Skillsize

— Organisation & Workforce

Capacity Map

Compares team capacity with planned demand to show where workloads are sustainable, where pressure is building and which changes could rebalance the load.

  • Organisation & Workforce
  • Traceable reasoning
  • Runs anywhere
Preview methodology

1 week → ~15 minutes

For one complete, review-ready pass

No coding required

Input
Workforce headcount and available hours
Output
Team-by-team capacity and demand comparison
Runs in
Skillsize · ChatGPT · Claude · Copilot
Export
SKILL.md · MCP
Time saved
~1 week per run

— USE CASES

What people use Capacity Map for

Testing a workforce plan

Assesses whether team capacity supports planned demand. Identifies where the figures indicate spare capacity or overload, giving workforce discussions a clear quantitative basis.

Understanding uneven team workloads

Shows how utilisation varies across teams and where allocations create pressure. Highlights options for redistributing work to make better use of available capacity.

Supporting resourcing decisions

Provides a transparent view of capacity gaps and their scale. Helps distinguish pressures that could be addressed through reallocation from those that may require additional resource.

Explaining delivery pressure

Pinpoints teams whose workloads exceed available capacity and shows the calculations behind that assessment. Gives leaders a concrete basis for discussing workload, priorities and delivery commitments.

What it works from

  • Workforce headcount and available hours
  • Team workload and allocation data
  • Existing utilisation figures
  • Planned work and demand requirements

What you get back

  • Team-by-team capacity and demand comparison
  • Utilisation calculations with supporting figures
  • Team capacity classifications: spare, balanced, stretched or overloaded
  • Summary of capacity pinch points and imbalances mechanisms

— HOW IT BEHAVES

How Capacity Map produces its result

The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.

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.

Delivered as a working table

The process steps land as a clean table you can sort, filter or drop straight into the deliverable.

Criteria-based analysis of every process step

Each process step is assessed against explicit criteria you control, so the same standard is applied across the end-to-end process on every run.

Grounded in your own process documentation and run data

The run works from process documentation and run data you supply, so conclusions about the end-to-end process are anchored to your evidence rather than general model knowledge.

Why this is expensive by hand

Workforce plans often show headcount without making clear whether teams have enough time to meet demand. In practice it shows up as testing a workforce plan: assesses whether team capacity supports planned demand. Identifies where the figures indicate spare capacity or overload, giving workforce discussions a clear quantitative basis. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 1 week of capacity for it.

How this Skill produces it

Here the same job runs as a Skill. Your material goes in; team-by-team capacity and demand comparison comes out, alongside utilisation calculations with supporting figures. 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, 1 week of senior time compresses into ~15 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

Capacity Map 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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