Abstract :

Key Performance Indicators (KPIs) Are Essential Quantitative Measures Used By Organizations To Evaluate Operational Efficiency, Financial Performance, And Strategic Progress. Accurate Analysis And Forecasting Of KPIs Play A Crucial Role In Effective Decision Making And Long-term Planning. However, Traditional KPI Analysis Approaches Primarily Rely On Historical Reports And Manual Interpretation, Which Are Often Time-consuming, Reactive, And Insufficient For Predicting Future Trends In Dynamic Business Environments. This Project Presents An AIBased KPI Prediction System That Leverages Ma-chine Learning Techniques To Forecast Future KPI Values Using Historical Business Data. The Proposed System Incorporates Data Collection, Preprocessing, Feature Engineering, And Predictive Modeling To Ensure Reliable And Accurate Predictions. Various Machine Learning Algorithms Are Utilized To Learn Complex Patterns And Relationships Within The Data, Enabling The System To Predict Key Business Metrics Such As Revenue Growth, Pro-ductility Levels, And Operational Efficiency. To Enhance Usability And Decision Support, The System Integrates A Stream Lit-based Interactive Dashboard That Visually Presents Historical Trends, Predicted KPI Values, And Performance Insights In Real Time. The Dashboard Allows Users To Analyze Patterns, Identify Potential Risks, And Evaluate Future Performance Scenarios Effectively. The Experimental Results Demonstrate That The AIbased Approach Significantly Improves Prediction Accuracy Compared To Traditional Statistical Methods. By Providing Timely And Data-driven Insights, The Proposed System Assists Organizations In Proactive Planning, Performance Optimization, And Strategic Decision-making, Thereby Contributing To Improved Business Efficiency And Competitiveness.

Published:

25-5-2026

Issue:

Vol. 26 No. 5 (2026)

Page Nos:

1580-1591

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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