In forest planning, the decision maker chooses for each stand a treatment schedule for a predefined planning period. The choice is based either on optimization calculations or on silvicultural guidelines. Schedules for individual stands are obtained using a growth simulator, where measured stand characteristics such as the basal area, mean diameter, site class and mean height are used as input variables. These characteristics include errors, however, which may lead to incorrect decisions. In this study, the aim is to study the sensitivity of harvest decisions to errors in a dataset of 157 stands. Correct schedules according to silvicultural guidelines were first determined using error-free data. Different amounts of errors were then generated to the stand-specific characteristics, and the treatment schedule was selected again using the erroneous data. The decision was defined as correct, if the type of harvest in these two schedules were similar, and if the timings deviated at maximum ±2 for thinning and ±3 years for clear-cut. The dependency of probability of correct decisions on stand characteristics and the degree of errors was then modelled. The proposed model can be used to determine the required level of measurement accuracy for each characteristics in different kinds of stands, with a given accuracy requirement for the timing of treatments. This information can further be utilized in selecting the most appropriate inventory method.