| Nazal Salam, 23LSCG29; Tigin Thomas Varghese, 23LSCG46; Ashith P, 23LSCG08, BCom VI Sem G, Department of Commerce, Kristu Jayanti University, Bengaluru, India |
Business analytics focuses on using data and analytical techniques to support effective business decision-making. It involves descriptive analytics, which explain past performance, predictive analytics, which forecast future trends, and prescriptive analytics, which recommend actions to improve outcomes. By relying on data-driven insights, organizations can make more accurate and objective strategic decisions.
Statistical and analytical methods play a key role in business analytics. Techniques such as regression analysis, hypothesis testing, time-series analysis, and machine learning models are used to identify patterns, predict customer behavior, forecast sales, and assess business risks. These methods help organizations anticipate future challenges and opportunities.
Business analytics is widely applied across marketing, finance, operations, and human resources. Marketing analytics aids in customer segmentation, campaign evaluation, and analysis of customer lifetime value. Financial analytics supports budgeting, risk management, fraud detection, and profitability analysis, while operations and supply chain analytics improve inventory management and process efficiency. Human resource analytics focuses on employee performance, recruitment, and attrition prediction.
Advanced business analytics includes big data, text, and prescriptive analytics. These approaches use large and complex datasets to generate real-time insights and optimize decision-making through simulations and optimization models. Business analytics also addresses ethical issues, such as data privacy and bias. It is applied across various industries, including retail, healthcare, banking, manufacturing, and e-commerce, to enhance competitiveness and performance.