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Improving Holistic Business Intelligence with Artificial Intelligence for Demand Forecasting
Badria Sulaiman Alfurhood, Wadi B. Alonazi, K. Arunkumar, S. Santhi, Jamal Fadhil Tawfeq, Tariq Rasheed and Parthasarathy Poovendran
Business Intelligence Model (BIM) plays a vital role in forming a strategy and taking correct data-based steps in a modern generation to achieve a better demand forecasting result. An inevitable resolution support structure that helps the organization conduct data analyses throughout the business process has been considered a significant challenge. The prediction of potential demands for businesses is predicted with the help of artificial intelligence has been introduced in this research. Based on the intelligence technique, demand estimation is considered one of the company’s major decision-making activities focused on Improving Holistic Business Intelligence Model (IHBIM). For predictions of demand, first raw data from the market is gathered, and then potential demand for sales/products is predicted according to requirements using IHBIM. This forecast is based on data obtained from multiple sources. Further, Artificial intelligence conducts data from various modules and calculates the goods/products’ demands regularly, monthly, and quarterly has been integrated into IHBIM. The simulation results show that the accuracy of the demand forecast is non-compromising. Furthermore, the model’s performance is validated by combining the projected results with accurate data and calculating the percentage error.
Keywords: Artificial intelligence, Business Intelligence Model, Demand forecasting, Data analysis