Structural decisions with evidence
Show the process step-level basis for a design or headcount decision instead of defending a judgement call.
— Organisation & Workforce
Workforce capacity planner
The scenario model recalculates required FTE, the gap against headcount and utilisation for every row under nine named scenarios — base, P50 / P90 / P95 absence, demand +10% / +20%, a productivity dip, an attrition-adjusted view and a combined downside — and flags every team-period where the gap turns positive.
- Organisation & Workforce
- Traceable reasoning
- Runs anywhere
2–3 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- Org data, role documentation or headcount exports
- Output
- A process step-level view of the end-to-end process with the reasoning attached
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2–3 weeks per run
— USE CASES
What people use Workforce capacity planner for
One standard across the organisation
Apply the same criteria to every part of the end-to-end process, so functions are genuinely comparable.
Re-run after each change
Re-run against updated org data each cycle and see what actually moved.
What it works from
- Org data, role documentation or headcount exports
- Your own design principles or planning assumptions
What you get back
- A process step-level view of the end-to-end process with the reasoning attached
- A roll-up for leadership at the level you report at
— HOW IT BEHAVES
How Workforce capacity planner produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Every row of the end-to-end process
Each row of your export is processed on the same basis, so no process step is skipped however long the table is.
The pattern charted
Movement across the end-to-end process is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings on the end-to-end process are written up as a document that reads like professional output, with each claim tied back to a process step.
Roll-up alongside process step-level detail
Detail rows are summarised into the grouped view of the end-to-end process without losing the underlying process steps.
Why this is expensive by hand
Work on the end-to-end process normally means pulling org data, role documentation and headcount exports together by hand, then applying a standard that only exists in the head of whoever is doing it. In practice it shows up as structural decisions with evidence: show the process step-level basis for a design or headcount decision instead of defending a judgement call. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 2–3 weeks of capacity for it.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; a process step-level view of the end-to-end process with the reasoning attached comes out, alongside a roll-up for leadership at the level you report at. What sits between input and output is the codified method: thresholds, sequencing and the points where a human confirms a call — all of it visible and editable in the Skill. In effect, 2–3 weeks of senior time compresses into ~25 minutes — and the output is comparable across clients, quarters and colleagues instead of shaped by whoever ran it.
Who it's for
- Org design and workforce planning leads
- COOs and functional leaders reshaping teams
- Transformation consultants sizing people impact
- HR business partners supporting redesign
Run it in Skillsize — or export it anywhere
Workforce capacity planner exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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