Risk Matrix Knowledge Bank

How Not to Design a Risk Matrix – Government of Western Australia’s Risk Matrix

Today, I stumbled across one of the most badly designed risk matrices I have ever encountered. It has been published by the Government of Western A...

How Not to Design a Risk Matrix—Cox’s Axioms

A review of the risk matrix design axioms of Cox (2008) reveals that they overly constrain risk matrix design leading to a false conclusion that only a limited range of risk matrix colorings are permissible.

When Can the Same Risk Matrix be Used with Different Axis Scales?

It is explained under what circumstances an organization can have a standard risk matrix and apply it with diverse axis scales.

Benchmarking Risk Matrix Performance

The benchmarking of risk matrix designs is discussed. A literature review is included and the benchmarking tools available in Quick RIsk Matrix (Premium) are described, with worked examples.

How Not to Design a Risk Matrix - NASA's Risk Matrix

NASA's standard risk matrix as used for its space mission projects is critically reviewed and demonstrated to contain inconsistencies. NASA's fundamental error is to assume that a single risk matrix coloring can be used in conjunction with very different axis scales.

How Not to Design a Risk Matrix - A Public Health Risk Matrix

A risk matrix used in public health assessment is critically reviewed and found to contain a commonplace error of design.

How Not to Design a Risk Matrix - National Health Service (UK) Risk Matrix

There are many ways in which to design a poor risk matrix, but one method is used so often that it deserves its own article. This unsound method involves the use of ordinal scales for likelihood and consequence and a pretense that the ordinal scales (which are essentially just labels) can express the magnitude of the likelihood and consequence variables.

How to Design a Risk Assessment Matrix (Correctly)

How to design a risk matrix that will be self-consistent and will map {probability, consequence} category pairs to risk categories with as few errors as possible.