AI Healthcare Facility Planning
The Problem
“Optimize healthcare facility sites, size, and timing”
Organizations face these key challenges:
1
Fragmented data across clinical demand, payer mix, demographics, and real estate market comps makes site selection and sizing error-prone
2
Long, consultant-heavy feasibility cycles delay land acquisition, entitlements, and lease negotiations—often missing optimal timing
3
High financial downside from mis-sized facilities (overbuilt space, underutilized clinics, parking shortfalls) and from selecting sites with weak access or competitive pressure
Impact When Solved
Feasibility and network planning cycles reduced from 8–12 weeks to 2–4 weeks with automated data ingestion and scenario modeling5–15% reduction in total occupancy cost via optimized footprint, lease-versus-own recommendations, and better site/term selection