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Exploring the Organizational Models for Data Science in Agile Software Development: Challenges and Strategies from a Multi-Case Study

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dc.contributor.authorUlfsnes, Rasmus
dc.contributor.authorBerntzen, Marthe
dc.contributor.authorMoe, Nils Brede
dc.contributor.authorBarbala, Astri
dc.contributor.authorSporsem, Tor
dc.contributor.authorStray, Viktoria
dc.date.accessioned2023-12-26T18:53:09Z
dc.date.available2023-12-26T18:53:09Z
dc.date.issued2024-01-03
dc.identifier.doihttps://doi.org/10.24251/HICSS.2024.870
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other91e8afc3-ec48-41cb-8be5-81da0617d307
dc.identifier.urihttps://hdl.handle.net/10125/107256
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAgile and Lean: Organizations, Products and Development
dc.subjectagile
dc.subjectdata science
dc.subjectteam
dc.subjectteam topologies
dc.titleExploring the Organizational Models for Data Science in Agile Software Development: Challenges and Strategies from a Multi-Case Study
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractIn an increasingly fast-paced and dynamic world with exponentially more data, more roles are required in agile software development. At the same time, the development team needs to maintain speed and autonomy. The challenges surrounding the organization of cross-functional teams are thus exacerbated. Through a multi-case study with interviews from five organizations, we show how agile companies use different models of organizing data scientists. We find that there are specific challenges related to each of these organizational models and that some challenges are shared among all the organizational models. Challenges include difficulty coordinating development strategies and a lack of resources. In addition, we identify strategies used to overcome the challenges, including coordinating mechanisms for platform teams, communities of practice for data scientists, and the development of shared playbooks.
dcterms.extent10 pages
prism.startingpage7249

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