Risk response
Project risk and marginal reduction as the selected task receives buffer.
Schedule sensitivity sandbox
See where one additional day of protective buffer creates the largest marginal reduction in project risk—and whether that protection moves the commitment date.
This is a transparent learning model, not a calibrated risk forecast. It uses a simple CPM network, an exponential risk response, and finite differences to make the “next best buffer day” visible.
Project risk and marginal reduction as the selected task receives buffer.
Higher values indicate more project-risk reduction from the next available buffer day. Tasks at the 10-day limit are excluded.
Solid red links sit on the current critical path; dashed links retain float.
A risk gradient answers a practical question: where would the next day of contingency buy the most reduction in overall exposure?
The model holds baseline CPM weights constant, adds protective buffer to each task’s baseline total float, and approximates a partial derivative with a one-day forward difference.
Task risk = 100 × exp(−(baseline slack + buffer) × coefficient / 2)
Displayed gradient = Project risk(b) − Project risk(b + 1 day)
The mathematical derivative is negative; the interface reports its positive magnitude as risk reduction. Commitment impact is calculated separately by rerunning the dependency network with buffer added to task duration. Risk uses fixed baseline slack and weights; it does not infer new protection from recalculated float. Within this example’s 0–10-day slider limits, the same branch remains critical: Documentation and Training together can use at most 20 of their 22 days of baseline float.
The chart includes a hypothetical next-day reduction at 10 days to show the response curve; allocating an 11th day is outside the controls. Recommendations and rankings include only allocations still available within the limit.
Select a task for the chart, then allocate 0–10 days. Dates below are the recalculated commitment schedule.