A mid-market wholesaler serving installers and trade counters had SAP Business One and disciplined masters — but buyers still argued from different spreadsheets about what to reorder each week.
The situation
Four buyers covered 1,800 SKUs and 400 key accounts. Service level targets were clear; execution was not. Each buyer maintained private Excel models. Leadership had no single view of aggregate stock risk entering the month.
What ERP data showed — but didn't say
SAP stored receipts, issues, transfers, and pricing history. Analytics dashboards displayed turnover buckets. None of them answered: "If we only process 50 purchase orders this week, which 50 SKUs matter most?"
Turning history into an action list
After a CSV export pilot, the team connected SAP read-only. Flowra normalized movement history and published:
- A SKU risk score combining velocity change, cover, and supplier lead time
- A weekly reorder queue capped to warehouse receiving capacity
- Account-level flags where demand dropped on historically stable lines
Management set thresholds: anything above risk 70 ships to the daily stand-up; 40–70 goes to the weekly buyer block.
Results
- 18% fewer emergency transfers between branches in the first quarter
- Fill rate on A-class SKUs improved 4.2 points without raising overall stock value
- Purchasing cycle time fell from five days of debate to same-day decisions on the ranked list
"The risk score gave our purchasing team a single number to align around. Decision-making went from weekly debates to daily actions."
— Supply Chain Manager, mid-market wholesaler