Risk Analysis

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Overview

The Risk Analysis page runs Dash360’s unified Monte Carlo engine. From a single set of iterations it produces both a project cost distribution and a project finish-date distribution, driven by two sources of variability:

• Estimating uncertainty: the spread in activity durations and resource-assignment costs, sampled from their Uncertainty Classes.
• Risk events: the risks in the Risk Register, each rolled against its probability and cost or schedule impact.

The page is organized into two cards: Cost and Schedule Uncertainty (the Uncertainty Cascade, where you decide which classes apply where) and Monte Carlo Simulations (where you run, read, save, and compare simulations). URL: /Risk/ScheduleRiskAnalysis/Index

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Video walkthrough

A full tour of the Risk Analysis page: setting the uncertainty cascade, running a simulation, reading the cost and schedule distributions, the contingency decompositions, sensitivity charts, and comparing saved runs.

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Prerequisites

• A project must be selected.
• Uncertainty Classes should be defined for the project. See Uncertainty Classes.
• For risk-driven results, the project’s Risk Register should contain risks with probabilities and Risk (pre-response) and Mitigated Risk (post-response) impacts.

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Uncertainty Cascade

The Cost and Schedule Uncertainty card (the Uncertainty Cascade) decides which Uncertainty Class applies to each part of the project. It resolves top down: a class set at the Project level applies everywhere unless a WBS overrides it, which a Work Package can override, which an Activity or Resource Assignment can override. This lets you set a sensible project-wide default and refine only where needed. The cascade is shown as a tree (Project, WBS, Work Package, Activity, Resource Assignment), expanded fully by default so you can see the whole structure at once. Each node has a Cost Uncertainty and a Schedule Uncertainty column showing its effective class and where that class came from (set directly, or inherited from a parent), plus a Cost Overlay column on the rows that carry that flag. Each class cell is a slider: a lock toggle on the left, then an OFF stop, then the Uncertainty Classes as color-graded stops (conservative on the left, aggressive on the right). Drag the thumb or click a stop to set the class.

• Set a class on a node to override what it inherits. The override cascades to that node’s children unless they have their own override.
• Lock / Unlock a node with the lock icon: a locked row holds an explicit class; unlocking clears the override and returns the row to inheriting from its parent (inherited rows show in italics).
• OFF sets an explicit no-uncertainty (deterministic single point) class. Unlike unlocking, OFF is itself an explicit assignment that stops inheritance and cascades a deterministic value to descendants; use the lock icon, not OFF, when you want to go back to inheriting the parent’s class.
• Cost Overlay column (Activity and Resource Assignment rows): whether that item’s cost scales with its sampled duration. See The Cost Overlay column below.
• Correlation column (Activity rows): link activities so their duration draws move together in the simulation (Activity-to-Activity correlation). This is a Pro feature. See Correlation and Activity Mapping.
• Reports column: once a simulation has been run or loaded, per-row icons open that node’s Cost Monte Carlo, Schedule Monte Carlo, and Schedule Delay Drivers charts. See Per-node reports (Reports column) for details.

The cascade is resolved at simulation time, so changes take effect on the next run.

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The Cost Overlay column

Cost Overlay ties a cost to a duration: when it is on, an iteration that samples a longer duration also scales that work’s cost. It is only physically true for level-of-effort work (labor, support staff, equipment rental); a firm-fixed-price subcontract or a purchased material costs the same however long the schedule runs. See Uncertainty and Cost Overlay for the full model and the arithmetic. The column shows one clock icon per row, and it appears only on the two row types that carry the flag. Project, WBS, and Work Package rows are blank, the same way Schedule Uncertainty is blank on Resource Assignment rows. Read the icon two ways at once:

• Color is the answer: orange means this cost will stretch with its duration, gray means it will not. Scanning for orange shows you every cost that is coupled to the schedule.
• Fill tells you where an orange came from: solid orange was switched on for that row, outline orange is inherited from a mapped activity. Every gray is an outline, whether the off was set on the row or inherited; the tooltip and the picker say which.

So there are three things to see: solid orange (on, set here), outline orange (on, inherited), outline gray (off). Hovering names the state in full, for example “Cost Overlay is ON, inherited from activity ESP-M035”. Clicking opens a small picker with the states written out and the current one checked: Inheritance is permissive: an assignment mapped to several activities overlays if any one of them has overlay on. An assignment mapped to no activity has nothing to inherit, so it reads “No mapped activity” and never overlays; set it to On explicitly if it should. Because inheritance flows through the activity mapping rather than the tree, setting overlay on an activity changes the resolved state of every assignment mapped to it, wherever those assignments sit in the tree. The cascade reloads after each change so those rows update immediately. Overlay only changes a number when the activity’s duration actually varies, which means the activity needs a schedule Uncertainty Class to sample from. This makes it a Pro-tier control in practice: the Lite tier runs risk events only, so nothing samples a duration and overlay has nothing to scale.

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Filtering which risks are included

A floating filter bar (the Filters pill, collapsed by default on the Project: row) decides which risks enter the simulation. The same filters drive both the Monte Carlo run and the Scenario Planner, so the planner always shows exactly the risk set being simulated.

• Risk Status (multi-select): defaults to Active. Add Proposed, Realized, Retired, or Deprecated if you want them in the run.
• Classification: Threats Only (default), Opportunities Only, or All. Threats add cost and extend the schedule; opportunities reduce cost and pull the schedule in.

Click the pill to expand the bar, Change Filters to edit, and Clear all to reset to the defaults. The bar also shows a read-only Project chip.

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Running a simulation

The Run New Simulation area holds the controls for a run:

• Mode (the Show choice): pick what the simulation includes before you run it (see below).
• Simulation Iterations: how many Monte Carlo iterations to run (default 5000). More iterations give smoother, more stable percentiles at the cost of a longer run.
• Scenario dropdown and Edit button: optionally run against a saved scenario (see Scenario Planner).
• Random Seed (optional): leave blank for a fresh random seed, or paste a seed to reproduce an earlier run exactly.
• Run: starts the simulation. The chart is hidden while the run is in progress and appears when results are ready.

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Simulation modes

You choose the mode before running, because changing it requires a new run: The chosen mode is echoed in the chart subtitle so a saved or exported chart is self-describing.

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Reproducibility (Random Seed)

Every run uses a random seed, shown with the results and saved with the simulation. To reproduce a run, copy its seed into the Random Seed input (the Reuse seed button does this for a loaded simulation) and run again with the same mode and inputs. This is also the clean way to do before/after comparisons: hold the seed fixed and change one input.

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Scenario Planner

The Monte Carlo Scenario Planner is a what-if workbench. It lets you model the effect of turning specific risks off, or turning individual response actions on or off, without changing your live risk data, then run the simulation against that saved scenario. Open it with the Edit button next to the Scenario dropdown on the Run New Simulation row. The planner lists the same filtered risk set the simulation uses (Active + Threats Only by default), so the scenario you build and the run you launch always match.

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Loading and saving scenarios

The Load Scenario dropdown starts on Default (Current State), which mirrors your live data with every risk and active response action turned on. Use the controls next to it to manage scenarios:

• Add (the + icon): start a new scenario. You must give it a name before you can toggle anything; the planner prompts you if you try.
• Rename (pencil) and Delete (trash) icons appear once a saved scenario is loaded.
• Every toggle auto-saves to the current scenario, so there is no separate save step once it is named.

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The summary bar

Three totals across the top update live as you toggle:

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The risk table

Each risk is a row, with its response actions nested beneath it. The columns are Active, Risk ID, Title / Action, Status, WBS, Work Package, Risk Probability (%), Risk Cost Impact, Mitigated Risk Probability (%), Mitigated Risk Cost Impact, and Mitigated Risk Exposure.

• Deactivating a risk (click its Active badge) excludes it entirely from the scenario: its row is struck through and it drops out of the totals and the simulation. Use this to ask “what if this risk never materializes?”
• Response actions appear as sub-rows under each Mitigate risk, each with its own Active toggle and its Probability Reduction, Cost Reduction, and Details (the action’s status and owner). Only the active actions’ reductions are subtracted from the Risk values to compute the Mitigated Risk numbers, so turning an action off restores its reduction and raises that risk’s Mitigated Risk exposure. Use this to test “what if we drop this mitigation?”
• The Mitigated Risk Probability / Mitigated Risk Cost / Mitigated Risk Exposure values are color-coded: green when the response improves the number, red when it is worse, and black when unchanged.

The selected scenario’s name is recorded with the run and shown in the results, so a saved or compared simulation always says which scenario produced it.

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Reading the Monte Carlo Cost Results

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The cost distribution chart

The chart overlays a histogram of iteration costs (the frequency bars) with the cumulative S-curve. The S-curve answers “what is the probability the project comes in at or below cost X?” Percentile lines (P10, P50, P80, and so on) can be toggled on from the Percentile Summary table.

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Risk and Mitigated Risk

When risks carry both Risk and Mitigated Risk impacts, the chart can show two curves:

• Mitigated Risk: the outcome assuming your planned mitigations and response actions are in place. This is the primary view.
• Risk: the outcome before mitigation.

Use the toggles above the chart to show either curve or both. The gap between them is the value of your mitigation plan.

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Percentile Summary

The Percentile Summary table lists the cost at each confidence level (P10, P50, P70, P75, P80, P90). When both Pre and Post curves are shown, it also shows the Reduction and % Improved between them. Each row has a Show checkbox to draw that percentile’s line on the chart. Use + Add to add a custom percentile, either by confidence level (for example, P85) or by a target cost value (which the table resolves to the percentile it falls at).

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Contingency Decomposition

The Contingency Decomposition panel answers “where does my contingency come from?” at a confidence level you choose. It appears after a Combined run, since the breakdown needs all sources present. It shows:

• Combined P[X]: the total project cost at the selected confidence level.
• Deterministic baseline: the point-estimate cost with no uncertainty and no risks.
• Contingency (P[X] minus baseline): the buffer you would hold.

The contingency is then split by source:

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Choosing a confidence level

The Confidence Level picker is populated from the percentiles in the Percentile Summary table (including any custom percentiles you have added) and defaults to P80 (a commonly cited level for cost contingency). Your choice is remembered per project. Changing it updates the numbers instantly, with no need to re-run, because the breakdown is computed from the cached iteration data.

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Understanding the Interaction line

The three sources are estimated independently, so they do not always sum exactly to the combined contingency; the difference is shown as Interaction / correlation. This line is usually negative, and that is expected and useful: it is unlikely that estimating uncertainty and risk events both land on their high-side outcomes in the same iteration, so the contingency you actually need is less than the sum of the parts. A negative interaction is the diversification benefit of analyzing the sources together. A positive interaction would mean the sources tend to spike together (positive correlation).

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Monte Carlo by WBS

The Monte Carlo by WBS tree rolls the results up the WBS structure, so you can see each WBS element’s contribution to the total at each percentile. Use the View selector to switch the rollup between the Mitigated Risk (default) and Risk contributions. Use Hide $0 Rows to suppress empty branches, and the Collapse All / Expand All link to toggle the tree.

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Cost Sensitivity (Top Drivers)

After the WBS rollup, two tornado charts rank what is driving the spread in project cost, so you know where to focus attention. Cost Risk Sensitivity Analysis (Top 10 Drivers) ranks the risk events by their effect on project cost: one signed bar per risk, sorted by magnitude. Threats point right and are shown in red (they add cost); opportunities point left and are shown in blue (they save cost). The axis is the signed cost impact (threat positive, opportunity negative). Clicking a bar opens that risk for editing, so you can go straight from “this risk moves my number the most” to adjusting it. Cost Sensitivity by WBS (Top 10 Uncertainty Drivers) ranks the estimating uncertainty instead: each bar is one WBS element’s P10 to P90 baseline-cost range, so a longer bar means a wider, less certain estimate. Where the risk tornado shows which discrete risks matter most, this shows which parts of the estimate itself carry the most uncertainty and might warrant tighter estimating or a basis-of-estimate review.

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Reading the Monte Carlo Schedule Results

The Schedule tab presents the same run from the finish-date angle: instead of “how much will the project cost?”, it answers “when will the project finish?”. It comes from the very same iterations as the cost results; because cost and schedule are sampled with shared random draws, a long-duration iteration also tends to be a high-cost iteration (the cost-schedule correlation), which is why running them together is more realistic than treating them separately. The Schedule tab mirrors the Cost tab section for section, but everything is expressed in finish dates and working days rather than dollars.

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The finish-date distribution chart

The chart overlays a histogram of iteration finish dates (the frequency bars) with the cumulative S-curve. The S-curve answers “what is the probability the project finishes on or before date X?” Toggles above the chart show the Risk curve, the Mitigated Risk curve, and the frequency bars; percentile lines can be turned on from the Percentile Details table.

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Risk and Mitigated Risk

When risks carry both Risk and Mitigated Risk schedule impacts, the chart can show two finish-date curves:

• Mitigated Risk: the finish distribution assuming your planned mitigations and response actions are in place. This is the primary view.
• Risk: the finish distribution before mitigation.

The gap between the two curves is how much earlier your response plan is expected to bring the project in. (In Uncertainty Only mode there are no risks, so Risk and Mitigated Risk are identical and the toggles stay hidden.)

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Percentile Details

The Percentile Details table lists the finish date at each confidence level (P10, P50, P70, P75, P80, P90), with a Description and, when both curves are shown, the Delta in days between Pre and Post. Each row has a Show checkbox to draw that percentile’s line on the chart. Use + Add to add a custom percentile either by confidence level (for example, P85) or by a target finish date (which the table resolves to the percentile that date falls at), so you can answer “what is my confidence of finishing by this committed date?”

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Schedule Contingency Decomposition

The schedule analog of the cost Contingency Decomposition. It shows the number of days between the deterministic baseline finish and the finish date at the confidence level you choose, then splits that schedule buffer by source: There is no cost-overlay source here, since that is a cost-only effect. As on the cost side, the Confidence Level picker (default P80) is populated from the percentiles in the table and recomputes instantly from the cached iterations, and the Interaction / correlation line is usually negative, the diversification benefit of analyzing duration uncertainty and risk events together.

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Calendar days versus working days

Each figure is shown in calendar days first, with the working-days equivalent alongside (for example, “134 calendar days (95 working)”):

• Calendar days is simply the elapsed time between the two dates. It is unambiguous, and it matches the finish dates and the Delta column used elsewhere on the page (and the Schedule Delay Drivers exposure).
• Working days is that same buffer expressed on the project’s default calendar, that is, its work week and holidays. This is the figure schedulers usually hold as reserve. The two differ by the calendar’s working ratio (roughly 5 in 7 for a standard five-day week, so 134 calendar days is about 95 working days).

The working-days figure is always counted on the one default calendar. If the activities on the driving path use different calendars, working days is still measured against the default calendar (and falls back to a plain five-day week only if no default calendar is set), so it can slightly misrepresent a finish that was actually driven on another calendar. Calendar days has no such dependency, which is why it leads. When in doubt, read the calendar-days figure.

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Schedule Sensitivity (Top Drivers)

The Schedule tab ranks what drives the finish date with two tornado charts, parallel to the cost Cost Sensitivity view:

• Schedule Risk Sensitivity (By Risk) ranks the risk events by their effect on the finish date: threats that extend the finish point right (red), opportunities that compress it point left (blue). It is shown for Combined and Risk-Only runs.
• Schedule Sensitivity Analysis (By Activity) — Top 10 Drivers ranks the activities by how many days their duration variation moves the project finish, so you can see which activities the schedule is most sensitive to.

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Schedule Criticality

The Schedule Criticality — Top 10 Activities chart shows the percentage of iterations in which each activity sat on the critical path (its total float was effectively zero). It complements the by-activity sensitivity tornado: sensitivity measures how much an activity moves the finish when its duration changes, while criticality measures how often the activity is actually on the binding path. An activity that is both highly sensitive and frequently critical is a prime candidate for schedule risk mitigation.

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Schedule modeling rules

A few schedule-modeling rules are worth knowing (the ? icon on the Schedule tab summarizes them, and the methodology page covers them in full):

• Schedule constraints are ignored (a constrained date never moves, which would distort the analysis).
• Start-to-Finish (SF) links are not modeled; convert them to Finish-to-Start.
• Activities use their own calendar, else the project default, else a 5-day work week.
• A risk’s schedule impact extends its mapped critical-path activities; a risk with no activity mapping extends the project finish directly.

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Per-node reports (Reports column)

The Uncertainty Cascade tree has a Reports column (just after Correlation) that lets you drill into the Monte Carlo result for any single node, not only the project total. Each row shows up to three icons, and they become active once you have run or loaded a simulation (they appear grayed out until then):

• Cost Monte Carlo (green): the node’s total-cost distribution. Shown on Project, WBS, Work Package, and Resource Assignment rows.
• Schedule Monte Carlo (blue): the node’s finish-date distribution. Shown on Project, WBS, Work Package, and Activity rows.
• Schedule Delay Drivers (purple): the schedule drivers of the node’s finish. Shown on the schedule-driving rows (Project, WBS, Work Package, Activity).

Hover an icon for a quick preview; click it to open the full modal.

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The Cost and Schedule modals

The Cost and Schedule modals are the same charts as the main results, scoped to the node you picked: the frequency histogram with the cumulative S-curve, the Risk and Mitigated Risk curves with their Show and Frequency toggles, the deterministic baseline and percentile crosshair lines, and a Percentile Details table (including any custom percentiles created in the main results). All three reports share a single modal with a tab strip at the top: Cost, Schedule, and Schedule Delay Drivers. A tab appears only when that report exists for the node, so a Resource Assignment shows just Cost, an Activity shows Schedule and Schedule Delay Drivers, and a Project, WBS, or Work Package shows all three. Whichever icon you click opens the modal on that report’s tab, and you can switch between the node’s reports without leaving the modal. The Project row matches the main Cost and Schedule charts exactly. Rows below the project are summarized for compact storage (see How per-node numbers roll up below, and Per-node distributions and bucketing on the methodology page), so their percentiles can differ from the exact value by a fraction of a percent.

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How per-node numbers roll up

Cost and schedule roll up the tree differently, and the modals state this inline:

• Cost is additive in the mean: a parent’s average cost equals the sum of its children. Its confidence levels do not add up, though: a parent’s P80 is lower than the sum of the children’s P80, because their risks rarely peak in the same iteration (diversification).
• Schedule is not additive at all: a parent’s finish is its latest-finishing child (the critical path), so child finish dates never sum to the parent, and a child can even show a larger delay than its parent.

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Schedule Delay Drivers

The Schedule Delay Drivers modal ranks the predecessors that drive the selected node’s finish, as horizontal stacked bars. Each bar is split into a duration-uncertainty segment plus one segment per mapped risk event (labeled with the risk’s ID and title), so you can see how much of a driver’s delay is baseline uncertainty versus specific risks. Controls at the top let you:

• Pick the exposure P-level (default P75). The bars rescale so they sum to the node’s risk exposure (the P-level finish minus the deterministic finish) at that confidence level.
• Toggle Risk versus Mitigated Risk (shown when the project has mitigations).

Days here are calendar days, consistent with the finish dates and the Delta column elsewhere on the page. Like the Schedule Monte Carlo, this view follows the critical path and does not sum up the hierarchy.

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Saving and comparing simulations

• Save: give a run a title to save it. Saved runs store the full results, the seed, the mode, the percentiles, the contingency decomposition, and the finish-date distribution, so they reload exactly as they ran.
• Load: pick a saved run from the Previous Simulations list to restore its charts, tables, and decomposition. A reloaded run renders through the same path as a live run, so it looks identical.
• Compare Simulations: open the comparison view to put saved runs side by side (for example, a Risk run against a Mitigated Risk run, or two scenarios), so you can quantify the difference.

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Compare Monte Carlo Results

Click Compare Simulations to open the Compare Monte Carlo Results window. Add 2 to 5 saved simulations, and the window overlays their cumulative-probability S-curves and lines up their percentiles in a comparison table. It is the cleanest way to answer “how much better is plan A than plan B?” Each comparison is built from a few controls at the top:

• Add simulation: pick a saved run from the dropdown and click Add. Each added run gets its own color, which is used consistently in the chart, the legend, and the table.
• Results (per run): choose Mitigated Risk or Risk for that run, so you can compare like-for-like or deliberately contrast a Risk run against a Mitigated Risk run.
• Base: the radio button marks one run as the baseline that the others are measured against. The base run is listed first, and every delta in the table reads “base vs other”.
• Remove (trash icon): drop a run from the comparison.

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Cost and Schedule tabs

The results are split into two tabs so you can compare a run on either dimension of the same iterations:

• The Cost tab overlays each run’s cost S-curve and a Percentile Comparison table of the cost at each confidence level (P10 through P90, plus any custom percentiles). Deltas are shown in dollars and percent; green means the run is lower than the baseline (an improvement), red means higher.
• The Schedule tab does the same for the project finish date: it overlays each run’s finish-date S-curve and lists the finish date at each percentile. Here deltas are shown in calendar days; green means the run finishes earlier than the baseline (an improvement), red means later.

In either tab, the Show checkboxes on the left of the table draw that run’s percentile line on the chart, so you can mark, say, every run’s P80 to see the spread at a glance.