We investigated data compression algorithms to boost science data return from high-data-volume instruments on planetary missions, particularly outer solar system missions where every bit of data represents an engineering triumph of over severe constraints on mass (limiting antenna size) and power (limiting signal strength). We developed a methodology to (1) investigate algorithms to improve compression and (2) to work with the science teams to evaluate the effects on the science. Our algorithm for compressing the Cassini Radio Plasma Wave Science (RPWS) data achieved a factor of 5 improvement in data compression (relative to what the RPWS team was using), and our algorithm for the Cassini Ultraviolet Imaging Spectrograph (UVIS) Saturn data set achieved a much higher factor (∼70). In both cases, the investigators on the science teams who evaluated our results reported that the science goals were not compromised. Our compression algorithm for Imaging Science Subsystem images achieved on average a factor of ∼1.7 improvement in lossless compression compared to the original algorithm. We also evaluated the compression effectiveness of JPL’s Fast Lossless EXtended (FLEX) hyperspectral/multispectral image compressor on Cassini’s Visible and Infrared Mapping Spectrometer data. FLEX lossless compression provides a factor of 2 improvement over the original compression. We also explore a different range of lossy compression, which can achieve an additional factor 2 to 5 depending on the fidelity required. Our findings have implications for the design of future space missions, particularly with respect to antenna size and overall size, weight, and power budgets, by demonstrating strategies to implement better data compression. In addition to improved algorithms, we show that an iterative process involving real-time science team evaluation and feedback to update the onboard compression algorithm is both essential and feasible. We make the case that a spacecraft facility compressor hosting a toolbox of compression algorithms, available to all of the science instruments and supported by a team of compression experts, convey significant benefits. Beyond the obvious benefits of increased science return and faster playback, better data compression enables design trades between antenna size and number of science instruments on the payload.