Will ops break at 10x?

Scenario controls

Projected median time-to-therapy, next 18 months

Queue model: stage utilization ρ drives wait non-linearly (W ∝ ρ/(1−ρ)). The cliff is the point — wait time is fine at 75% utilization and catastrophic at 92%. The dashed line is the one-day brand promise.

Why this matters

Growth is the stated #1 priority, and the brand promise — therapy in ~1 day, not a week — is a queueing promise. At 10x provider growth, the human-in-the-loop review layer is the binding constraint, and headcount planning that looks fine on averages fails on the utilization curve. This model makes the break-point visible 6–9 months before it happens, and prices the two levers (hiring vs. automation) in the same units.

Stack rank: reviewers offset by month 12

Every automation is priced in the only currency the build-vs-hire conversation needs: reviewer headcount it replaces — at months 4, 8, and 12 of your scenario. Because volume compounds at your growth rate, automation appreciates: the same shipped feature offsets more people every month. Hiring doesn't.

Uses the scenario set on the Simulator tab. Clinical-content steps (†) are shown at ramped value — they ship behind a human-review gate with explicit exit criteria, so early offset is discounted by design.

The math, exposed

Two numbers per project, both derived from one measurable input — manual minutes recovered per case: divide by the 22-minute case to get coverage points added; multiply by monthly case volume and divide by effective reviewer capacity to get headcount offset. No weights, no composite score — arithmetic anyone in the room can check.