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 pr
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Run the capacity-planner skill on this input:
$ARGUMENTS
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}.
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.
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).
Never plan to 100% utilization. Reinertsen 2009: utilization >80% in knowledge work destroys throughput via queueing.
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.