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

N. Verma, A. Voida
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引用次数: 8

Abstract

We 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.
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关于可操作:商业智能的神话和演练中的断开
我们介绍了在一个人力服务组织中使用商业智能系统的案例研究的结果。我们描述了四种商业智能神话,线人将其体验为共享的组织价值观,并且是他们走向“数据文化”轨迹的核心:数据驱动、预测和主动、共享责任和好奇。然而,对于每一个神话,我们还讨论了可操作性被数据的聚合视图(允许他们识别决策的重点领域)和期望的数据“深入”视图(允许他们了解如何在数据驱动的上下文中行动)之间的脱节所阻碍的方式。这些发现为商业智能的认识论偏差对组织的影响提供了初步的经验证据,并为更好地支持数据驱动决策的技术设计提供了启示。
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