The Data Quality Gap

Clinical trials seldom fall short due to a lack of skill, motivation, or technological capability. More often, they struggle because pivotal choices are made prematurely, relying on information that is not strong enough to support effective execution in real-world settings.

Across every stage of clinical development — from protocol planning and feasibility assessments to site selection and participant enrollment — teams are expected to move quickly while navigating increasing complexity. However, the data used to guide these decisions is often siloed, outdated, or not sufficiently validated, limiting teams’ ability to move forward with confidence.

This article explores the growing divide between data availability and data reliability in clinical development. It explains why greater data volume or more sophisticated analytics alone do not guarantee better results, and it identifies the traits shared by teams that consistently make practical, well-informed decisions.

Ultimately, the distinguishing factor is not technology, but decision-ready data: trusted, high-quality insights that provide clear direction and empower teams to turn information into confident, precise action.