Short-term mine planning plays a crucial role in determining the destination of all extracted material to align with long-term strategic goals and meet production targets. Compared to other planning horizons, short-term planning benefits from a higher volume of available geological data. However, this advantage is offset by the daily operational challenges posed by the variability of the deposit. Fluctuations in grade, rock type, and geometallurgical performance can significantly affect the achievement of production targets and reduce the expected revenue of the operation. In this study, we analyse the impact of grade uncertainty on a critical step within the grade control workflow: the dig-limit definition. This step incorporates operational constraints related to shovel selectivity to generate a feasible short-term destination plan. While manual methods are commonly employed for this task, several optimisation-based approaches have been proposed to enhance efficiency and accuracy. Using an optimisation model, we demonstrate that grade uncertainty can lead to profit deviations of up to 20 per cent, depending on the scenario, in a real-world case study. Additionally, by evaluating the variability of profit through a deterministic model, we highlight a significant gap between the expected value derived from a traditional grade control workflow and the actual realised profit, particularly in low-grade benches. We also show that a most-probable destination assignment based on the optimal dig-limits outcomes for each grade simulation is virtually identical to the deterministic dig-limit based on the estimated scenario, with no advantages in terms of profit or variability. Our findings underscore the importance of integrating grade uncertainty into short-term planning optimisation models to improve decision-making and maximise operational profitability.