This section defines the three foundational ideas you must know.

1.1 Model

A model is a simplified representation of a real-world system, created to understand its structure, properties, and behavior. The primary purpose is to build a virtual version of a system that we can study and experiment with, allowing us to safely test changes and ask “what if?” questions without impacting the real thing.

…creating a model which represents a system including their properties.

For an analyst, the benefit of a model is the ability to predict the effect of changes on the system. It’s a safe and effective way to explore possibilities.

In short, a model is a representation of a real system.

1.2 Simulation

A simulation is the process of operating a model to analyze how the system it represents behaves over time or space. It is the act of bringing the model to life to study its performance, test theories, and gather insights that would be difficult or impossible to get from the real system.

…the process of using a model to study the performance of a system.

If a model is the blueprint for a factory, the simulation is running a virtual version of that blueprint to watch how products move through the assembly line over the course of a day.

1.3 System

A system is the specific, real-world object or process that you are trying to represent with your model. According to the source text, a system is “the articulate object under definite conditions, which exists in the real world.” This could be anything from an airport terminal or a computer network to a biological process.

Now that we understand the relationship between a real-world system and its representative model, let’s look at the individual components that make up a model.