Enhancing Operational Efficiency: Integrating Machine Learning Predictive Capabilities in Business Intellgence for Informed Decision-Making


  • Feng Wang
  • Joey Aviles




Business intelligence, Big data, Algorithm, Machine learning, Data analysis, System integration.


With the rapid advancement of information technology, business intelligence and data analysis have become integral to the success of modern enterprises. Through the utilization of various computing technologies, organizations can gain a better understanding of their vast amounts of data and optimize their business decisions. Machine learning technology, in particular, has presented significant potential for enterprises. By analyzing historical sales data and relevant factors, machine learning can predict the sales volume of goods. Commonly used algorithms in machine learning for this purpose include regression algorithms and neural network algorithms. By establishing mathematical models, future sales trends can be accurately forecasted. These algorithms have the capability to automatically identify hidden patterns and trends within the data, enabling enterprises to predict demand and adjust their production and supply chain strategies accordingly, thus better meeting market demand. By integrating regression algorithms and neural network algorithms with enterprise data, managers can obtain real-time and precise sales forecasts. These forecast results provide robust support for enterprise decision-making, enabling operators to formulate more informed marketing strategies, optimize inventory management, and make accurate production plans during peak demand periods. Additionally, by analyzing sales data and other relevant information, enterprises can identify key factors that influence sales, such as product characteristics, market trends, and consumer behavior. This deeper understanding of the market and customer needs allows organizations to enhance their competitiveness further. The application of machine learning technology, specifically regression algorithms and neural network algorithms, coupled with comprehensive data analysis, empowers enterprises to make more accurate sales forecasts. These forecasts aid in strategic decision-making, including marketing strategies, inventory management, and production planning, while also enabling businesses to gain valuable insights into market dynamics and customer preferences, ultimately strengthening their competitive advantage.


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How to Cite

Wang, F., & Aviles, J. (2023). Enhancing Operational Efficiency: Integrating Machine Learning Predictive Capabilities in Business Intellgence for Informed Decision-Making. Frontiers in Business, Economics and Management, 9(1), 282–286. https://doi.org/10.54097/fbem.v9i1.8694