We discuss data production rates and their impact on the performance of scientific applications using parallel computers. On one hand, too high rates of data production can be overwhelming, exceeding logistical capacities for transfer, storage and analysis. On the other hand, the rate limiting step in a computationally-based study should be the human-guided analysis, not the calculation. We present performance data for a biomolecular simulation of the enzyme, acetylcholinesterase, which uses the parallel molecular dynamics program EulerGROMOS. The actual production rates are compared against a typical time frame for results analysis where we show that the rate limiting step is the simulation, and that to overcome this will require improved output rates.