Monte Carlo Simulation as a Demand Forecasting Tool

Purpose: This article aims to evaluate the effectiveness of Monte Carlo simulation as a tool for demand forecasting.Design/Methodology/Approach: The study analyzes historical data on product sales, fits a theoretical distribution, and then applies Monte Carlo simulation to forecast demand for the next 15 days.Findings: The result of the research shows that Monte Carlo simulation can outperform more straightforward methods such as averaging, particularly in the presence of uncertainty or randomness Practical Implications: The study demonstrates how Monte Carlo simulation can improve demand forecasting accuracy, which is crucial for optimizing various business operations.Originality/Value: This study's novelty lies in demonstrating the practical application of Monte Carlo simulation for demand forecasting and comparing its performance against traditional methods.