Census growth simulator

Each month: new census = census + admits, minus discharges. Discharges = discharge rate x census. So census always drifts toward a plateau of admits divided by discharge rate, and growth requires admits to keep rising as census grows.

• Alumni, BD and other admits are grouped in one lever because they are relationship capped and do not scale with ad spend. The default holds them at their January to June average.
• Other admits are the gap between Kipu admits and Salesforce attributed sources. Elevate's gap is about 14 per month and is worth reconciling before large spend decisions.
• Preset ceilings are grounded in demonstrated performance: Base is the best month this year or a funnel fix on existing volume, Stretch adds 25 to 50 percent more spend at current efficiency.
• Elevate and Indiana each show one unusually heavy discharge month 60 to 90 days back. If that month is a data artifact, their true discharge rates sit at the low end of the noted Kipu range.
• The model covers admissions only. Red Ribbon Indiana and Colorado also need capacity, staffing, and licensing headroom before their targets are physically possible.
• Edit baselines opens the numbers behind each facility so you can refresh them when a new month posts. Copy scenario link captures your exact settings in a link you can send. Restore July 2026 data brings back the shipped pulls. Your changes stay in this browser only.