⚡ LIVE TOOL — DEPLOYED
🔴 LogiRisk —
Supply Chain Risk Monitor
AI-powered dashboard that scores every shipment lane by risk level and flags emerging disruptions 48–72 hours before they escalate — turning reactive firefighting into proactive supply chain management.
1,247
Total Shipments Analysed
2.3 days
Avg Delay (Disrupted Lanes)
67 / 100
Network Risk Score
€42,300
Est. Disruption Cost Avoided
// live dashboard
Risk Analytics Overview
📈 6-Month Rolling Risk Score by Shipping Lane — weekly average
🔴 Disruption Type Breakdown — last 12 months
📊 Delay Days by Origin Port — top 8 ports by volume
▶ Problem
- Port congestion and transit delays cause reactive, costly supply chain disruptions with no early warning system in place.
- Companies only discover delays after goods are already stuck, causing production halts and SLA breaches.
- Delay data exists in carrier portals and freight systems but is never aggregated into a single risk view.
- Risk management is entirely backward-looking — based on incidents that already happened, not what is about to happen.
▶ Solution
- AI pipeline extracts standard operating procedures from historical logistics disruption data using pattern recognition across 1,247 shipment records.
- Each shipment lane is scored 0–100 for risk based on delay frequency, carrier reliability, port congestion index, and disruption type weight.
- Automated alert fires when a lane's rolling 7-day risk score exceeds threshold — 48–72 hours before disruption typically escalates.
- Power BI dashboard provides drill-down by lane, carrier, port, and disruption type with interactive scenario modelling.
▶ Key Findings
- Hamburg–Shanghai lane showed a 34% higher risk score than network average — driven by seasonal port congestion in Q2 and Q3.
- 3 carriers (out of 11 tracked) account for 67% of all delay events, despite handling only 38% of volume.
- Weather-related disruptions are 2.1× more predictable than carrier-caused delays — making them ideal for early-warning automation.
- Lanes with >2 transshipment stops showed 3.4× the delay rate of direct routes — a structural cost hidden in routing decisions.
- Early intervention on flagged shipments reduced average delay from 4.1 days to 1.8 days across 6 months of testing.
// projections
📈 Forecast & Projections
📉 6-Month Forward Risk Score Forecast — solid = historical, dashed = projected
Base scenario: Network risk score is projected to decline from 67 to 54 over the next 6 months as lane-specific mitigation actions are applied to the top 3 high-risk lanes. Hamburg–Shanghai congestion is expected to normalise post-Q3 peak. If no action is taken (pessimistic), the risk score could reach 81 by month 6, with an estimated additional €28,000 in disruption costs. Optimistic scenario assumes carrier contract renegotiation and dual-sourcing on 2 critical lanes, bringing network risk below 45 — a level not seen in 18 months.
// dataset
📊 Raw Dataset
Real data used in this analysis — 50 rows shown. Download full dataset below.
| Shipment ID | Origin Port | Destination Port | Carrier | Sched. Departure | Actual Departure | Delay (Days) | Disruption Type | Risk Score | Status |
|---|
// strategic guidance
💡 Advice for Companies with Similar Challenges
💡 Practical Recommendations
- Invest in predictive risk monitoring rather than reactive firefighting. Even a basic delay-scoring model built on 12 months of historical shipment data can reduce operational disruption costs by 25–40% within the first year of deployment.
- Consolidate your shipment tracking data into a single SQL table before attempting risk analytics. Fragmented carrier portals are the #1 barrier to building effective early-warning systems — the analysis is straightforward once the data is unified.
- Weight your risk score model heavily on carrier on-time performance (40%) and port congestion index (30%). These two variables alone explain approximately 68% of delay variance in standard logistics datasets.
- Build a "tier 1 lane" list — your top 10 lanes by shipment volume or revenue impact — and monitor these daily. Automated alerts on tier 1 lanes deliver the highest ROI at the lowest implementation cost.
⚡ Key Takeaway
The companies that win at supply chain resilience are not the ones with the most complex systems — they are the ones that act on the right signal 48 hours earlier than their competitors. A risk score threshold alert on your 5 most critical lanes is a deployable, high-impact starting point that requires no major infrastructure investment.