In this article, I look at The Risk Matrix, a widely used technique in many industries. Risk Matrices have many applications!

In this article, I have used material from a UK Ministry of Defence guide, reproduced under the terms of the UK’s Open Government Licence.

**Introduction**

A risk matrix is a graphical representation of the various risks associated with a project and its corresponding risk management strategies. It helps to identify and prioritize potential risks.

**What is a Risk Matrix?**

A safety risk matrix provides a framework for ranking or classifying safety issues according to their significance. The matrix is sometimes called a “hazard ranking matrix” or a “hazard classification matrix”, but it is strictly applied to accidents, since these have harmful outcomes, whereas hazards only have the potential for harm. The matrix can be used as a risk screening tool to help decide which issues need treatment first or which need not be considered further at this time.

Risk matrices can cover exposure to different types of loss, including harm to humans, damage to the environment, financial loss or impact on reputation. If a loss in these diverse categories can be considered in common terms (e.g. the monetary impact of all types of loss), then a single matrix can cover all such issues together and prioritize which are the most significant.

The matrix covers a “risk space” defined by the two component parts of risk, namely likelihood on one axis and consequence (or severity) on the other. Each axis must span the full range of outcomes, which are considered possible for the system of interest. Each range is divided into a number of categories or bands (typically between 3 and 8) to define the cells of the matrix.

The bands on the two axes may be defined in terms that are purely qualitative, semi-quantitative, or fully quantitative, for example:

- Qualitative:
- Likelihood is (Frequent/Reasonably Probable/Remote/Extremely Remote)
- Severity is (Minor/Significant/Severe/Catastrophic)

- Semi-quantitative:
- Likelihood is (e.g. likely to occur once per year on one site)
- Severity is (e.g. a single death)

- Quantitative:
- Likelihood is (e.g. between 1×10-4 and 1×10-5 per year on one site)
- Severity is (e.g. between 1.0 and 10.0 Fatalities and Weighted Injuries)

Each cell of the matrix is assigned an indicator defining the relative significance of issues falling in that zone. This indicator could be:

- A risk descriptor (e.g. Low, Moderate, High, Very High)
- A risk score or index (e.g. a number from 1 to 20)
- A priority category (e.g. High, Medium or Low)
- A risk class (e.g. A, B, C or D)
- A measure of expected rate of harm or loss (e.g. 5.4 Fatalities and Weighted Injuries per year or £45,000 per year)

Where likelihood and consequence are stated quantitatively, the axes are usually considered to have logarithmic scales. Adjacent bands will typically differ by one order of magnitude. In this case, lines of constant risk run diagonally across the matrix and the risk will range by a factor of 100 across the area covered by a single cell. This illustrates that the matrix is a coarse tool, which can show large differences in risk, but does not address fine detail, such as compliance with quantitative risk requirements.

To apply the matrix, users must have a list of the relevant safety issues (from Hazard Identification and Hazard Analysis) and estimates of the likelihood and severity of each possible accident (from Risk Estimation). The matrix is therefore a technique for Risk Evaluation, which follows on from Risk Estimation. The estimates of accident likelihood and severity may be generated by different methods, depending on the stage of the project, the information available and the significance of the safety issue being explored. For example, the estimates may come from:

- Engineering judgement by Subject Matter Experts with knowledge of similar systems
- Historical data from this or similar systems
- Detailed modelling (e.g. using Fault Tree Analysis and Event Tree Analysis or Bow-Tie Analysis)

**Examples of Risk Matrices**

The following example matrices show some of the variations in format, terminology and risk indicators across a range of sectors and standards.

**Example 1: IEC 31010** Example risk ranking matrix. Severity on x-axis increasing left to right, likelihood on y-axis increasing bottom to top, with five “risk levels” which are linked to decision rules such as the level of management attention or the time scale by which response is needed.

**Example 2: Def Stan 00-56 Issue 2** Example accident risk classification table. Severity on x-axis increasing right to left, likelihood on y-axis increasing bottom to top, four risk classes identify significance and so management level for approval.

Catastrophic | Critical | Marginal | Negligible | |

Frequent | A | A | A | B |

Probable | A | A | B | C |

Occasional | A | B | C | C |

Remote | B | C | C | D |

Improbable | C | C | D | D |

Incredible | C | D | D | D |

**Def Stan 00-56 Issue 2 Example Accident Risk Classification Table**

**Example 3: IMO Guidelines on FSA**. Example hazard risk index matrix. Severity on x-axis increasing left to right, likelihood on y-axis increasing bottom to top, risk index (RI) in each cell calculated by adding Severity Index (SI) for column and Frequency Index (FI) for a row. RI can be considered as log(risk), obtained by adding FI and SI.

FI | Frequency | Severity (SI) | |||

1 | 2 | 3 | 4 | ||

Minor | Moderate | Serious | Catastrophic | ||

7 | Frequent | 8 | 9 | 10 | 11 |

6 | 7 | 8 | 9 | 10 | |

5 | Reasonably probable | 6 | 7 | 8 | 9 |

4 | 5 | 6 | 7 | 8 | |

3 | Remote | 4 | 5 | 6 | 7 |

2 | 3 | 4 | 5 | 6 | |

1 | Extremely remote | 2 | 3 | 4 | 5 |

**IMO Guideline on FSA: Risk Ranking Matrix**

**Example 4: ISO 17776 Offshore Sector** Example risk matrix. Severity on y-axis increasing top to bottom, likelihood on x-axis increasing right to left to top, matrix areas define future action to be taken.

## R**isk Matrix Assessment**

### When it Might be Used

The matrix is usually set up at an early stage of the lifecycle, defining the framework to be used for risk evaluation at subsequent stages. It should be used early in the lifecycle to provide a coarse sift of the identified safety issues so that attention can be focused on the most significant ones. This attention may involve more detailed analysis to understand complex accident sequences and to apply semi-quantitative or fully quantitative risk assessment techniques where appropriate.

Later in the lifecycle, the risk matrix may be used for determining the appropriate management level for review and acceptance of each safety issue. This ensures that the key risk drivers are brought to the attention of senior managers but they are not swamped with masses of information on less significant matters.

During the in-service stage of the lifecycle, the risk matrix technique can be applied to give an indication of significance for new safety concerns, such as those revealed by incidents or due to proposed design changes. Risk monitoring can be focused on the issues of highest significance as well as targeting resources for risk reduction.

**Advantages & Disadvantages**

### Advantages

- Risk matrices provide a quick appreciation of the most significant issues so that attention can be focused where it will have most benefit.
- Matrices provide a visual representation which is easily understood and so aids communication with non-specialists.
- Risk matrices can cover impacts which are different in nature (e.g. harm to people, harm to the environment, material or financial loss), provided that these can be equated in common units (e.g. in money terms).

### Disadvantages

- Risk matrices are good for examining different issues affecting one system or activity on the basis of their risk relative to each other. They are not effective for understanding absolute risk.
- There is no single, correct interpretation of the level at which “safety issues” should be selected for presentation on the risk matrix. This means that different analysts may choose different levels and the resulting list of prioritised issues is somewhat subjective. The apparent results may be changed by “accident splitting” (i.e. defining one safety issue as two or more different accidents, each of which will appear to have lower risk).
- Risk matrices consider safety issues one at a time and so do not help understanding the overall or aggregate risk exposure.
- When a variety of different outcomes is possible from a single issue (e.g. fire – consequences can range from no harm to multiple deaths) it can be difficult to choose which likelihood and consequence combination should be used.
- As a broad-brush technique, risk matrices should not be used for considering whether quantitative risk targets have been met or as the only technique for examining complex or high consequence issues. The matrix can, however, highlight high consequence issues so that they then receive more detailed consideration.

## R**isk Matrices for Project Management**

In project management, we are aiming for specific outcomes, often represented as the project management triangle.

In the center is quality (and/or safety), which is central to indicate that this cannot be compromised. The three corners are cost, time, and scope (or requirements), and these can be traded off against each other.

This representation helps us to identify project risks by the effect that they might have on the project’s objectives. ISO 31000 defines risk as “the effect of uncertainty on objectives”. Again, the risk matrix allows us to identify and rank risks, identifying the biggest, most critical risks. These risks are where we will focus most attention, looking for multiple controls, or defense-in-depth, for the most serious ones.

An old saying is that “you can have a quick job, a proper job, or a cheap job; you can have two out of three, but you can’t have all three.” Taken literally this is a little pessimistic, but it does remind us that if we set an absolute target on one of these axes, then we will likely have to trade the other two off against each other.

This axiom also gives us some basic principles on which to identify controls. We might desire controls that allow us to achieve all objectives at the same time, but this is often unrealistic. Practical experience – encoded in a saying – suggests that we must be prepared to accept some trades in budget/schedule/scope.

Thus the risk matrix, in combination with some basic project management principles, enables more realistic decision-making. (Real decisions involve saying ‘no’ to some things in order to say ’yes’ to others.) Rather than naively thinking that we can have it all, the risk matrix supports robust early decision-making.

This should make project success more likely – until somebody changes the objectives!

**Additional Considerations**

It should be noted that risk matrices from different standards and industry sectors are not always represented in the same way. The most common convention has a Cartesian representation (i.e. values increasing left to right and bottom to top on the two axes) so that risk increases from bottom left to top right, but the examples below show that several common matrices have a different format.

If risk estimates are generated by a team of Subject Matter Experts, their deliberations can be biased (consciously or unconsciously) if they know the risk matrix framework. There may be a tendency to choose likelihood and/or severity estimates that result in a lower apparent risk so that it attracts less management scrutiny.

Uncertainty of the estimates of severity and likelihood can be represented on a risk matrix by showing that risk with error bars rather than a single point. This can help understanding by senior managers.

Using common matrices for different systems does not necessarily result in risk estimates that can be compared in a meaningful way. The systems may have diverse risk exposure factors (e.g. number of people exposed, usage rate) and different numbers and types of accidents to consider.

(For more on risk management, **see the FAQ**.)