Description
Optimise staff and resource planning
Key considerations
Upside3
Linked Case Studies
Case Study
Mercy Hospital Fort Smith
Mercy Hospital Fort Smith improves patient flow and throughput in the ER to improves LWBS rates by over 30% using machine learning
Case Study
Hong Kong Metro System
The Hong Kong Metro saves 800,000 hours annually by optimising engineering work scheduling and resource allocation with AI
Case Study
Gold Coast Health
Gold Coast Health saves $3m per annum in operational costs by forecasting patient arrival rates at emergency care using machine learning
Case Study
Aviva
Aviva accelerates from 400 to 10 days post-merger organisational planning and employee data integration with the use of machine learning
Case Study
DM Drugstores
DM drugstores optimises shift planing in retail stores using advanced prediction modelling
Case Study
Natividad Medical Center
Natividad Medical Center reduces time to see doctor by 20% and left without being seen rates by 42% by optimising patient flow and resource allocation in ER
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Source: kaggle.com · Editor: original-sdg