• A model is just a series of calculations that abstractly represent some systems in the real world. We use models all the time.
• We may work out the routes we could take to get to work at a specific time of the day. We use past data to make predictions about what we can expect in the future in a given set of circumstances.
• As the volume of data and the number of variables increase, the computational task would increase.
• Powerful models aim to forecast inherently unpredictable events and make use of machine learning to look for patterns in the data that would otherwise be missed.

You can never accurately predict what's going to happen. Some efforts come close.

For example, models looking at the weather can achieve more than 90% accuracy. But crises are about change, and a model working from historical data may miss a dramatic and new change.