The sharpening focus on quality management is fueling greater use of standardized metrics to optimize clinical trial performance. Stakeholders are embracing this trend through growing adoption of cloud-based technologies, such as clinical trial management systems (CTMS), source data, and the electronic trial master file (eTMF). The information they generate is flowing into data analytic tools, and with this capability, standardized metrics are gaining mainstream status. But just because data from disparate sources can now be aggregated does not necessarily mean that this information or the resulting metrics are actionable, or can identify risk proactively. That’s why targeted performance metrics that measure the many details of clinical trial operations are essential. And for study startup (SSU) in particular, performance metrics are critical, given that it is one of the most complicated parts of clinical trials and one of the most crucial to meeting site activation timelines and study completion milestones. Yet, its performance scores lag other stages of clinical research.