From Data to Learning: The Role of Data Pathways in Advancing Cross-Functional Public Sector Team Inquiry Cycles
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Title
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From Data to Learning: The Role of Data Pathways in Advancing Cross-Functional Public Sector Team Inquiry Cycles
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Description
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Addressing climate change requires public and private organizations with varying disciplinary approaches to collaborate in cross-functional partnerships. This research investigates how cross-functional teams learn new knowledge and skills while developing adaptive responses to large scale climate challenges.
Two case studies of cross-functional teams working on sustainability programs in a federally owned electric utility in the American South demonstrate the importance of managing data pathways as the basis for team learning. Project scope and preconceptions of colleagues’ professional identities were major factors that affected how the teams acquired and utilized information.
Technological advances have made tools for complex data analysis and interpretation widely accessible. The findings from this research provide guidelines that help leaders of cross-functional public sector teams maximize the data their teams use to learn about and develop adaptive solutions to climate challenges.
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Creator
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Royalty, Adam
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Contributor
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Forsyth, Ann
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Bechthold, Martin
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Mayne, Quinton
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Date
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2024-10-25T12:01:04Z
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2024
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2024-10-23
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2024
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2024-10-25T12:01:04Z
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Type
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Thesis or Dissertation
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text
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Format
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application/pdf
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application/pdf
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Identifier
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Royalty, Adam. 2024. From Data to Learning: The Role of Data Pathways in Advancing Cross-Functional Public Sector Team Inquiry Cycles. Doctoral dissertation, Harvard Graduate School of Design.
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31565016
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https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37379631
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Language
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en