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Mythologies of BI

My paper entitled “On being actionable: Mythologies of business intelligence and disconnects in drill downs ” has been accepted to the ACM Conference on Supporting Groupwork. This research, a collaboration with Ph.D. student Nitya Verma, presents findings 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 allow 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.