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Case study · Supply chain
Multi-tier supplier risk before disruption hits the P&L
A global industrial manufacturer unified supplier telemetry, lead-time forecasts, and alert routing across 140+ nodes.
- Industry
- Industrial manufacturing
- Profile
- Global OEM · $2.4B revenue
- Timeline
- Live in 52 days · Snowflake + SAP
85%
forecast accuracy
11d
earlier warnings
$3.1M
inventory savings
Summary
Operations teams were discovering supplier stress a week too late — after expedite fees and line-down events were already booked. Predicta ranked supplier failure risk daily and pushed executive-ready narratives to planners.
The challenge
Forecasting lived in forty regional spreadsheets. Inbound OTIF, customs dwell, and tier-2 capacity signals never met in one model. When a Southeast Asia packaging vendor slipped, planners learned from customer chargebacks — not from upstream telemetry.
What we deployed
- 01Ingested SAP IBP purchase orders, carrier EDI events, and Snowflake feature store history without replacing the ERP workflow.
- 02Deployed tier-level anomaly models tuned for volatile lead times — not smoothed monthly averages.
- 03Routed ranked risk signals to category managers with scenario libraries (single-source loss, port congestion, FX shock).
- 04Published weekly executive briefs with confidence bands instead of dashboard sprawl.
SnowflakeSAP IBPPredicta streaming alertsSlack + PagerDuty
Outcomes
- Forecast accuracy on critical SKUs improved from 68% to 85% within one planning cycle.
- Average disruption warning moved 11 days earlier versus the prior manual process.
- Inventory carrying cost down $3.1M annualized in the first two quarters after go-live.