Real-life structures and systems can be represented in a mathematical or statistical way. The reasons for modelling include:

• Understanding the inter-relationships of components in the system
• Determining factors or variables that most influence events or components.
• The ability to predict or forecast the long-term behaviour of the system
• The ability to predict how the system responds when changes are made to the factors influencing it.

Once a statistical model has been developed, simulations of the real-life system can be built in an artificial environment. The modeller can construct and test a wide range of scenarios by changing the influential factors. The key advantage of conducting simulations is that the system can be observed under various conditions without risk.

Another application of models is in optimising systems or processes. Data Analysis Australia applies operations research tools such as linear programming and integer programming to determine an optimal solution for a system, given the constraints upon it. Optimisation modelling is widely applied to systems and business processes where the components and constraints of it can be measured.