Three weeks in your data. An opportunity map you can execute.
One question: where is money being left on the table, and in what order should you go get it.
The audit fits when the numbers exist but don't conclude.
- You suspect promo is destroying margin, but nobody can say by how much. The audit sizes it in €, with the assumption stated in the same sentence.
- Reports multiply, decisions don't. The Monday meeting reviews numbers and ends. We sit in that meeting during the audit. What it should decide becomes part of the map.
- You're about to invest (a BI tool, a data hire, an agency) and want to know what's actually worth building first. The 90-day roadmap ranks it by € return against effort, not by vendor pitch.
Three weeks, one line: data → analysis → decisions.
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Week 1 · The data lands
Access first, opinions later
Access is confirmed before kickoff, so week 1 is spent profiling, not chasing. Every dataset passes the quality gate.
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Week 2 · The analysis
Every candidate opportunity gets sized
Promo, trading, assortment, forecasting: each candidate is quantified as a € range with its driving assumption named.
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Week 3 · The conclusions
The map, the roadmap, the readout
The opportunity map ranks everything by effort against return; the readout ends in decisions with owners and dates.
Four deliverables. One of them is a map of money.
The opportunity map
Your top opportunities, each shipped as a Note (rated, sized as a € range, dated), ranked by effort against return.
The data-maturity scan
One page: which data you can trust, which KPIs disagree between systems, and what to fix first, before anyone builds a dashboard on sand.
The 90-day roadmap
The opportunity map turned into a sequence: what to capture now, what needs a sprint, what to leave alone. Executable with or without us.
The executive readout
45 minutes with your leadership. Findings, decisions, owners, dates. No 80-slide appendix. The analysis is available, not performed.
Two of ten opportunities pay back inside a quarter
Opportunity map: annual € value against effort to capture. Illustrative, from the audit template.
Illustrative · audit template. In your audit, every point carries its source file and assumption.
Fixed price. Credited if we continue.
One fixed fee, agreed before kickoff. Not a day rate. Signed within 30 days of the readout, the full fee is credited against any sprint. If we continue together, the audit was free.
If three weeks in your data turn up nothing worth more than the fee, the readout says exactly that, and you still keep the maturity scan and the roadmap.
Asked before most audits.
What data access do you need?
- Read access to sales, margin and promo data. Exports in xlsx or csv are enough.
- Access is confirmed in writing before kickoff, so the three weeks go to analysis, not to chasing files.
- Personal customer data never appears in a deliverable.
Our data probably isn't clean enough. Is that a problem?
- It's the normal starting point.
- Every dataset passes a quality gate before analysis. The data-maturity scan tells you what to fix first.
- If the data can't support a trustworthy conclusion, we say so.
How much of my team's time does it take?
- About four hours across the three weeks.
- A kickoff, one working session with whoever owns the data, your regular trading meeting and the readout.
- The audit adds decisions, not meetings.
Put your last trading pack on the table.
Thirty minutes tells you whether the audit will pay for itself.