Monte Carlo Enhancement via Simulation Decomposition: A “Must-Have” Inclusion for Many Disciplines

This paper was about making SimDec usable. After the first applications, the question became practical: how do we turn the idea into a clean, repeatable visualization algorithm that anyone can implement? Here we streamlined the SimDec procedure, formalized the step-by-step decomposition logic, and built an Excel-based implementation that makes the method accessible without specialized software. The Excel template is downloadable here, and the video tutorial is available. Note: The Excel template does not compute sensitivity indices.

The paper demonstrates how simulation decomposition enhances standard Monte Carlo analysis across geology, business, and environmental science. Instead of running multiple separate scenarios, the algorithm records input states during a single simulation and produces a stacked, color-coded distribution that reveals which multi-variable combinations drive outcomes. The contribution is methodological: SimDec becomes a lightweight, generalizable visualization layer that can be appended to virtually any Monte Carlo model with negligible computational overhead — and immediately improves how decision-makers see uncertainty.