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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21578
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Total Authors : 22438
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| Paper Title: | Intelligent Vendor Performance Analysis and Prediction using Machine Learning and Power BI |
| Authors Name: | Sonar Priyanka , Dalvi Sarita , Sawant Shraddha |
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| Author Reg. ID: |
IJRTI_207288
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| Published Paper Id: | IJRTI2511021 |
| Published In: | Volume 10 Issue 11, November-2025 |
| DOI: | |
| Abstract: | Vendor selection and monitoring are critical for supply-chain stability, cost control, and product quality. Traditional vendor evaluation methods are often manual, subjective, and unable to forecast future performance. This paper presents a data-driven system that integrates machine learning (ML) prediction with Power BI visualization to evaluate and predict vendor performance. Using cleaned procurement records (delivery times, costs, quality ratings, fulfilment rates), we engineered features, trained ensemble ML models, and exported predictions to Power BI for interactive dashboards. The Random Forest model produced the best results in our experiments (high accuracy and stable feature importances), enabling classification of vendors into performance tiers and early identification of risk. The integrated solution reduces subjectivity, provides actionable KPIs, and supports data-driven procurement decisions. |
| Keywords: | Vendor performance, Predictive analytics, Machine learning, Power BI, Vendor reliability, Random Forest, Feature engineering. |
| Cite Article: | "Intelligent Vendor Performance Analysis and Prediction using Machine Learning and Power BI", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.a149-a152, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511021.pdf |
| Downloads: | 000234 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2511021
Registration ID:207288
Published In: Volume 10 Issue 11, November-2025
DOI (Digital Object Identifier):
Page No: a149-a152 Country: PUNE, Maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2511021 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2511021 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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