High work load, from high inventory levels, impacts unit processing times, but prior operations management studies have found conflicting results regarding direction. Thus, it is difficult to predict inventory’s effects on productivity a priori, inhibiting effective capacity management in high load systems. We categorize load into in-process inventory (congestion) and incoming inventory, decomposing the latter into its levels of bottleneck (BN) pressure and predictability, and quantify the magnitudes and directions of change on processing times. Using data from 283 hospitals, we find (1) high congestion increases a patient’s hospital stay up to 28%, indicating inefficiencies from overloaded resources; (2) a patient stays up to 11.7% longer if there is a high load of incoming low BN pressure patients, consistent with the slowdown associated with “social loafing”; (3) a patient’s stay is up to 10.2% shorter when there is a high incoming load of predictable patients, consistent with workload smoothing
