Forecasting is the use of past and present data to predict the future. This process is hugely important for strategic thinking in businesses, governments, and other organizations, who use forecasts of market factors like supply and demand as well as macroeconomic trends to guide their future plans and investment decisions.
Forecasts often use a statistical technique called regression analysis, which looks at past trends of two or more variables of interest to see how they are correlated over time. Once these relationships are established, modelers can then create a relatively simple projection for how trends might play out in the future based on expected values of the independent variable. For example, if you make assumptions about the overall growth of the economy, you can predict how that will influence demand for your product.
Of course, the future is full of surprises that can challenge these assumptions. Thus, more sophisticated approaches to forecasting may use the Monte Carlo method or other tools to run many simulations of the future based on an expected range of values for the independent variable. By creating a probabilistic model showing a distribution of expected outcomes, forecasters can use a scenario development process to stimulate thinking across different futures with a goal of creating more robust insights.