Achieving Lean Data Science Agility Via Data Driven Scrum Saltz, Jeffrey Sutherland, Alex Hotz, Nicholas 2021-12-24T18:26:33Z 2021-12-24T18:26:33Z 2022-01-04
dc.description.abstract This paper first explores the concept of a lean project and defines four principles team should follow to achieve lean data science. It then describes a new team process framework, which we call Data Driven Scrum (DDS), which enables lean data science project agility. DDS is similar to Scrum but key differences include that DDS defines capability-based iterations (as compared to Scrum time-based sprints), DDS increases the focus in observing and analyzing the output of each iteration (experiment), and that DDS defines process improvement meetings (e.g. retrospectives iteration reviews) to be held on a frequency the team deems appropriate (as compared to Scrum which defines these meetings to be at the end of each iteration). The paper also reports on a pilot study of an organization that adopted the DDS framework.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.876
dc.identifier.isbn 978-0-9981331-5-7
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Agile and Lean: Organizations, Products and Development
dc.subject agile
dc.subject kanban
dc.subject process
dc.subject scrum
dc.title Achieving Lean Data Science Agility Via Data Driven Scrum
dc.type.dcmi text
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