Insights Dashboard

Data-driven analysis of 15 failures across 10 years. Patterns, trends, and the expensive lessons behind the numbers.

Total Failures

Documented case studies

Total Losses

$184M

Combined financial impact

Average Loss

$12.3M

Per failure

Time Span

10 years

2016 to 2026

Most Common Failure Patterns

Due Diligence9 failures (60%)

Overconfidence8 failures (53%)

Financial Mismanagement6 failures (40%)

Market Timing5 failures (33%)

Scaling Too Fast5 failures (33%)

Losses by Industry

Technology

$83.0M(5 failures)

Real Estate

$23.0M(1 failure)

Retail

$20.0M(2 failures)

Energy

$18.0M(1 failure)

Manufacturing

$12.0M(1 failure)

Finance

$9.0M(1 failure)

Failures Over Time

2010s

7 failures$124.0M

2020s

8 failures$60.0M

Impact Level Distribution

Level 52 failures (13%)

Level 46 failures (40%)

Level 36 failures (40%)

Level 21 failure (7%)

Level 10 failures (0%)

Most Expensive Failure

The $45M Tech Bubble Overexpansion

$45.0M lost

Led a $45M investment at the height of the dot-com bubble despite partner opposition. Lost everything when the market crashed 6 months later.

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Key Takeaways From The Data

1.Overconfidence and due diligence failures are the top two patterns, appearing in 17 of 15 failures.
2.Technology and Real Estate sectors account for $106.0M in losses—58% of total.
3.8 failures (53%) were catastrophic (Level 4-5), showing how quickly small mistakes can compound.
4.The average loss per failure is $12.3M, but the range is$3.0M to $45.0M— showing how context and timing dramatically impact outcomes.
5.Market timing mistakes cluster in the ( failures), reflecting the dot-com bubble and 2008 financial crisis.