Sales and finance quote different revenue
We write shared definitions down. One team counts from the order date, another from the invoice date, a third deducts Allegro returns.
Order in the core records is step one. A common warehouse with dashboards is step two. Running in parallel, software extracts data from paperwork that still turns up as PDFs and scans.
One list of customers, suppliers and products: tax IDs checked against the GUS register and the VAT white list, duplicates merged, rules for adding new entries. Skip this and a warehouse simply displays the mess faster.
Figures from Symfonia, enova365 or Comarch ERP XL, from Allegro, your web shop and Google Ads flow into a single EU-hosted database. Power BI or Looker Studio reports sit on top and show identical numbers whoever opens them.
KSeF has structured domestic invoices, yet foreign supplier invoices, WZ and PZ stock documents, consignment notes and contracts remain. We read those automatically; a colleague just checks and approves.
Projects often start with “we need a dashboard”. A short conversation usually shows the real trouble lies deeper, in one of the places described here.
We write shared definitions down. One team counts from the order date, another from the invoice date, a third deducts Allegro returns.
We clean the records and add rules. “Kowalski sp. j.”, “KOWALSKI SPÓŁKA JAWNA” and an entry with no tax ID count as three separate firms in any report.
We build a warehouse that loads itself. Excel exports and stitching sheets together swallow the financial controller’s time.
We schedule automatic refreshes. When an Allegro listing sells faster than the report arrives, restocking decisions are made blind.
We introduce automatic reading. Someone copies every line of supplier delivery notes and German or Chinese invoices into the system manually.
A dashboard does not fix data; it only makes it look better. A hand-built spreadsheet has one virtue: a person looks at every figure and occasionally spots nonsense. A colourful chart looks professional, so nobody questions it, even when duplicate accounts noticeably inflate the customer count. Data quality is therefore checked right at the start, before the first chart exists.
Phase one covers a single area, usually sales or stock, and a handful of key indicators. Other departments join once the first report is part of daily routine. Everything happens remotely through secure access to your systems.
Together with finance and sales we settle how revenue, margin and marketplace returns are calculated. Skip this and every report gets challenged at its first meeting.
We list the sources: ERP, shop, Allegro, spreadsheets. Each gets an owner, an access method and a note of fields holding personal data for your GDPR records.
The first report is compared against the old Excel file. Every gap gets explained before the automated version reaches the board.
New departments and metrics come on board. With the data model and loading already running, every later report is quicker and cheaper to produce.
If you run on Microsoft 365 and your data comes from an ERP and SQL Server, Power BI usually wins: it models data well and makes permissions easy. Looker Studio plugs straight into Google Ads, GA4 and Sheets, so it suits marketing teams and online shops. You can also use both, with one shared warehouse underneath.
It should not. Extraction runs overnight or in small batches, ideally via an API or a database replica, never as heavy queries during office hours. That is exactly why reports sit on a separate warehouse rather than directly on the Comarch ERP or Symfonia database your whole sales team is using at the same moment.
Inside your Azure or Google Cloud subscription in an EU region or, if you prefer, on a server in your own data centre. A processing agreement is in place and permissions follow job roles: the sales director sees the whole country, a regional rep only their territory and clients. Every time a report is opened, the log records it.
Where records are in decent shape, the first report arrives much sooner, definitions included. With thousands of duplicates, clean-up becomes the bulk of the job. We give a date only after inspecting the database, never at the first meeting.
Tell us which reports are still assembled by hand and where the figures disagree. We will look at the source systems and suggest a starting point.
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