Optimus GlobalPerspectives on governance, visibility, and capital project delivery.
Every euro of overtime, expediting, and rework gets booked correctly — procurement can explain its variance, engineering can explain its hours, finance can explain where it landed. What nobody can explain is the whole €18,800, because the chain of assumptions and dependencies that made it necessary was never preserved anywhere.
I expected this study to confirm that people struggle with decisions because they lack information. It did not. Almost nobody had the full picture — yet most still felt confident deciding anyway. That gap should make us uncomfortable.
There is a question that rarely gets asked before an AI implementation in a project environment. Not which tool. Not which vendor. Not which use case. The question is simpler — and yet harder: do we actually understand the context we are asking AI to work with?
Many project risks appear sudden only in hindsight. In reality, the warning signs often existed weeks or months earlier — scattered across teams, systems, conversations and decisions that appeared insignificant when viewed individually.
Information existed in both situations. It lived in someone's inbox, in an assumption, in an unspoken expectation. This is not a people problem — it's a visibility architecture problem.
After years across London, Mumbai, and the Netherlands, one pattern kept repeating. Projects rarely struggled due to lack of effort — they struggled because the system wasn't designed for execution.