You can use MC to compute your intrinsic value +/- variance. For example, instead of using one number for WACC, margin rate, growth rate, etc., you use a range of values (maybe take them from the company's historical record) to model their probability distributions. Then, use MC to sample from those probability distributions to compute a range of intrinsic values.

The variance information can then be used for your portfolio allocation (i.e., bet sizing). Basically applying the idea of Kelly's criterion - place bigger bets (more confidence) on companies with intrinsic values with lower variances.

Interestingly, if you apply this approach, you will basically place bigger bets on non-cyclical and steady "moaty" companies vs. cyclical ones (because cyclical ones will have higher variances in their performance metrics). Also, I find it is a good way to distinguish steady tech companies vs. volatile ones.