Integrating Predictive Analytics into Core MBA Pedagogy: A Multi-Disciplinary Framework for Enhancing Data-Driven Decision-Making in Business Education

Abstract: The rapid and unprecedented datafication of the global economy has generated an urgent, systemic imperative for business schools to transcend traditional pedagogical boundaries and integrate predictive analytics deeply into their core management curricula. Despite widespread institutional recognition of data-driven decision-making as a fundamental competency for the twenty-first-century leader, contemporary management education frequently remains heavily siloed. Traditional business programs often maintain a rigid separation between quantitative technical techniques taught in specialized analytics tracks and qualitative strategic oversight taught in general management courses. This structural disconnect leaves many business graduates well-versed in descriptive, retrospective historical analysis yet fundamentally ill-equipped to navigate the complexities of forward-looking, algorithmic enterprise management. To address this widening competency gap, this paper proposes a comprehensive, multi-disciplinary framework designed to embed predictive analytics seamlessly across foundational business domains, including finance, marketing, human resource management, supply chain operations, and strategic planning.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23052734
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Integrating Predictive Analytics into Core MBA Pedagogy: A Multi-Disciplinary Framework for Enhancing Data-Driven Decision-Making in Business Education

Dhanraj Kalgi, Tejas Pawar
Zenodo (CERN European Organization for Nuclear Research)
Big Data and Business Intelligence
article

Integrating Predictive Analytics into Core MBA Pedagogy: A Multi-Disciplinary Framework for Enhancing Data-Driven Decision-Making in Business Education

Dhanraj Kalgi, Tejas Pawar
article en

Abstract

Abstract: The rapid and unprecedented datafication of the global economy has generated an urgent, systemic imperative for business schools to transcend traditional pedagogical boundaries and integrate predictive analytics deeply into their core management curricula. Despite widespread institutional recognition of data-driven decision-making as a fundamental competency for the twenty-first-century leader, contemporary management education frequently remains heavily siloed. Traditional business programs often maintain a rigid separation between quantitative technical techniques taught in specialized analytics tracks and qualitative strategic oversight taught in general management courses. This structural disconnect leaves many business graduates well-versed in descriptive, retrospective historical analysis yet fundamentally ill-equipped to navigate the complexities of forward-looking, algorithmic enterprise management. To address this widening competency gap, this paper proposes a comprehensive, multi-disciplinary framework designed to embed predictive analytics seamlessly across foundational business domains, including finance, marketing, human resource management, supply chain operations, and strategic planning.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Big Data and Business Intelligence
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Integrating Predictive Analytics into Core MBA Pedagogy: A Multi-Disciplinary Framework for Enhancing Data-Driven Decision-Making in Business Education — Dhanraj Kalgi, Tejas Pawar · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS