact their physical and mental wellbeing. In this year long study, we use mobile sensing to track physiological and behavioral patterns of N=141 information workers who are promoted. We show that the workers experience a change in their physiological and behavioral patterns after promotion captured by passive sensing from phones, wearables and Bluetooth beacons. Furthermore, we use a random convolutions based approach to extract patterns from multivariate time series signals and evaluate the performance of different models to classify a worker's mobile sensing data as belonging to a promoted or non-promoted period with an AUC of 0.72. As a result, we report for the first time that mobile sensing can detect job promotion events by modeling physiological and behavioral changes of information workers in an objective manner.