Defining and Conceptualizing Actionable Insight: A Conceptual Framework for Decision-centric Analytics
Year: 2016
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Tan, Shiang-Yen, Chan, Taizan
Institution: Queensland University of Technology
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2433052443