As HPC systems advance to exascale, communication networks are becoming ever more complex including, e.g., support for in-network processing. While critical in facilitating scalability, we note that this network complexity is rendered ineffectual when there is workload imbalance. The problem we address here is to measure and characterize workload imbalance and to do so in a way that is useful in network design. We characterize five proxy applications where in-network processing is likely to be effective. Our results reveal that on average 45% of the total execution time of these applications is wasted due to workload imbalance and other types of performance variability when running on the Stampede2 compute cluster with up to 3072 processes.