On Being Actionable: Mythologies of Business Intelligence and Disconnects in Drill Downs

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dc.contributor.authorVerma, Nitya
dc.contributor.authorVoida, Amy
dc.date.accessioned2023-03-17T22:48:41Z
dc.date.available2023-03-17T22:48:41Z
dc.date.issued2016
dc.description.abstractWe present results from a case study of the use of business intelligence systems in a human services organization. We characterize four mythologies of business intelligence that informants experience as shared organizational values and are core to their trajectory towards a culture of data": data-driven, predictive and proactive, shared accountability, and inquisitive. Yet, for each mythology, we also discuss the ways in which being actionable is impeded by a disconnect between the aggregate views of data that allows them to identify areas of focus for decision making and the desired "drill down" views of data that would allow them to understand how to act in a data-driven context. These findings contribute initial empirical evidence for the impact of business intelligence's epistemological biases on organizations and suggest implications for the design of technologies to better support data-driven decision making."en
dc.identifier.doi10.1145/2957276.2957283
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/4494
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofProceedings of the 2016 ACM International Conference on Supporting Group Work
dc.subjectbusiness intelligence
dc.subjectdata analytics
dc.subjectmythology
dc.subjectbig data
dc.titleOn Being Actionable: Mythologies of Business Intelligence and Disconnects in Drill Downsen
dc.typeText/Conference Paper
gi.citation.startPage325–334
gi.citations.count9
gi.citations.elementNitya Verma, Lynn Dombrowski (2018): Confronting Social Criticisms, In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, doi:10.1145/3173574.3174043
gi.citations.elementShiva Darian, Aarjav Chauhan, Ricky Marton, Janet Ruppert, Kathleen Anderson, Ryan Clune, Madeline Cupchak, Max Gannett, Joel Holton, Elizabeth Kamas, Jason Kibozi-Yocka, Devin Mauro-Gallegos, Simon Naylor, Meghan O'Malley, Mehul Patel, Jack Sandberg, Troy Siegler, Ryan Tate, Abigil Temtim, Samantha Whaley, Amy Voida (2023): Enacting Data Feminism in Advocacy Data Work, In: Proceedings of the ACM on Human-Computer Interaction CSCW1(7), doi:10.1145/3579480
gi.citations.elementRobson Carlos Bosse, Mario Jino, Ferrucio de Franco Rosa (2024): A Study on Data Quality and Analysis in Business Intelligence, In: Advances in Intelligent Systems and Computing, doi:10.1007/978-3-031-56599-1_33
gi.citations.elementChris Bopp, Lehn M. Benjamin, Amy Voida (2019): The Coerciveness of the Primary Key, In: Proceedings of the ACM on Human-Computer Interaction CSCW(3), doi:10.1145/3359153
gi.citations.elementNaveena Karusala, Jennifer Wilson, Phebe Vayanos, Eric Rice (2019): Street-Level Realities of Data Practices in Homeless Services Provision, In: Proceedings of the ACM on Human-Computer Interaction CSCW(3), doi:10.1145/3359286
gi.citations.elementNitya Verma (2016): Towards Re-Orienting the Big Data Rhetoric, In: Proceedings of the 19th International Conference on Supporting Group Work, doi:10.1145/2957276.2997027
gi.citations.elementChris Bopp, Amy Voida (2023): "Showing the Context": A Need for Oligopticonic Information Systems in Homelessness Measurement, In: Proceedings of the ACM on Human-Computer Interaction CSCW1(7), doi:10.1145/3579622
gi.citations.elementChris Bopp, Ellie Harmon, Amy Voida (2017): Disempowered by Data, In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, doi:10.1145/3025453.3025694
gi.citations.elementTaneea S Agrawaal, Samar Sabie, Robert Soden (2024): Moving Towards Mobility Justice: Challenges and Considerations for Supporting Advocacy, In: Proceedings of the ACM on Human-Computer Interaction CSCW1(8), doi:10.1145/3637373
gi.conference.locationSanibel Island, Florida, USA

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