Prioritising automation investment
Identifies activities with the strongest payback potential, supported by estimated hours and costs released. Provides a roadmap that makes competing automation opportunities easier to compare.
— Operations & Process
Process automation assessment
Scores every activity on repetition, rule clarity, judgement and exception rate to assign an execution mode — AI, automation, tooling or human — with the hours and cost released calculated from your own numbers.
- Operations & Process
- Traceable reasoning
- Runs anywhere
2 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- Activity inventory with responsibilities and supporting systems
- Output
- Scored activity inventory covering repetition, rule clarity, input structure, judgement, exceptions, system access and error consequences
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2 weeks per run
— USE CASES
What people use Process automation assessment for
Choosing the right approach
Distinguishes activities suited to AI assistance, AI-led execution, workflow tooling, rules-based automation or continued human delivery. Grounds each recommendation in the activity’s requirements and constraints.
Assessing operational risk
Examines judgement requirements, exception rates, system access and the consequences of error. Defines candidate-specific safeguards to clarify where controls and human oversight are needed.
Building the investment case
Connects automation recommendations to the organisation’s own operating figures. Provides a scored activity assessment and quantified savings estimates to support funding and prioritisation discussions.
What it works from
- Activity inventory with responsibilities and supporting systems
- Activity volumes and time per instance
- Labour costs and relevant implementation cost assumptions
- Exception rates and judgement requirements by activity conceptually covered in the assessment criteria
What you get back
- Scored activity inventory covering repetition, rule clarity, input structure, judgement, exceptions, system access and error consequences
- Recommended execution approach for each activity
- Estimated hours and costs released
- Automation roadmap prioritised by payback
— HOW IT BEHAVES
How Process automation assessment 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.
Each process step enriched in place
Derived columns are added row by row, keeping your source data and the judgement about each process step side by side.
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
Automation decisions often favour visible inefficiencies without accounting for judgement, exceptions, system constraints or the consequences of error. In practice it shows up as prioritising automation investment: identifies activities with the strongest payback potential, supported by estimated hours and costs released. Provides a roadmap that makes competing automation opportunities easier to compare. It is the kind of work that decides whether a recommendation survives scrutiny — and the kind that quietly eats 2 weeks of senior time whenever it comes round.
How this Skill produces it
As a Skill, the work is already sequenced. You bring the evidence, and the run produces scored activity inventory covering repetition, rule clarity, input structure, judgement, exceptions, system access and error consequences plus recommended execution approach for each activity. 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. Net effect: 2 weeks down to ~25 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Who it's for
- Operations and continuous improvement leads
- Transformation and automation teams
- Service delivery and shared services managers
- Consultants running process diagnostics
Run it in Skillsize — or export it anywhere
Process automation assessment 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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