Supply chain and logistics generate massive data flows: stocks, transports, supplier orders, deliveries, returns. Apache Superset is an excellent tool to steer these flows in a unified way, with a modern data-driven stack. This guide details essential dashboards in 2026.
1. Why Superset for supply chain?
- Multi-source: ERP, WMS, TMS, carriers, IoT sensors;
- Massive volumes: supply chain events in millions of rows/day;
- Real time: operational dashboards that refresh;
- Cost: no per-user license, unlike proprietary logistics tools.
If you want a supply-chain-ready instance, TVL Managed Superset offers preconfigured templates.
2. Dashboard 1 — Stocks and inventories
- Stock level per SKU, warehouse;
- Days of remaining coverage;
- SKUs in imminent stockout (alert);
- Identified overstocks (obsolescence risks);
- Total stock valuation.
3. Dashboard 2 — Transport and shipments
- Shipment volume / day / carrier;
- Average cost per package;
- Average delivery time;
- Transport incident rate;
- Geographic delivery map.
4. Dashboard 3 — OTIF (On Time In Full)
The key supply chain KPI: percentage of orders delivered on time and complete.
- Global OTIF and per customer segment;
- OT (on time) vs IF (in full) breakdown;
- Top 10 SKUs in stockout having broken OTIF;
- Month-over-month evolution;
- Per B2B customer OTIF target.
5. Dashboard 4 — Forecasting and procurement
- Historical demand vs actual (forecast error);
- Supplier service rate;
- Average lead time per supplier;
- Supplier concentration (risk);
- Average procurement cycle.
This configuration is applied by default on TVL Managed Superset, which follows community best practices.
6. Dashboard 5 — Returns and reverse logistics
- Return rate per category;
- Top reasons (defective, wrong SKU, doesn't match);
- Average refund time;
- Total reverse logistics cost;
- SKUs with high return rate (to investigate).
7. Supply chain KPIs
| KPI | Formula | Target |
|---|---|---|
| OTIF | Orders delivered on time + complete / total | > 95% |
| Inventory turnover | COGS / average stock | 6-12 (varies) |
| Days of inventory | 365 / inventory turnover | 30-60 days |
| Order fill rate | Complete orders / total | > 98% |
| Forecast accuracy | 1 − ABS(forecast − actual) / actual | > 80% |
| Return rate | Returns / total shipments | < 5% (e-commerce) |
8. Typical data stack
- ERP: SAP, Oracle, NetSuite, Cegid → real-time replication;
- WMS: Manhattan, Reflex, stock events;
- TMS: Shippeo, Project44, transport events;
- Warehouse: Snowflake / BigQuery / ClickHouse;
- Superset connected read-only for dashboards.
9. Common pitfalls
- Daily batch ERP data: too late for operational steering;
- SKU repositories not aligned between WMS and ERP;
- OTIF definitions varying across teams;
- No upstream Master Data Management: inconsistent dashboards.
10. Conclusion
Apache Superset for supply chain is a structuring investment for mid-cap manufacturing or e-commerce companies wanting data-driven steering. The condition is to have a solid upstream ERP/WMS/TMS integration layer (Fivetran, Airbyte) before building dashboards.
Want the benefits of Apache Superset without the friction of installation and maintenance? Deploy your instance in 3 clicks with TVL Managed Superset, hosted in Europe (OVHcloud, Roubaix, France).
For more: e-commerce dashboards, finance BI, real-time IoT.