A probability and impact matrix is a tool used in qualitative risk analysis to evaluate the likelihood and impact of identified risks. It uses a numerical scale to rate the likelihood and impact of each risk, which can then be used to prioritize risks and develop strategies to mitigate or manage them.

This matrix specifies combinations of probability and impact that allow individual project risks to be divided into priority groups.

The probability of occurrence for each individual project risk is assessed as well as its impact on one or more project objectives if it does occur, using definitions of probability and impact for the project as specified in the risk management plan.

The matrix can be made using;

• Cardinal scales Identify the probability and impact on a numeric value from 0.01 (very low) to 1.00 (certain).
• Ordinal scales Identify and rank the risks with common terms, such as very high to very unlikely, or using a RAG (red, amber, green) rating to signify the risk score

The scores within the probability-impact matrix can be referenced against the performing organization’s policies for risk reaction. Based on the risk score, the performing organization can place the risk in differing categories to guide risk reaction. There are three common categories based on risk score:

Red condition These high-risk scores are high in impact and probability.

Amber condition (aka yellow condition) These risks are somewhat high in impact and probability.

Green condition These risks are generally fairly low in impact, probability, or both.

An Example of Probability and Impact Matrix

An example of using a probability and impact matrix in manufacturing could be as follows:

• Identifying potential risks such as equipment failure, supply chain disruptions, and employee injury.
• Evaluating the likelihood and impact of each risk using a numerical scale, for example:
  • Likelihood: 1 (very unlikely) to 5 (almost certain)
  • Impact: 1 (minor) to 5 (catastrophic)
• Plotting each risk on the matrix according to its likelihood and impact rating, for example:
  • Equipment failure: likelihood 4, impact 3
  • Supply chain disruptions: likelihood 3, impact 4
  • Employee injury: likelihood 2, impact 5
• Prioritizing risks based on their overall risk score. For example, the risk of employee injury, which has a low likelihood but high impact, would be considered a high-priority risk.

It’s important to note that different organizations or projects may use different numerical scales and different criteria to evaluate risks, so it’s important to understand the specific guidelines used in your organization or project

Further Readings

1. Qualitative Risk Analysis