Risk-Adjusted Scenarios
What Are Risk Levels?
Every task in Lineo-PM has an associated risk level — a qualitative or quantitative indicator of how uncertain the task’s duration is. A low-risk task is one you are highly confident about; a high-risk task is one where the actual effort could be significantly more (or less) than estimated.
Risk levels are the primary input that feed the Monte Carlo simulation engine. They define the width of the probability distribution from which task durations are sampled during each simulation iteration.
How Risk Levels Feed Into Simulations
When a simulation runs, each task’s duration is not taken as a fixed value. Instead, the engine samples from a triangular distribution defined by three parameters derived from the task’s risk level: a minimum, a most-likely (baseline), and a maximum duration.
The risk level controls how asymmetric and wide that triangle is — a low-risk task has a narrow, nearly symmetric distribution, while a high-risk task has a wider range skewed toward longer durations.
Note: Per-task risk level variance (low / medium / high) and per-task slip probability will be exposed as direct inputs in a future release. The current model uses the triangular distribution as its sampling mechanism.
Building Risk-Adjusted Scenarios
A risk-adjusted scenario is a scenario in which you have deliberately modeled a pessimistic or conservative risk profile. This is useful for:
- Stress-testing your plan — “What does delivery look like if every high-risk task runs long?”
- Stakeholder communication — presenting a range of outcomes with explicit assumptions
- Contingency planning — identifying the worst-case delivery date before it becomes a surprise
To build a risk-adjusted scenario:
- Select pessimistic risk level (P80, P90, or P99) in dropdown named “Create risk-adjusted scenario”
- Lineo creates a new scenario with the same tasks and dependencies as the baseline, but with risk levels adjusted to reflect the selected confidence level
Interpreting the Risk-Adjusted Results
After the engine runs, a results panel shows two tabs: Task Shifts and Original Monte Carlo.
Task Shifts
The Task Shifts table shows exactly what the engine did to each task and why:
| Column | Meaning |
|---|---|
| Task | Task name |
| Orig dates | Baseline start → end dates |
| New dates | Adjusted start → end dates in the risk scenario |
| Buffer | Calendar days of buffer added to this task’s duration |
| CI | Critical Index — how often this task appeared on the critical path across all simulation runs (higher = more dangerous) |
| σ | Duration uncertainty in days (standard deviation of the triangular sample distribution) |
| End Δ | How many days later the task ends compared to the baseline |
| Reason | Plain-language explanation of why (or why not) a buffer was applied |
Tasks with no schedule shift are shown at reduced opacity — they were evaluated but did not require adjustment.
Original Monte Carlo
The second tab shows the Monte Carlo analysis that was run on the original baseline before any risk adjustment. This gives you the full picture: slip probability, delay distribution histogram, percentiles (P50/P75/P90/P99), and the critical index ranking for each task.
When you compare a risk-adjusted scenario to the baseline, focus on:
- How slip probability changes — does the adjusted risk profile push you above an acceptable threshold?
- Which tasks now carry the highest per-task risk — these are your candidates for mitigation
- Critical index shifts — do different tasks become structurally critical under the higher-risk assumptions?
Risk-adjusted scenarios give you the information you need to decide whether to add resources, cut scope, or adjust the schedule before uncertainty materializes into delay.