Promoting worker learning is an increasingly urgent priority: To succeed at executing technology-driven strategies, a company must have a workforce that can rapidly adapt to and master new tools, processes, and roles. As AI systems automate more manual and routine tasks, humans will likely take on work that is more cognitively challenging.1 All of this makes it increasingly critical that managers understand how to foster cognition and accelerate learning in the workplace.2
We already know that both on-the-job learning and expert knowledge are strong drivers of higher worker performance.3 But how can we further enhance work to promote learning? Is it possible to speed up people’s informal learning at work? Can some types of work make people more (or less) intelligent over time? Our research addresses these important questions. The results show that not all work is equal when it comes to fostering learning — but the differences do not result from the type of work being done. From a review of research studies across multiple disciplines (including organizational psychology, occupational health, ergonomics, and gerontology), we identified the powerful role of work design for enhancing workers’ cognition.4 This means that, irrespective of a person’s occupation, more learning will happen when work is well designed.
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Work design is about the nature of people’s work — for example, which tasks workers do and how many tasks they have — as well as how the work is organized, such as whether people work on a team or independently.5 In this article, we’ll describe five aspects of work design that we identified as shaping worker cognition, and ways to maximize them to boost learning. We’ll also discuss the implications that this research has for an aging workforce and provide recommendations that managers can put into practice.
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2. S.K. Parker and G. Grote, “Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World,” Applied Psychology, Feb. 13, 2020, https://doi.org/10.1111/apps.12241.
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18. K.Y. Pan, W. Xu, F. Mangialasche, et al., “Working Life Psychosocial Conditions in Relation to Late-Life Cognitive Decline: A Population-Based Cohort Study,” Journal of Alzheimer’s Disease 67, no. 1 (2019): 315-325.
19. T.W.H. Ng and D.C. Feldman, “The Relationship of Age to Ten Dimensions of Job Performance,” Journal of Applied Psychology 93, no. 2 (March 2008): 392.
20. R. Andel, M. Crowe, E.A. Hahn, et al., “Work-Related Stress May Increase the Risk of Vascular Dementia,” Journal of the American Geriatrics Society 60, no. 1 (January 2012): 60-67.
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24. The SMART model is based on S.K. Parker and C. Knight’s “A Higher-Order Analysis of Work Design Characteristics,” which is currently under review. Practical information about the model is available at www.smartworkdesign.com.au.
25. C. Knight and S.K. Parker, “How Work Redesign Interventions Affect Performance: An Evidence-Based Model From a Systematic Review,” Human Relations 74, no. 1 (January 2021): 69-104.
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27. S. O’Mahony and B.A. Bechky, “Stretchwork: Managing the Career Progression Paradox in External Labor Markets,” Academy of Management Journal 49, no. 5 (October 2006): 918-941.
i. X. Parent-Rocheleau and S.K. Parker, “Algorithms as Work Designers: How Algorithmic Management Influences the Design of Jobs,” Human Resource Management Review, May 10, 2021, https://doi.org/10.1016/j.hrmr.2021.100838.