Case Study: Mercy saves $4.3 million in nursing labor costs with SAP predictive analytics

Bringing Both Patients and Caregivers the Best Services with SAP Solutions

Mercy, a large Catholic health system in the U.S. Midwest, faced challenges in optimizing its nurse scheduling to prevent the leakage of full-time nurses' hours, which occurred when available nurses were not assigned work. The organization needed to harness big data to gain oversight and use predictive analytics to adjust resource assignments efficiently. To address this, they turned to vendor SAP for its SAP BusinessObjects Business Intelligence, SAP Predictive Analytics, and SAP Lumira software running on the SAP HANA platform.

By implementing SAP's solutions, Mercy gained an enterprise-wide view of capacity utilization, enabling managers to forecast care needs and create more predictable schedules for nurses. The solution provided deep insight into performance trends and eliminated manual report collation. This resulted in operational efficiencies and significantly improved employee satisfaction. Most notably, SAP's tools helped Mercy save $4.3 million in contingent labor costs within the first nine months, allowing those funds to be redirected toward patient care.

Mercy

Kyle Falkenrath

Director - Labor Strategy Alignment & Governance