#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.