Finance dashboard

A year late is not a number.
It's a guess.

The dashboard now refreshes 48 times a day.

A retailer on a prime high-street location only saw his figures once the books were closed. By then there was nothing left to steer. This is what changed when the data went live.

The situation

Deciding on instinct, twelve months too late.

Before

  • Figures arrived once a year, through the accountant
  • No way to correct course while the year was running
  • No view of which costs were quietly climbing
  • Decisions made on gut feeling, with the stress that comes with it

Now

  • Live figures down to the day and the individual invoice
  • Deviations surface within the day, not after the year
  • Cost per category and per supplier in plain view
  • Decisions backed by benchmark data
Under the bonnet

From ERP to alert, without anyone touching it.

No exports, no side spreadsheet, no copy-paste. The chain runs itself, 48 times a day.

ERPInvoices and bookings
ETLPulled 48 times a day
Data modelFive years of history
AlertsSignal past 20% drift
48×refreshed per day
5 yrsfilterable history
>20%drift fires an alert
Invoicedeepest level of detail

Figures taken from the case itself, no estimates.

The breakthrough

The numbers showed an asset, not a problem.

Gross margin was stable and better than the benchmark. The problem was never the selling. It was the cost.

Finding from the first full analysis
FirstBring OPEX down

Renegotiate the rent, rework the staffing structure, tidy the internal setup. Benchmark data on the table as the argument.

SecondPut the margin to work

Reinvest in purchasing volume. A simulation showed higher purchasing feeding straight through to revenue and gross profit.

Free startup phase

Phase one cost this client nothing.

Listening, pulling the data, building a working prototype. Only then do you decide whether we go on.

Ask for your prototype
Illustrated · finance dashboard caseERP → ETL → data model → Power BI