Translational failures and replication issues of published research are undermining preclinical research and, if the outcomes are questionable, raise ethical implications over the continued use of animals. Standardization of procedures, environmental conditions, and genetic background has traditionally been proposed as the gold standard approach, as it reduces variability, thereby enhancing sensitivity and supporting reproducibility when the environment is defined precisely. An alternative view is that standardization can identify idiosyncratic effects and hence decrease reproducibility. In support of this alternative view, Voelkl and colleagues present evidence from resampling a large quantity of research data exploring a variety of treatments. They demonstrate that by implementing multi-laboratory experiments with as few as two sites, we can increase reproducibility by embracing variation without increasing the sample size.