This paper examines whether there is room for the improvement of farm program decisions through the incorporation of mathematical optimization in the practical planning process. Probing the potential for improvement, we investigate the cases of four German cash crop farms over the last six years. The formal planning approach includes a systematic time series analysis of farmspecific single gross margins and a stochastic optimization model. In order to avoid solutions that simply exceed the farmer's risk tolerance, the apparently accepted variance of the observed program's total gross margin which represents an observable reflection of the individual farmer's risk attitude is used as an upper bound in the optimization. For each of the 24 planning occasions, the formal model is used in a quasi ex-ante approach that provides optimized alternative programs. The total gross margins that could have been realized if the formally optimized programs had been implemented are then ex-post compared to those that were actually realized. We find that the farmers could have increased their total gross margins significantly if - instead of using simple routines and rules of thumb - they had used the more sophisticated formal planning model. However, we also find that the superiority of formalized planning approaches depends on the quality of statistical analysis and the resulting forecasting model. Using our approach for practical decision support implies that farmers first specify their "own" production programs without the formal planning aid. Then, an alternative program can be provided which leads to superior expected total gross margins without exceeding the farmer's accepted total gross margin variance.