B

Geopolitical Risk Supply Chain Checker

3.55

Derivation Chain

Step 1 Iran risk and Strait of Hormuz crisis
→
Step 2 Supply chain risk management for SMEs
→
Step 3 Automatic diagnosis of supply chain vulnerabilities by geopolitical event and alternative suggestions

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

SMEs with 10-50 employees in manufacturing take 3-7 days to identify which raw materials and components in their supply chain pass through the affected region when a geopolitical event like the Middle East crisis occurs. The purchasing manager must individually check with dozens of suppliers, and during this period, they miss the timing for alternative sourcing, incurring late delivery penalties (several million KRW per incident).

Solution

When a company registers its supplier list and raw material origin/transit information, the service automatically identifies affected items and suppliers when a geopolitical event occurs and recommends alternative sourcing options. Key features: (1) automatic supply chain impact report upon detection of geopolitical events, (2) alternative sourcing recommendations by item (based on Korea Customs Service import statistics), (3) risk heatmap dashboard.

Target: Purchasing/SCM managers at SMEs with 10-50 employees that rely on imported raw materials.
Revenue Model: SaaS monthly subscription at 59,000 KRW (approx. $44.25) per account (up to 100 suppliers), additional suppliers at 300 KRW (approx. $0.23) per month each. Emergency reports at 5,000 KRW (approx. $3.75) per report.
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
4.0/5
M Market
3.0/5
R Realizability
3.0/5
V Validation
4.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (70%)

Tech Complexity
29.3/40
Data Availability
20.8/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (58/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
18.0/20
Revenue Signals
9.0/15
Pick-Axe Fit
12.0/15
Solo Buildability
5.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [medium] Frontend [medium] Data Pipeline [low]
Dashboard