Predictive Modeling for Business Optimization: Leveraging Machine Learning to Enhance Decision-Making in Data-Driven Organizations

Authors: Shafeeq Ur Rahaman

DOI: https://doi.org/10.5281/zenodo.14352046

Short DOI: https://doi.org/g8t7mm

Country: India

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Abstract: The Predictive modeling has become one of the most valuable tools for optimization within organizations with data-driven approaches. By applying machine learning algorithms, predictive modeling reshapes decision-making processes. This article evaluates how predictive modeling through a machine learning algorithm enables enterprises to achieve better forecast accuracy, improved resource allocation efficiency, and more effective strategic planning. The predictive model leverages both historical data and real-time data to unlock actionable insights by predicting market trends, which point toward growth opportunities and efficiency. Key applications discussed include demand forecasting, supply chain management, customer behavior analysis, and financial planning. The study also examines the challenges associated with integrating predictive modeling into organizational workflows related to data quality, scalability, and ethical considerations. This article highlights how predictive modeling enables organizations to remain competitive in an increasingly dynamic marketplace by showing successful implementations across industries.

Keywords: Predictive modeling, machine learning, business optimization, data-driven decision making, forecasting, resource allocation, strategic planning, data analytics, market trends, organizational scalability

Paper Id: 231788

Published On: 2020-06-02

Published In: Volume 8, Issue 3, May-June 2020

Cite This: Predictive Modeling for Business Optimization: Leveraging Machine Learning to Enhance Decision-Making in Data-Driven Organizations - Shafeeq Ur Rahaman - IJIRMPS Volume 8, Issue 3, May-June 2020. DOI 10.5281/zenodo.14352046

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