[clairity]

those are great resources. i've also used the crystal ball plugin for excel, which was bought out by oracle a few years ago: https://www.oracle.com/applications/crystalball/

scenario modeling is useful when you have a set of uncertain inputs and you want to estimate the range of possible output values.

the monte carlo part is providing random sets of inputs that conform to the distributions for each input (often estimated as just a normal distribution for each). you run thousands (or more, depending on the margin of error you wish to achieve) of these random input sets to generate the mean, variance and estimated error of the output variable.

in financial modeling, the inputs are typically estimates of future revenue, costs, cost of capital, etc., and NPV (net present value) of the enterprise as the output. sometimes you even include environmental or regulatory uncertainty (as a binomial value) in the model.