Using Machine Learning and Business Intelligence Combining for Building Reliable Demand Forecasting Models

Abstract

Machine learning and business intelligence in combination make for very robust demand forecasting models. Based on historical data, machine learning identifies complex patterns, and with business intelligence, it helps transform this data into meaningful insights. This allows for making accurate predictions, optimizing inventories, improving planning, and making better decisions. The research is conducted to explore the usage of business intelligence (BI) tools and machine learning models to enhance the accuracy of demand forecasting, by analyzing the impact of sales, marketing spends, promotions, price, and customer traffic from 2014 to 2023. The research was done using secondary data sourced from industry reports, where the results showed strong correlations between sales, customer traffic, and marketing spend. This clearly indicates that using BI tools together with machine learning has better implications for decision-making, thus giving accurate forecasting models that help the business.