Mercy Healthcare Uses SAP Analytics for Nurse Scheduling Optimization

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Mercy Healthcare Uses SAP Analytics for Nurse Scheduling Optimization

Case study showing how Mercy reduced nurse hour leakage and saved $4.3M in contingent labor using SAP HANA, BusinessObjects BI, and Predictive Analytics.

Published

June 4, 2026

Read time

3 min read

Source

SAP

Mercy, a large Midwest Catholic health system, implemented SAP HANA, BusinessObjects Business Intelligence, and Predictive Analytics to gain enterprise visibility into nurse scheduling and capacity utilization. The solution enabled managers to identify leakage risks 90 days in advance and redirect full-time nursing resources, eliminating reliance on agency staff. Results included $4.3 million in first-year savings, improved schedule predictability for 44,000 employees, and better alignment of care delivery across 40 hospitals and clinics.

Key takeaways

SAP Predictive Analytics identified nurse hour leakage risks with 90-day lead time

$4.3 million saved in agency labor costs within nine months

Enterprise-wide capacity view replaced manual report collation across hospitals and clinics

Predictable schedules improved nurse satisfaction and reduced contingent staffing needs

Resource forecasting by type, location, and cost supports service expansion

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