π΄ FLAGS HIGH RISK SUPPLIERS EARLY
β οΈ Supplier
Risk Scorecard
Power BI scorecard rating 30 suppliers across 5 weighted dimensions on time delivery, lead time variance, quality defect rate, financial stability, and geographic risk. Composite score triggers automatic alerts when any supplier falls below the 60 point safety threshold.
30
Suppliers Scored
7
High Risk (Score <50)
11
Medium Risk (50 70)
12
Low Risk (Score >70)
// scoring model
Risk Dimension Weights
On Time Delivery
25%
Lead Time Variance
20%
Quality Defect Rate
25%
Financial Stability
20%
Geographic Risk
10%
// live scorecard
Supplier Risk Scorecard 30 Suppliers
Filter:
Click a row to see radar chart
| Supplier | Country | Category | OTD % | LT Variance | Defect % | Fin. Stability | Geo Risk | Composite Score | Tier |
|---|
π Composite Risk Score All 30 Suppliers (lower = higher risk)
π Risk Distribution by Dimension avg score per dimension
π Risk Tier by Supplier Country
π Risk Score Trend Top 5 High Risk Suppliers (6 months)
βΆ Problem
- Supplier reliability issues were discovered only after production halts and quality failures reactive firefighting rather than proactive risk management was the norm.
- No standardised supplier scoring framework meant that buyer assessments were subjective, inconsistent, and impossible to compare across categories or regions.
- Geographic concentration risk was invisible: 40% of spend was sourced from suppliers in two countries with elevated political or logistics instability, with no mitigation strategy in place.
- Financial instability in the supply base went unmonitored two suppliers entered administration in 18 months, each causing 6 8 weeks of supply disruption and emergency sourcing costs.
βΆ Solution
- Five dimension composite scoring model: OTD rate (25%), lead time variance (20%), quality defect rate (25%), financial stability indicator (20%), and geographic risk score (10%).
- Data sources: ERP PO/GR records for OTD and lead time, quality system for defect rates, credit agency scores for financial stability, and country risk indices (Euler Hermes) for geo risk.
- Power BI dashboard auto refreshes monthly. Alert fires when composite score drops below 60, or when any single dimension score drops below 40 (red flag threshold).
- Scores are trended over 6 months a declining trajectory triggers a "Watch" flag even if the current score is still in the amber zone, giving buyers early warning before a breach.
βΆ Key Findings
- 7 of 30 suppliers scored below 50 (high risk) 3 of these are sole source suppliers for critical components, representing an unacceptable concentration of risk with no backup identified.
- Quality defect rate is the highest variance dimension: scores range from 92 (excellent) to 18 (critical), indicating that quality management maturity across the supply base is highly inconsistent.
- Financial stability scores have deteriorated in 4 suppliers over the past 6 months all 4 are in the manufacturing sector in Eastern Europe. Proactive dual sourcing has been initiated for two of them.
- Geographic risk accounts for only 10% of the composite score but 3 of the top 7 high risk suppliers would drop from medium to high risk if geo risk weighting were increased to 20%, suggesting this dimension is currently underweighted.
- On time delivery and quality defect rate together explain 73% of the variance in composite score validating the weighting model and confirming these are the right leading indicators.
// projections
π 6 Month Disruption Probability Forecast
π Projected Supply Disruption Probability High Risk Supplier Average (%)
Base scenario: Average disruption probability for the 7 high risk suppliers is projected to remain at 34 38% over the next 6 months without active intervention meaning a statistically likely disruption event in at least 2 3 of those suppliers within the year. With mitigation actions: Implementing dual sourcing for the 3 sole source high risk suppliers and initiating quarterly review calls reduces projected disruption probability to 18 22% below the 25% internal threshold. Geo risk escalation: If political or logistics instability increases in Eastern Europe, projected disruption probability for 4 affected suppliers climbs to 52 58%, requiring emergency buffer stock of 6 8 weeks for critical components.
// dataset
π Raw Dataset
Real data used in this analysis all 30 suppliers shown. Download full dataset below.
| Supplier ID | Supplier Name | Country | Category | OTD % | LT Avg (d) | LT Variance | Defect % | Fin. Risk Score | Geo Risk Score | Composite Score | Risk Tier |
|---|
// strategic guidance
π‘ Advice for Companies with Similar Challenges
π‘ Practical Recommendations
- Build a supplier risk scorecard before your next supplier review cycle. Weighting on time delivery and lead time variance most heavily (40% combined) gives you the fastest signal of deteriorating supplier performance these two metrics are available from ERP data you already have.
- Never rely on a single supplier for a critical component without a qualified backup. Sole source relationships are a business continuity liability. The cost of qualifying a second supplier (typically β¬5,000 15,000 in audit and testing) is always less than the cost of one supply disruption event.
- Score trend matters as much as score level. A supplier at 62 (amber) with 3 consecutive months of decline is more dangerous than one at 58 (amber) with 3 months of improvement. Build trending into your scorecard a declining trajectory should trigger review even before the threshold is breached.
- Share the scorecard with your suppliers annually. Transparency drives improvement suppliers who see their scores relative to peers consistently improve OTD and defect rates within two review cycles. It also signals that you are a sophisticated, data driven buyer worth performing well for.
β‘ Key Takeaway
The most expensive supply chain event is always the one you didn't see coming. A supplier risk scorecard built from data you already have ERP delivery records, quality system defect rates, and a credit score feed costs less than a week of analyst time to build and can prevent supply disruptions worth 10 100Γ that investment. Start with your top 20 suppliers by spend and build from there.