  Despite actionable insight is widely recognized as the outcome of data
analytics, there is a lack of a systematic and commonly-shared 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 for actionable insight in data analytics. For this purpose, this
study conceptualizes actionable insight as a multi-component concept. The
components, namely analytics insight, synergic insight, and prognostic insights
are grounded in theories from multiple disciplines. Collectively, the
components provide a holistic definition for actionable insight. Based on the
multi-component view, a conceptual framework is introduced to actionable
insight in detail, at both the concept-level and component-level. Each
component's analytical, cognitive, and computational requirements are explained
and relevant design considerations are suggested. We hope this study could be a
rudimentary step toward the realization of data-centric data analytics that can
deliver the promised actionable insight.
