Monte Carlo Simulation as a Demand Forecasting Tool

Bartosz Przysucha, Piotr Bednarczuk, Wlodzimierz Martyniuk, Ewa Golec, Michal Jasienski, Damian Pliszczuk
European Research Studies Journal, Volume XXVIΙ, Special Issue 2, 103-113, 2024
DOI: 10.35808/ersj/3391


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.

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