Proof
/ Healthcare ProvidersData-Driven Demand Forecasting for a Large Hospital System
Business situation
A large hospital system operating under cost-reduction pressure with a D+1 capacity forecast that created frequent mismatches between available capacity and actual demand.
The challenge
Reactive, single-day capacity forecasting led to persistent gaps between demand and supply, increasing operational costs and reducing care quality.
Why it matters
Quantum Rise deployed a library of care demand forecasting algorithms broken down by unit, department, level of care, day of the week, and intraday periods, integrated into the client's shift scheduling management tool.
What Quantum Rise delivered
The QR/OS™ approach in practice
- • New demand planning process and algorithm framework • 17 different forecasting models covering unit profiles, seasonality, and other variables • Supply + demand balancing capability (capacity by shift, vacation, overtime, FTE fluctuations) • Daily integration with shift management system • Bottleneck visibility dashboards
Measurable outcome
+83% demand forecast accuracy with greater bottleneck visibility. 17% cost reduction through optimised planning and scheduling.
Moved the organisation from reactive daily scheduling to proactive, data-driven workforce planning.
What became repeatable
A reusable demand forecasting library for healthcare operations: 17 configurable models covering any combination of unit type, care level, and intraday period.