TinTrust - SNR Analytics Dashboard

🏢 Industry-Specific Failure Rates

Financial

Healthcare

Manufacturing

Retail

📊 Failure Rates by Data Modality CRITICAL

📈 Modality Complexity Ladder

Structured

72% Failure

Image

76% Failure

Text

79% Failure

Geospatial

81% Failure

Time-Series

83% Failure

Graph

89% Failure

Multi-Modal

94% Failure

✅ SNR Impact Metrics

91%

Success Rate with SNR

13%

Industry Average

$12M

Average Loss Prevented

6.2x

ROI Improvement

📋 Data Modality Failure Details

Structured (72%)
Hidden duplications, temporal misalignment

Image (76%)
Inconsistent formats, quality degradation

Text (79%)
Language drift, encoding issues

Geospatial (81%)
Coordinate system conflicts, precision loss

Time-Series (83%)
Missing timestamps, irregular intervals

Graph (89%)
Broken relationships, orphaned nodes

Multi-Modal (94%)
Cross-modal inconsistencies, sync failures

☠️ The Seven Deadly Patterns of AI Failure

1. The $12 Million Assumption

Average Loss: $12M

"Our data is good enough" - 40% inconsistency discovered post-investment

📋 Unity $110M, GE Predix Examples

2. The Expertise Blindspot

Average Loss: $8M

Data scientists validate, ops teams discover production failures

📋 Watson, Tay, Alexa Examples

3. The POC-to-Production Canyon

Average Loss: $6M

94% accuracy in POC, 61% in production - 88% of POCs abandoned

📋 70-88% Industry Failure Rate

4. The Platform Delusion

Average Loss: $8M

Premium platform purchased, data still unusable

📋 Palantir, Databricks Examples

5. The Compliance Time Bomb

Average Loss: $6M + Fines

Regulatory requirements discovered post-deployment

📋 GDPR, FDA, EU AI Act Examples

6. The Executive Dashboard Disaster

Average Loss: $4M

AI-powered insights based on 35% duplicate data

📋 Equifax, Marketing Attribution

7. The Vendor Integration Maze

Average Loss: $5M

Promised APIs don't exist, 6-month rebuild required

📋 Salesforce, ERP AI Examples