Distribution Long-term Forecast Prototype

Forecasted weight 42.8k t +7.4% vs last 12 months

Peak capacity month Nov 5.1k t expected

Forecast confidence 82% Stable historical coverage

Routes at risk 2 Capacity watch required

Monthly weight outlook

Prototype sample data

AI forecast output requires planner review before publish. 80% interval

Route contribution

Next 12 months

Capacity watchlist

Planner queue

Route	Trigger month	Gap	Recommended action	Risk

Forecast explainability

Human-in-the-loop

Sources: SAP shipment history, lane master, open PO signal Data freshness: good

Active lanes10Transport Pulse network source

High-risk lanes3Capacity review required

Forecasted lane volume160.1k tNext 12 months sample

Avg lead-time variance+1.6dDriven by sea corridors

Route network capacity

From Transport Pulse network

Air Sea Road High-risk halo Count = in transit

Map count badges and table rows select the route inspector.Transport Pulse map reference

Selected route

High

Lane capacity matrix

Lead time, capacity, forecast risk

Lane	Mode	Std LT	Actual LT	Variance	Shipments	Forecast weight	Capacity	Risk

SAP shipment history98.4%18-month coverage

Lane master completeness92.1%8 lanes need owner review

Refresh statusGoodLast run 2026-06-17 09:30

Source health

Data readiness

Quality rules

Blocking vs warning

Lane master gaps

Owner queue

Field	Impacted scope	Impact	Owner	Status

Saved scenarios53 published, 2 draft

Latest approvedBase 2026Q3Approved by planner

Largest delta+18%Peak demand stress test

Scenario timeline

Audit trail

Scenario compare

Base vs stress

Scenario history

Versioned forecast snapshots

Scenario	Mode	Demand adj.	Total weight	Routes at risk	Status	Owner

Forecast model configuration

Planner governed

Model approach Training window Default confidence Retrain cadence Publish caveat Feature notes

Governance controls

AI trust

Require planner approvalBlock official snapshot until reviewed. Show confidence bandDisplay uncertainty next to forecast decisions. Record override reasonKeep a visible audit trail for scenario changes. Use data for trainingDisabled until data ownership approval.

Model health thresholds

Monitoring setup

Metric	Target	Warning	Blocking condition	Owner