#2 (EN): Why Big IT Projects Often Fail

In this episode, Nova and Daniel discuss why large IT projects so often become later, more expensive, or harder than originally planned.

Daniel breaks the problem down into three root causes:

- mathematics: communication paths, Brooks' Law, and structurally unreliable estimates

- politics: underestimated business cases, sunk cost, and stakeholder interests that are never fully synchronized

- human behavior under complexity: blame games, unclear ownership, and agile theater

Takeaways for IT leaders:

- avoid major projects where manageable, iterative goals are possible

- if a major project is unavoidable, start with honest numbers from day one

- define ownership clearly, in writing, even when it feels uncomfortable

- measure success not only by budget, time, and scope, but by business value, stability, operational simplicity, and user adoption

The episode closes with a look ahead: how AI could help organizations analyze complex projects more honestly and identify risky patterns much earlier.

Me, Myself & IT Leadership. Techie. Leader. Human.