- A single weather delay on one trade quietly pushed back every trade scheduled after it
- Change orders triggered by delays were discovered weeks after the cost had already been incurred
- Static spreadsheets could not account for how one variable affected every other variable downstream
- Weather and supply data fed directly into schedule risk scoring for every active trade
- Downstream delay alerts flagged knock on effects before they reached the critical path
- Project managers kept full control of schedule changes, with the model only flagging risk earlier
The schedule was never wrong on day one. It just had no way of updating itself when reality changed.
Hary Periya
- Every delayed project I have reviewed had a warning sign that showed up weeks before the actual cost did
- Project managers were not missing skill. They were missing visibility into how trades depended on each other
- The fix was never more reporting. It was earlier reporting on the variables that already mattered
- Average project delay across flagged risks dropped meaningfully once issues surfaced earlier
- Costly change orders caught before execution fell significantly compared to the prior year
- Project managers reported far more confidence in schedules they once treated as rough guesses
Project Delays Reduced
0
%
Change Orders Caught Early
0
%