The problem
Multi-warehouse operations were planning inventory on last month’s numbers and discovering discrepancies at count time.
The approach
We built a time-series forecasting dashboard integrated with the sales and inventory modules, and a traceability dashboard that follows stock from supplier receipt to customer delivery, both in Python and OWL with Chart.js visualisation and variance alerts.
The outcome
Planners order against a forecast instead of a hunch. Discrepancies surface the day they happen, not at quarter-end. +45% planning accuracy, 60% fewer discrepancies.
Multi-warehouse operations were planning inventory on last month’s numbers and discovering discrepancies at count time.
What we built
- Time-series sales forecasting integrated with sales and inventory modules
- Stock traceability from supplier receipt to customer delivery
- Real-time dashboards in Python and OWL with Chart.js visualisation
- Alerts on variance thresholds
+45%
Inventory planning accuracy
−60%
Stock discrepancies
Outcome
Planners order against a forecast instead of a hunch. Discrepancies surface the day they happen, not at quarter-end.
