Before you start
This tutorial walks through a full Probabilistic Margin Analysis on a simple worked example: a six-subsystem fan system, where a redesign in any subsystem may propagate to others through their interfaces.
You only need a modern web browser. The module runs entirely client-side; no installation is required.
Walkthrough
6Add components to the DSM
Open the DSM editor and add the components of your system as rows/columns. Optionally group them into subsystems for cleaner readability and faster editing.
Fill in direct likelihood
For each ordered pair of components, enter the probability that a change in the source will require a change in the target. Use a coarse 0–1 scale (e.g. 0.1, 0.3, 0.7, 0.9) elicited from designers' judgement — the CPM is robust to ordinal-style inputs.
Fill in direct impact
For each pair, enter the average severity of the propagated change — how much redesign work the target component would require if the change reached it. Same coarse scale.
Run CPM
Click the analysis button. The module composes direct probabilities along all paths between every pair of components and produces three derived matrices: combined likelihood, combined impact, and combined risk.
Inspect per-element profiles
Click on any component to see its incoming and outgoing risk profile. Components with high outgoing risk are sources of propagation; components with high incoming risk are absorbers — both can guide where to invest in margins or in interface decoupling.
What-if exploration
Edit a direct value, decouple a pair, or insert an interface buffer, and watch the combined-risk matrix update live. Use this to test design decisions before committing to them.
Next steps
- See the worked examples on the Case Studies page.
- Read Clarkson's original CPM paper on the Literature page.
- Combine PMA results with Margin Value Analysis to weight margins by their exposure to propagating change.
- Get in touch via the contact page.