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The Strategic Impact of Advanced Data Analytics Tools on Organizational Decision-Making: A Cross-Industry Comparative Study
Subject area: Science,Engineering and Technology · Area of research: Data Analytics
Abstract
This article presents a systematic literature review on the strategic impact of advanced data analytics tools on organizational decision-making processes across multiple industries, including financial services, healthcare, retail, and manufacturing. The review draws on research from information systems, strategic management, and operational studies to identify patterns of analytics adoption, key facilitators and barriers, and implications for performance metrics. By examining scholarly articles published within the last ten years, the study highlights how data accuracy, governance frameworks, and leadership support serve as foundational elements in successful analytics initiatives. Findings indicate that the integration of big data, machine learning, and AI-driven platforms substantially enhances decision-making agility, risk assessment accuracy, and resource allocation. The review also reveals that human capital particularly data scientists and cross-functional teams plays a crucial role in translating complex analytical outputs into actionable insights. Despite these benefits, challenges persist, including legacy systems, regulatory constraints, and ethical considerations related to data privacy and algorithmic bias. The analysis contributes to theoretical debates on resource-based and dynamic capabilities by emphasizing the interplay between technology, organizational culture, and market pressures. It further addresses practical concerns regarding the strategic alignment of analytics with core business objectives, underscoring the importance of tailoring analytics solutions to distinct regulatory and operational contexts. This literature review concludes that organizations across sectors stand to gain competitive advantages by developing robust analytics capabilities, but they must simultaneously navigate technical, cultural, and ethical complexities to realize the full potential of data-driven decision-making.
How to cite this paper
@article{1708914,
author = {Enuma Ezeife, Telma Erebor, Alexandra Buchanan, Raphael Iyitor},
title = {The Strategic Impact of Advanced Data Analytics Tools on Organizational Decision-Making: A Cross-Industry Comparative Study},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {11},
pages = {381-393},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708914.pdf},
abstract = {This article presents a systematic literature review on the strategic impact of advanced data analytics tools on organizational decision-making processes across multiple industries, including financial services, healthcare, retail, and manufacturing. The review draws on research from information systems, strategic management, and operational studies to identify patterns of analytics adoption, key facilitators and barriers, and implications for performance metrics. By examining scholarly articles published within the last ten years, the study highlights how data accuracy, governance frameworks, and leadership support serve as foundational elements in successful analytics initiatives. Findings indicate that the integration of big data, machine learning, and AI-driven platforms substantially enhances decision-making agility, risk assessment accuracy, and resource allocation. The review also reveals that human capital particularly data scientists and cross-functional teams plays a crucial role in translating complex analytical outputs into actionable insights. Despite these benefits, challenges persist, including legacy systems, regulatory constraints, and ethical considerations related to data privacy and algorithmic bias. The analysis contributes to theoretical debates on resource-based and dynamic capabilities by emphasizing the interplay between technology, organizational culture, and market pressures. It further addresses practical concerns regarding the strategic alignment of analytics with core business objectives, underscoring the importance of tailoring analytics solutions to distinct regulatory and operational contexts. This literature review concludes that organizations across sectors stand to gain competitive advantages by developing robust analytics capabilities, but they must simultaneously navigate technical, cultural, and ethical complexities to realize the full potential of data-driven decision-making.},
month = {May},
}