We show you where margin leaks, how much is recoverable, and the exact levers to get it back — from one data export, in your browser, in two weeks.
An on-plan top line is easy to mistake for a healthy one — the revenue number can’t tell you whether volume is really growing or just price, whether margin is keeping pace with cost, or whether discounts still track account size. The diagnostic answers those, and sizes what’s worth fixing.
Figures from a recent diagnostic · anonymized €213M industrial book.
Where each step of your commercial engine stands, from at risk to strong — a verdict, not a data dump.
Every recovery lever quantified and sequenced — quick wins first.
Named accounts and SKUs, ready for the sales conversation — not themes.
Runs in your browser on one export. Nothing is uploaded or stored.
Size-fair pricing reallocates the same discount pool by account size — the biggest accounts earn the deepest prices, the smallest earn the premium. Then it flags every account priced like a giant that isn’t.
The diagnostic runs on a working tool, not on spreadsheets and hand-built slides. These are its screens, on the same anonymized €213M book — every number computed from the transaction lines, none of it typed in.
Each card is one type from a fixed catalogue of 38 — its figures read from your data, the euro it is worth, what it means and the move it points to. Ranked by severity, then by euro.
Plan margin to actual in four effects — volume, mix, price and cost — then by territory and by category. The pieces add up to the gap exactly, so the discussion starts from what moved, not from who missed.
Trend, seasonal run-out and plan delivered, each named with the assumption it makes and read as a cumulative gap to last year and to plan. The room between them is the uncertainty.
Set what the business can actually do: every lever is sized from the real book, and the bridge shows where the year lands against plan. Save a scenario and compare it with the next, lever by lever.
Every activity freezes the potential it works on, and every new export measures it again. Progress is what the data shows — not what someone reported.
Revenue, margin, forecast and plan attainment against its peers; the six steps of commercial health with the rule behind every light; the findings that fire on that one account.
Live screens — anonymized €213M industrial book. Your team keeps the tool after the diagnostic.
No reformatting, no copy-paste into slides. The diagnostic exports itself — cover, health scorecard, the € at stake, the size-fair analysis, the roadmap — as an editable PowerPoint, sized and captioned, ready to present.
⤓ Export → PowerPoint · or PDFAn actual export — anonymized €213M industrial book. Charts stay editable; every figure traces to a transaction.
The engine doesn’t leave when the audit ends. Start with the two-week diagnostic — then keep it as an ongoing subscription your commercial team runs itself, refreshed on every new export and ready before every decision.
Pull any account’s size-fair position and pricing index in seconds — walk in knowing exactly where the discount should land.
Refresh on the latest export: the health monitor, the forecast and every planned activity are measured again — see the recovered margin actually land.
Turn the size-fair line into policy — flag off-line discounts before they’re signed, not after.
One click regenerates the board-ready deck each quarter — no scramble before the QBR.
No IT project, no data warehouse — the engine runs in your browser and hands back a board-ready deck.
Trailing twelve months of invoice lines, costs and customers. That’s the whole ask.
Pricing, mix, retention, the size-fair reshuffle and the buy side — all from the one export.
The health monitor, the € at stake, prioritized measures and a roadmap — plus the live tool to keep.
No black box — every figure traces to a transaction line.
Runs in your browser; your data never leaves the building.
Two weeks from export to a board-ready readout.
Derived from your data, not a template — any commercial book.
See it on a live example, then on your own data — before you commit to anything.