Scoping a cost reduction programme
Builds a sized pipeline of potential savings linked to specific cost reduction levers. Confidence levels and effort estimates help teams judge which opportunities warrant attention.
— Finance & Investment
Aggregates a spend extract by category and supplier, exposes concentration, scores each material line for reducibility, and sizes a savings pipeline with the lever, confidence and effort per opportunity.
2–3 weeks → ~40 minutes
For a full population, not a sample
No coding required
— USE CASES
Builds a sized pipeline of potential savings linked to specific cost reduction levers. Confidence levels and effort estimates help teams judge which opportunities warrant attention.
Highlights where spending is concentrated among suppliers and categories. Provides a clearer basis for examining purchasing patterns and potential commercial leverage.
Identifies anomalies and material cost drivers within the available spend data. Focuses the diagnostic on areas that merit explanation or closer scrutiny.
Provides a structured report that connects the cost base to potential reductions. Makes the estimated scale, confidence and effort of each opportunity visible without presenting potential savings as guaranteed.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Each row of your export is processed on the same basis, so no line item is skipped however long the table is.
Movement across the reporting period in scope is visualised from the computed data, so the trend is legible at a glance.
Findings on the reporting period in scope are written up as a document that reads like professional output, with each claim tied back to a line item.
Derived columns are added row by row, keeping your source data and the judgement about each line item side by side.
Detail rows are summarised into the grouped view of the reporting period in scope without losing the underlying line items.
Cost base reviews often leave advisory teams reconciling fragmented spend data while trying to distinguish genuine savings opportunities from costs that are difficult to change. Scoping a cost reduction programme is the typical trigger — builds a sized pipeline of potential savings linked to specific cost reduction levers. Confidence levels and effort estimates help teams judge which opportunities warrant attention. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 2–3 weeks of manual work.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces cost base diagnostic report plus category and supplier spend breakdowns. 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: 2–3 weeks down to ~40 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Cost Base 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.
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