Business Analytics Overview

Principles

Definition

Business analytics is a research field and methodological approach that employs quantitative methods, statistical modeling, and data analysis techniques to extract actionable insights from business data. Its significance lies in informing data-driven decision-making, optimizing organizational performance, and generating strategic value through understanding past trends and predicting future outcomes.

Ontological type

Core Methods

Applications

Organizational Impact

Key developments

Key Figures

Process-Centric Integration era

Chêng Hsiao [1] is associated with Nanyang Technological University [3] and the University of Hong Kong [4] during the Process-Centric Integration era. His work on Panel data analysis—advantages and challenges [7] articulates how panel data strengthens empirical inference for operational interventions and supports timely, process-aware decision-making in dashboards and conformance testing. Umeshwar Dayal [2] is associated with University of Tennessee at Knoxville [5] and Queen's University [6] in the Process-Centric Integration era. His Business Process Intelligence [8] outlined approaches to live dashboards, process mining, and governance-aligned interventions, bridging analytics outputs with operational workflows in this era.

Analytics as Infrastructure era

Francis X. Diebold [1] is a prominent economist associated with the University of Pennsylvania [3] and the University of Chicago [4] during the Analytics as Infrastructure era. The 2009 paper Real-Time Measurement of Business Conditions [7] illustrates how real-time data could be integrated into managerial routines, enabling timely, data-driven decision making. Graeme Shanks [2] is associated with The University of Melbourne [5] and Monash University [6] during this era. His works, Towards a business analytics capability maturity model [8] (2012) and Creating Value From Business Analytics Systems: The Impact Of Strategy [9] (2011), helped establish formal maturity frameworks and strategic alignment that anchored analytics as core organizational infrastructure.

Analytics Value Creation era

Varun Grover [1], with affiliations at Michigan State University [3] and the University of South Carolina [4] during this era, is a leading figure shaping how analytics translates into strategic value. It presents Creating Strategic Business Value from Big Data Analytics: A Research Framework [7], a contribution that outlines a research framework to derive strategic business value from big data analytics and underscores governance and measurement as enablers for value creation. Dongsong Zhang [2], associated with University of Maryland, Baltimore [5] and Jinan University [6] during this era, contributed to Creating Strategic Business Value from Big Data Analytics: A Research Framework [7]. This work illustrates how analytics-enabled capabilities, supported by governance and enterprise-scale architectures, can translate data insights into measurable business value, reflecting the themes of Analytics Value Creation (2016-2023).