Case Study: Cleveland Clinic achieves 2–3 years of development time savings and faster, higher-performing predictive models with Wazoku

Cleveland Clinic - Customer Case Study

Cleveland Clinic partnered with InnoCentive to address a practical healthcare analytics challenge: their existing predictive algorithm worked but was too slow for timely clinical decision-making. The Clinic needed to retain predictive accuracy while dramatically improving performance and exploring comparative effectiveness to stay at the forefront of medical technology.

Using InnoCentive’s crowd of over 1,100 solvers, the 157-day challenge produced 20 shortlisted algorithms—each outperforming the Clinic’s internal model and more than half judged “high quality.” Cleveland Clinic estimates the project saved 2–3 years of development time, delivered production-ready solutions immediately, and reduced cost and duplication by pursuing many parallel research approaches.

Cleveland Clinic

Michael Kattan

Quantitative Health Sciences