The standard methodology of conducting a simulation is universally broken down into five distinct sequential steps designed to guarantee reliability and accuracy. The first step is problem formulation and objective definition, where analysts clearly establish what questions the simulation needs to answer and outline the boundaries of the system. The second step is model conceptualization and data collection, involving gathering empirical data and mapping out the variables, flowchart logic, and mathematical relationships required. The third step is model translation and coding, where the conceptual framework is built inside a chosen software environment or programming language. The fourth step is verification and validation, a rigorous quality-control phase where code execution is checked for bugs and outputs are compared against real-world observations to ensure the model behaves realistically. The fifth and final step is experimentation and analysis, which involves running the validated simulation across multiple scenario variations to generate actionable insights and support strategic decision-making.