Exploring Critical Success Factors in Agile Analytics Projects
Files
Date
2020-01-07
Authors
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
Via updating Chow and Cao’s list of success factors for agile projects, attributes of potential critical success factors (CSF’s) for agile analytics projects were identified from the literature. Ten new attributes were added to Chow and Cao’s original list. Seven new attributes from the general agile project literature address: risk appetite, team diversity and availability, engagement, project planning, shared goals, and methods uncertainty. Three attributes specific to analytics projects were added: data quality, model validation, and building customers’ trust in model solution. The potential validity of the various CSF’s and attributes was explored via data from case studies of two analytics projects that varied in deployment success. The more successful project was found to be stronger in almost all the factors than the failed project. The findings can help researchers and analytics practitioners understand the environmental conditions and project actions that can help get business value from their analytics initiatives.
Description
Keywords
Big Data and Analytics: Pathways to Maturity, agile, analytics projects, business intelligence, success
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 53rd Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.