Key methodologies such as HTS and combinatorial chemistry have allowed pharmaceutical discovery to focus on identifying promising drug candidates through the use of statistics. Thus, amassing large data sets from large-scale screening campaigns of ever-increasing corporate compound collections was expected to deliver unprecedented success for the pharmaceutical industry. This feature review explores aspects of how the reliance on using numbers to drive discovery has gone awry. Building knowledge equity from the integration of multiple parallel screening assays, workstreams and data sources provides an alternative to driving discovery through statistics. Thus, a more rational approach to creating and inventing new leads and drug opportunities may be pursued.