Business Intelligence and Decision Making: Understanding B.I. as a Theory-performing Discipline of Decision Improvement

Business intelligence (BI) is a DSS discipline aimed at providing timely, accurate information and analytical capabilities to support business decision-making. Despite much research on BI, though, we still understand little about how it actually affects decisions, because most of the literature has a data-centric or technology-centric focus which takes decision-making for granted. A decision-centric study of business intelligence is difficult because of the diversity of, and tension between, normative and descriptive theories of decision-making. We propose to view business intelligence as a theory-performing discipline in which a dialogue between academics and practitioners transforms normative decision theories into prescriptive theories-in-use. We identify three theories that constitute our current understanding of decision-making, and relate them to three separate but complementary slices of business intelligence practice. We are able to separate the complicated activities of business intelligence into three rational logics of action. We discuss how these three practices fit together, their interactions, and their relationship to the concepts of strategic, tactical, and operational business intelligence. We conclude that the way BI practitioners think about decision shapes the organizational and technological interventions they make in the name of business intelligence. We also consider future directions for research.

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