Episode 2 (EN): Why Big IT Projects So Often Fail
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Episode 2 (EN): Why Big IT Projects So Often Fail
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Narrated by:
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By:
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.