Real-time Insight Across 20 Depots

The challenge

Management was manually collecting data from 20 depots each week to build reports. The process took 2 full working days and the data was always outdated by the time it was ready.

Our approach

Automated data connections between all locations, a central data warehouse and a real-time management dashboard with automatic weekly reports.

1. Phase 1

   Decide which figures actually matter

   The existing weekly reports had 40+ columns of which management used six in practice. So we started not with technology but with the question: which figures do you actually decide on?

2. Phase 2

   Unlock data from 20 depots

   Not every depot used the same systems or the same definitions. A "delivered shipment" turned out to be counted in three different ways. Before connecting anything, we agreed those definitions: the underestimated part of every data project.

3. Phase 3

   Central warehouse and nightly refresh

   All depots now write into one central environment overnight. Everyone looks at the same numbers, and arguments about whose spreadsheet is correct are a thing of the past.

4. Phase 4

   Dashboards per role

   The CEO sees four key figures, the depot manager sees their own site against the average, the operations lead sees exceptions. Weekly reports go out automatically every Monday morning.

The results

• 2 working days per week saved on reporting
• Data always up to date instead of 5 days old
• €65,000 in annual cost savings
• Management makes decisions 40% faster

Frequently asked questions

Do all sites need to use the same software?

No. The data warehouse pulls from different source systems. What does need to match are the definitions: all sites must mean the same thing by the same term.

Is this real-time or daily?

A nightly refresh in this case, which is more than enough for management decisions. Real-time is possible but more expensive and rarely needed outside operational monitoring.

Which tools do you use for this?

Usually Power BI or Looker Studio on top of a structured database layer. The choice depends on what is already in place and what the team is comfortable with.

What does a data project cost for an SME?

It depends heavily on the number of source systems and data quality. We always produce a cost estimate with expected payback before starting.