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Impact of Predictive Analytics on Business Decisions Making
Subject area: Management and Commerce · Area of research: Predictive Analysis
Abstract
Predictive analytics has revolutionized business decision-making by leveraging historical data, statistical algorithms, and machine learning to forecast future trends. This research examines how predictive analytics influences strategic, operational, and tactical decisions in businesses. A survey was conducted among 150 business professionals across industries to assess the adoption, benefits, and challenges of predictive analytics. The findings indicate that companies using predictive analytics experience improved accuracy in forecasting, cost reduction, and enhanced customer satisfaction. However, challenges such as data quality and integration persist. The study concludes that predictive analytics significantly enhances decision-making but requires proper implementation strategies.
Keywords
Predictive analytics, business intelligence, decision-making, data-driven decisions, machine learning.
References
[1] Chase, C. W. (2013). Demand-Driven Forecasting: A Structured Approach to Forecasting. Wiley.
[2] Davenport, T. H. (2014). Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press.
[3] Gartner. (2021). Predictive Analytics Market Trends: Key Insights for Business Leaders. Gartner Research.
[4] Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know About DataMiningandData-Analytic Thinking. O’Reilly Media.
[5] Siegel, E. (2016). Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Wiley.
[6] IBM. (2020). The Business Value of Predictive Analytics: ROI and Use Cases. IBM Institute for Business Value.
[7] McKinsey & Company. (2022). Scaling AI and Analytics for Competitive Advantage. McKinsey Analytics.
How to cite this paper
@article{1708772,
author = {Madhumala Kumari},
title = {Impact of Predictive Analytics on Business Decisions Making},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {11},
pages = {1884-1887},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708772.pdf},
abstract = {Predictive analytics has revolutionized business decision-making by leveraging historical data, statistical algorithms, and machine learning to forecast future trends. This research examines how predictive analytics influences strategic, operational, and tactical decisions in businesses. A survey was conducted among 150 business professionals across industries to assess the adoption, benefits, and challenges of predictive analytics. The findings indicate that companies using predictive analytics experience improved accuracy in forecasting, cost reduction, and enhanced customer satisfaction. However, challenges such as data quality and integration persist. The study concludes that predictive analytics significantly enhances decision-making but requires proper implementation strategies.},
keywords = {Predictive analytics, business intelligence, decision-making, data-driven decisions, machine learning.},
month = {May},
}