I am using Monte-Carlo simulations in Microsoft Excel to determine optimum reorder points and safety stock levels. I have the demand patterns of the last one year of the product. Using that I can construct a cumulative distribution function of the demand to draw random samples from and construct a table of demand on each day for a whole year.
One problem that I found was that the simulation is based on demand patterns alone. That is, if the company did not forecast at all, then the individual runs of the simulation would generate the demand pattern that they can expect in a year. However, if the company is able to forecast demand with 100% accuracy, then there would be no need to keep a safety stock (or very little of it). Forecast accuracy is something I am not sure how to incorporate in my model. There are formulas for calculating safety stock such as using the Mean Absolute Deviation from the forecasted demand but I would like to develop a simulation model that takes into account forecast accuracy.