/cs-capacity-plan

disable-model-invocation: true
description: Model headcount + tooling capacity for ops teams (CX/Support/CS/BizOps/IT ops/Finance ops) using Erlang-C queueing math. Sizes the team around the bottleneck process-mapper found. NOT engineering capacity. Direct invocation of the capacity-planner skill.
argument-hint: "<team + demand intake or path to capacity JSON>"

/cs-capacity-plan — Ops capacity sizing + utilization risk + hiring sequence

Run the `capacity-planner` skill on this input:

**$ARGUMENTS**

Three-tool workflow

1. **`capacity_modeler.py`** — Erlang-C / queueing math: required FTE at 70/80/90% utilization, P(SLA breach) per utilization level, capacity headroom. Industry tuning `--profile {support,cx,bizops,finance-ops,it-ops}`.

2. **`utilization_analyzer.py`** — Red-zone detection per team member: >85% sustained = throughput collapse (Little's Law), <40% = under-loaded or wrong skills, variance >30% = unbalanced. Verdict: HEALTHY / SQUEEZED / OVERLOADED / UNBALANCED.

3. **`hiring_sequencer.py`** — 12-month quarterly hiring plan accounting for ramp curve (50% productive weeks 1-N, 100% after) + attrition + growth. Surfaces "manager trigger" point (span of control >7-8 ICs).

Hard rule

**Never plan to 100% utilization.** Reinertsen 2009: utilization >80% in knowledge work destroys throughput via queueing.

Distinct from

• `c-level-advisor/vpe-advisor` — engineering throughput specifically. Capacity-planner is for non-eng ops teams.
• `c-level-advisor/chro-advisor` — strategic workforce planning. Capacity-planner is tactical sizing.
• `business-operations/skills/process-mapper` (sibling) — finds the bottleneck. Capacity-planner sizes the team around it.
• `project-management/*` — delivery tracking. Capacity-planner is forward sizing.