Defining and Conceptualizing Actionable Insight: A Conceptual Framework for Decision-centric Analytics

Shiang-Yen Tan, School of Information Systems, Queensland University of Technology, Queensland, Australia
Taizan Chan, School of Information Systems, Queensland University of Technology, Queensland, Australia

Abstract

Despite actionable insight being widely recognized as the outcome of data analytics, there is a lack of a systematic and commonly-agreed definition for the term. More importantly, existing definitions are generally too abstract for informing the design of data analytics systems. This study proposes a definition of actionable insight as a multi-component concept comprising analytic insight, synergic insight, and prognostic insights. This definition is informed by a conceptual framework, which also can be used to systematically understand actionable insight, both at the concept-level and component-level. Each component is explained from the analytical, cognitive, and computational perspectives and relevant design considerations are suggested. We hope this study could be a rudimentary step toward the realization of decision-centric data analytics that can deliver the promised actionable insight.