Quantified factory worker: field study of a web application supporting work well-being and productivity

Abstract

The work on the factory floor is gradually changing to resemble knowledge work due to highly automated manufacturing machines. In the increasingly automated work environment, the machine operator’s task is to keep the production running and to solve possible problems quickly. This work is expected to become more autonomous, which raises the importance of supporting the workers’ well-being. An important aspect of that is giving concrete feedback of success at work as well as feedback on physical and mental load. We implemented a smartphone optimized web application, Worker Feedback Dashboard that offers feedback to machine operators about their well-being at work and personally relevant production data as well as their connections to each other. The feedback is personal and based on objective, near real-time measurements. We present the results of a field study, in which ten machine operators used the application for 2–3 months. We studied the operators’ user experience, usage activity, perceived benefits and concerns for the application with questionnaires, interviews and application log data. The operators found the feedback interesting and beneficial, and used the application actively. The perceived benefits indicate impacts on well-being as well as on work performance. Based on the results, we highlight three design implications for quantified worker applications: presenting meaningful overviews, providing guidance to act based on the feedback and refraining from too pervasive quantification not to narrow down the meaningful aspects in one’s work.