Supplier selection
Rank a field of vendors on a weighted basis instead of on the strongest presentation.
— Procurement & Vendors
Vendor scorecard & rank
Scores vendor responses on quality, cost and risk, computes weighted totals, ranks the field and writes a recommendation with trade-offs stated.
- Procurement & Vendors
- Traceable reasoning
- Runs anywhere
3–4 days → ~15 minutes
For a full population, not a sample
No coding required
- Input
- A table of vendor responses, one row per vendor
- Output
- Scored and ranked vendors with weighted totals
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~3–4 days per run
— USE CASES
What people use Vendor scorecard & rank for
Panel and framework reviews
Re-score an existing supplier panel on the same criteria to see who still earns a place.
Defensible recommendations
Show the weighting and the trade-off behind the recommended vendor.
What it works from
- A table of vendor responses, one row per vendor
- Your criteria and weightings
- Any must-have thresholds
What you get back
- Scored and ranked vendors with weighted totals
- A written recommendation with trade-offs stated
- A derived scorecard you can re-run
— HOW IT BEHAVES
How Vendor scorecard & rank 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.
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.
Why this is expensive by hand
Load a table of vendor responses, one row per vendor. Supplier selection is the typical trigger — rank a field of vendors on a weighted basis instead of on the strongest presentation. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 3–4 days of manual work.
How this Skill produces it
Skillsize turns that work into a Skill: you supply the material, and what comes back is scored and ranked vendors with weighted totals, with a written recommendation with trade-offs stated. 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, 3–4 days 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
- 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
Vendor scorecard & rank 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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