capacity-planner

The saved excerpt is a snapshot from review. The external source remains the complete and most current version.

---
name: capacity-planner
description: "Use when an ops leader (Director of CX, Head of Support, VP Ops, Head of BizOps, Head of IT ops, Head of Finance ops) is sizing ops capacity, building a headcount plan, modeling utilization risk, planning Q3 capacity or annual support capacity, or designing CS coverage — and needs Erlang-C queueing math, P90 demand sizing, shrinkage-adjusted FTE, manager-trigger thresholds, and a quarterly hiring sequence with ramp + attrition. Apply when sustained team utilization is above 80% or when the team is growing >50% in 12 months. Run before committing the headcount budget. This is NOT engineering capacity (see vpe-advisor for DORA + cycle time) and NOT strategic 3-year workforce planning (see chro-advisor)."
version: 2.8.0
author: claude-code-skills
license: MIT
tags: [bizops, capacity, headcount, utilization, queueing-theory, ops-planning, little-law, workforce]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---

# capacity-planner

Sizing tool for **ops teams that handle queued work** — Support, CX,
Customer Success, BizOps, IT ops, Finance ops. Built on Erlang-C
queueing theory, Little's Law, and the operational-leadership canon
(Fournier, Larson, Cleveland, Reinertsen). Deterministic, stdlib-only,
no LLM calls.

## Purpose

You are an ops leader sized 15 → 35 with no idea how the 35-person org
will actually behave at peak load. Or you are at 88% utilization and
SLA is starting to slip. Or you have a hiring budget approved and need
to sequence it across four quarters without burning out the existing
team. This skill answers those questions with arithmetic, not vibes.

It produces three artifacts:

1. **Capacity sizing** at 70/80/90% utilization against P50/P90/P99
   demand, with P(SLA breach) at each point and a SAFE/WATCH/AT_RISK/CRITICAL
   risk band.
2. **Utilization health** at the per-member traffic-light level plus a
   team verdict (HEALTHY/SQUEEZED/OVERLOADED/UNBALANCED).
3. **12-month quarterly hiring plan** accounting for ramp curves,
   attrition, QoQ demand growth, and span-of-control manager triggers.

## When to use

- **Annual ops capacity planning** (October-November for the following
  fiscal year).
- **Quarterly re-sizing** if demand changed >15% or attrition spiked.
- **Pre-budget defense** — the math that justifies the headcount ask
  to your CFO.
- **Diagnostic** when an ops team is missing SLA and you need to know
  whether it's a sizing problem, a process problem, or a bottleneck
  problem.
- **M&A / new-segment launch** modeling — sizing a new team or
  combined org.

## Workflow

1. **Intake demand**. Pull P50/P90/P99 daily ticket/case volume from
   your work system (Zendesk, Intercom, JSM, ServiceNow, Salesforce).
   If you only have averages, stop and pull the distribution. Single-
   point demand estimates are the most expensive anti-pattern in ops.
2. **Model throughput**. Run `capacity_modeler.py` with your demand,
   AHT, SLA target, current FTE, and shrinkage. Use `--profile` for
   your function (support / cx / bizops / finance-ops / it-ops). Read
   the 80%-utilization row — that's your sizing point.
3. **Flag utilization risk**. Run `utilization_analyzer.py` against
   your current team's actual utilization data. Anyone >85% sustained
   is a throughput-collapse risk per Reinertsen. Spread >30 percentage
   points across team means UNBALANCED — fix that before hiring.
4. **Sequence hiring**. Run `hiring_sequencer.py` with current FTE,
   target EOY, ramp time, attrition, and growth. It will front-load
   hires (Q1 35%, Q4 15%), apply ramp curves, and trigger a manager
   hire when span of control crosses 7 ICs/manager.
5. **Walk the Forcing-question library** (see below). One question at
   a time. Do not skip ahead. Answers must be written down before
   you commit the plan.

## Scripts

- `scripts/capacity_modeler.py` — Erlang-C sizing with shrinkage
  adjustment and P50/P90/P99 breach probabilities. `--profile`