The estimation methods, such as the multiple variants of kriging, inverse-distance, etc., generate a smooth representation of the mineral deposits. That is, low values are overestimated, whereas high values are underestimated. This smoothing effect has serious adverse effects on the scheduling optimization process that is highly influenced by the connectivity and proportions of high grades, where we make money. The geostatistical simulations, on the other hand, honor the data at their location, reproduces statistics (mean, variance, histograms, variograms, and potentially high-order statistics) of the exploration data. The simulations are equally probable realizations of the mineral deposit and provide a quantitative measure of its spatial uncertainty. Hence, they are improved inputs for the long-term mine planning process. The same simulations also allow for managing the risk of not meeting production targets on KPI-COSMO and enable outputting probabilistic long-term production forecasts for the mineral value chain.