Risk & Strategy / Cost Model Explorer

What this is for: Compare the six PQC costing-model families on one scenario, with a live Monte Carlo run.

What a good answer looks like: A range, not a point. The honest output of this tool is the spread between your best and worst assumptions, and which assumption drives it.

Worked example: Enter the systems in scope and the annual IT budget, then compare the parametric, bottom-up and Monte Carlo estimates: the spread between them is your honest range, and the driver that moves it most is the assumption to defend.

Runtime and privacy: This planning tool runs in your browser. Use synthetic or approved organizational data and review the site privacy terms before entering sensitive material.

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For your role

Executive / Business Leader
Enter the systems in scope and the annual IT budget, then read the parametric, bottom-up and Monte Carlo estimates side by side: the spread between them is the honest range to bring to a budget discussion.
GRC / Risk & Compliance
Run Monte Carlo and note which slider moves the result most: that assumption is the one to document and defend, and the cost-of-inaction line is shown as a reference because it measures a different thing.

Feel the difference. One scenario, six lenses. Five estimate the cost of migrating; the sixth (cost of inaction) is shown as a reference line, because it measures a different thing. Every figure is illustrative and driven by the sliders below — the lesson is how far the methods diverge.

Your scenario
102505000
$5M$50.0M$500M
0.5 modern1.0×2.0 legacy
15 yr10
Five ways to price the same migration
spread 1.8×
Cost of inaction $3.9M
Parametric (budget-anchored)$20.0M

8% of IT budget × 5yr — ignores system count entirely, and is the lens most sensitive to programme duration.

Bottom-up (activity-based)$13.3M

$40K/system × complexity × 250 + $3.3M standing program cost over 5yr.

Probabilistic (Monte Carlo)$11.5M – $22.8M

Samples an uncertain per-system cost → P10–P90 band. A range, not a point.

Judgemental (scenario)$9.3M – $21.3M

Optimistic / expected / conservative around the bottom-up number.

Analogical (historical)$10.8M

$30K/system from past crypto migrations × 250 + $3.3M standing program cost (illustrative).

On this scenario the five migration-cost methods range from $10.8M to $20.0M — a 1.8× spread on identical inputs. No single number is “the” cost; that is exactly why you estimate more than one way and reconcile.

How the spread is built: all five lenses estimate the same quantity — the total cost of this programme — so all five respond to the planning horizon. Per-system work does not stretch with the schedule, but standing programme costs (PMO, governance, discovery) accrue for as long as the programme runs, so those scale while the per-system term does not. The parametric lens remains the most horizon-sensitive by construction, since it is a share of annual budget spent every year. The cost-of-inaction marker is a different quantity and is deliberately kept off the migration-cost comparison.

Monte Carlo, run live

The probabilistic lens doesn't give a number — it gives a distribution. Run it and watch 1,000 draws build the shape. Each draw samples an uncertain average cost-per-system; the band is where the middle 80% lands (P10–P90).

0 / 1,000 draws

Next, the ROI Calculator builds a defensible bottom-up estimate for your own estate and cross-checks it against your assessment — one honest number you can take to the board, with the humility this explorer just demonstrated.

Cost Model Comparison — Export

Export the comparison as markdown, PDF, or DOCX — also saved to your Command Center Risk Artifacts.

Illustrative simulation for building intuition. Figures derive from the sliders above and the labelled constants in each method — not from your organization's data.

Try it

After Run Monte Carlo, what is the honest number to bring to a budget discussion?

Next step

Next in Risk & Strategy: CRQC Scenario Planner

CRQC Scenario Planner is the next Risk & Strategy tool in the Command Center.