What kind of process do you want to simulate? What does each trial look like? What are the choices of each trial?
It is fairly easy to do simulations of random distributions (even ones in the Bayesian framework), but the key thing to establish is what the qualitative aspects of the process include so then we can move to the modelling and quantitative processes.
For example you are talking about redundancies and you can assign for example a Bernoulli distribution to each (true/false distribution), however some things to think about include who is getting made redundant (department, what they do, experience level, how old they are [yes this is an issue], how high nn the food chain, etc) and also if redundancies have effects on other redundancies or people leaving.
When you get mass layoffs, this will affect things in ways that have spill over effects: if a tonne of people are laid off you might get people that suddenly becoming a lot more willing to get a severence package and you may even get people that think about quitting altogether even if they don't get one.
If morale is low and people think the ship is sinking, then some will go for the life boats. Sometimes if key people leave, others will follow them.
These are the kinds of things you need to think about because it's these things that will help you come up with a better model and although all models aren't really correct, some are more useful.