Understanding personal productivity: How knowledge workers define, evaluate, and reflect on their productivity
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019•dl.acm.org
Productivity tracking tools often determine productivity based on the time interacting with
work-related applications. To deconstruct productivity's diverse and nebulous nature, we
investigate how knowledge workers conceptualize personal productivity and delimit
productive tasks in both work and non-work contexts. We report a 2-week diary study
followed by a semi-structured interview with 24 knowledge workers. Participants captured
productive activities and provided the rationale for why the activities were assessed to be …
work-related applications. To deconstruct productivity's diverse and nebulous nature, we
investigate how knowledge workers conceptualize personal productivity and delimit
productive tasks in both work and non-work contexts. We report a 2-week diary study
followed by a semi-structured interview with 24 knowledge workers. Participants captured
productive activities and provided the rationale for why the activities were assessed to be …
Productivity tracking tools often determine productivity based on the time interacting with work-related applications. To deconstruct productivity's diverse and nebulous nature, we investigate how knowledge workers conceptualize personal productivity and delimit productive tasks in both work and non-work contexts. We report a 2-week diary study followed by a semi-structured interview with 24 knowledge workers. Participants captured productive activities and provided the rationale for why the activities were assessed to be productive. They reported a wide range of productive activities beyond typical desk-bound work-ranging from having a personal conversation with dad to getting a haircut. We found six themes that characterize the productivity assessment-work product, time management, worker's state, attitude toward work, impact & benefit, and compound task and identified how participants interleaved multiple facets when assessing their productivity. We discuss how these findings could inform the design of a comprehensive productivity tracking system that covers a wide range of productive activities.
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