Prediction vs. Intervention
Why schedule risk does not identify the right recovery action
Forecasting can show that a milestone is at risk. It does not, by itself, tell the team whether adding labor, expediting material, or resequencing work is the response most likely to help under current conditions.
Full article coming soon.
Decision-Making Under Uncertainty
Why adding labor helps in some conditions and hurts in others
The same action can produce different results depending on workface readiness, congestion, and material status. Effective decision support estimates the effect of an action under the conditions that exist now—not on average.
Full article coming soon.
Learning Across Projects
Why repeated work packages create learning opportunities
Work repeated across floors, units, and facilities produces comparable conditions, decisions, and outcomes. That repetition is what allows early estimates on the next project to start better informed.
Full article coming soon.
Technical Perspectives
Why historical intervention data can be misleading
Projects that received extra crews often finished later—because extra crews are assigned to work that is already in trouble. Raw comparisons confuse the condition that triggered the action with the effect of the action itself.
Full article coming soon.
Decision-Making Under Uncertainty
Why uncertainty should be visible in project decisions
A single-number forecast hides the information leaders need most: the range of likely outcomes, the probability of improvement, and the assumptions that could change the answer.
Full article coming soon.
Technical Perspectives
Why field observations can be incomplete or biased
Field reports arrive late, cover part of the work, and reflect what was easiest to observe. Decision support should treat evidence as uncertain rather than assuming the record is complete.
Full article coming soon.