A 120-person regional FMCG distributor ran Odoo for eight years. Reports showed stock value; they did not show which lines were quietly tying up cash ahead of the summer peak.
The situation
The operations director managed 2,400 active SKUs across two warehouses. Monthly reviews mixed ERP pivot tables, buyer memory, and supplier promotions. Slow movers were discussed every quarter — but rarely cleared before seasonality shifted demand again.
What ERP data showed — but didn't say
Odoo held complete sales, returns, and on-hand history. Standard inventory reports listed quantities and valuation. What was missing was a ranked decision: which SKUs to stop buying, discount, or return — and in what order — given cover days and declining velocity.
Turning history into an action list
The team connected Odoo read-only and uploaded one structured export for validation. Flowra ingested five years of transactions and produced:
- A stop-buy list for 89 SKUs with rising days-of-supply and falling velocity
- A clear-down list prioritized by cash trapped and salvage risk
- Evidence per SKU: sales trend, cover days, and last movement date
Purchasing stopped reorders on the stop-buy list immediately. Sales ran a targeted promo on the top 40 clear-down lines.
Results
- €240,000 of slow stock reduced within one season
- Reorder meetings dropped from weekly debates to a daily 15-minute action review
- Stockouts on top movers did not increase — velocity tiers separated clearance from core lines
"We were sitting on three months of slow stock we couldn't see in one view. Flowra flagged it in the first analysis — we cleared it before the season ended."
— Operations Director, regional FMCG distributor