TB: How Big Things Get Done (Flyvbjerg & Gardner)
Core Thesis
Large projects fail predictably and for understandable reasons — primarily bad incentives and optimism bias. Reference class forecasting (using base rates from similar past projects) is a simple, proven, and underused corrective.
Key Takeaways
- Think slow, act fast: invest heavily in planning before committing; execute quickly once committed.
- Reference class forecasting: instead of using your specific project's estimates, look at the distribution of outcomes for similar past projects. Better on biases, better on unknown unknowns, simple and proven.
- Most large project failures can be explained by bad incentives — skin in the game would improve results significantly.
- Private sector projects generally have better outcomes than public sector ones.
- Do the estimates come with intervals? If not, they are not honest estimates.
Mental Models
- Incentives Matter — bad incentives explain most large project failures
- Inversion — think about what makes projects fail, not just what makes them succeed
- Absence Blindness — optimism bias is inability to see the reference class of failures