Repeatable client analysis
Run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work.
— Operations & Process
Workload allocation review
Computes hours and cost by role and grade for every activity, identifies work sitting too senior or too junior, and quantifies the hours and cost released by rebalancing it.
- Operations & Process
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- Documents, exports or uploads you already hold
- Output
- A structured, review-ready deliverable
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 weeks per run
— USE CASES
What people use Workload allocation review for
Faster first drafts
Turn raw source material into a working draft in minutes and spend your time on judgement instead of assembly.
Comparable results over time
Produce the same shape of output each cycle so movement is measurable rather than re-argued.
What it works from
- Documents, exports or uploads you already hold
- Your own criteria, framework or house method
What you get back
- A structured, review-ready deliverable
- A traceable record of what informed each conclusion
— HOW IT BEHAVES
How Workload allocation review produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Row-level table processing
Every row of your table is processed on the same basis, however long the table is.
Charted, not just stated
The pattern is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings are written up as a document that reads like professional output rather than raw model text.
Enriched row by row
Each row gains derived columns from the analysis, keeping the source data and the judgement side by side.
Roll-up alongside detail
Detail rows are summarised into the grouped view without losing the underlying lines.
Why this is expensive by hand
In operations & process work, workload allocation review is one of those tasks that looks straightforward until you are three documents deep and the details stop agreeing with each other. In practice it shows up as repeatable client analysis: run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 1–2 weeks of capacity for it.
How this Skill produces it
As a Skill, the work is already sequenced. You bring the evidence, and the run produces a structured, review-ready deliverable plus a traceable record of what informed each conclusion. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. In effect, 1–2 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
- Independent consultants codifying their own methodology
- Strategy and transformation teams standardising delivery
- Internal advisory functions under pressure to produce faster
- Operators who need defensible output, not a one-off chat answer
Run it in Skillsize — or export it anywhere
Workload allocation review 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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