Article Title
Evaluation of Financial Performance Indicators Using Ensemble Machine Learning Techniques: A Case Study of a Diversified Industrial Enterprise
- Author Name: Rajendra Kattunga, Bilquis Ali and Prabha Patil
- Affiliations: Business Systems Lead Analyst, Zimmer Biomet, USA
- Published Date: 2025-11-06
- DOI: https://doi.org/10.55124/jbid.v2i4.266
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Abstract
Financial performance evaluation plays an important part in understanding firms’ operational efficiency and profitability. This study examines the link between important financial input parameters—Revenue, Earnings before Interest, Taxes, Depreciation, and Amortization (EBITDA), and Profit Margin—and the output parameter Net Profit. By adopting a structured evaluation framework, the research aims to assess how variations in core financial indicators influence overall profitability. This discovery is significant because it bridges the gap between standard financial analysis and structured performance evaluation models. While revenue generation and profitability metrics are commonly analyzed independently, their combined impact on net profit is often underexplored in a systematic manner. The methodology adopted in this study involves a quantitative evaluation framework based on clearly defined input and output financial parameters. Initially, relevant financial data are collected from reliable sources such as annual reports or financial databases. The input parameters—Revenue, EBITDA, and Profit Margin—are analyzed to determine their influence on the output parameter, Net Profit. Data normalization and comparative analysis techniques are applied to ensure consistency and reliability of results. In this study, Revenue, EBITDA, and Profit Margin are considered as alternative input parameters representing different dimensions of organizational financial performance. Revenue reflects the overall sales-generating capability of the organization, while EBITDA indicates operational profitability by excluding non-operational expenses. Net Profit is the major output evaluation parameter was chosen because it symbolizes the ultimate financial outcome of organizational operations. It reflects the combined effects of revenue generation, cost management, taxation, and financial structure. By using Net Profit as the output parameter, the study ensures that the evaluation focuses on the most critical indicator of financial success. The results of the study indicate a strong dependency of Net Profit on the selected input parameters. Revenue and EBITDA show a direct and significant influence on Net Profit, highlighting the importance of operational performance in achieving financial sustainability. The study concludes that effective management of Revenue, EBITDA, and Profit Margin is essential for enhancing Net Profit. A structured evaluation framework provides deeper insights into financial performance compared to conventional analysis methods. Keywords: Financial Performance Evaluation; Revenue; EBITDA; Profit Margin; Net Profit; Quantitative Analysis; Decision Support Systems.