“Risk Matrix Pitfalls” Webinar Summary
Posted on February 9, 2022 | in Operational Risk
Recently, we hosted a webinar on risk matrix pitfalls presented by resident expert and Risk Management Senior Solutions Strategist, Dana Garber. In the session, Dana shared – you guessed it, some common pitfalls of risk matrices that people often overlook. His advice was based on subject literature review conducted by VelocityEHS experts and the experience of clients undertaking Risk Matrix design activities.
A risk matrix itself is a chart that assesses a business risk, based on that risk’s likelihood and consequences, and organizes them in such a way that you can determine varying risk levels. To create one, an organization needs to decide the credible severity and likelihood levels of all risks, and determine tolerable thresholds and actions associated with those risks. Risk matrices are useful for grouping similar tolerability determinations, but it’s always best to do a cost-benefit analysis to determine specific prioritization.
When designing a risk matrix, there are three common approaches – each with its own kind of pitfall to keep in mind when determining which to use.
Quantitative Risk Matrix
- Treats the risk matrix as a graph/chart
- Utilizes numeric logic to construct a sound risk matrix
- Has a heavy reliance on use of scales, banding threshold curves and calculation
- Requires some level of user sophistication in understanding of the risk being assessed
- Recommended for high-hazard industries and takes most subjectivity out of the evaluation process
- Pitfall: Using formulae and numbers can be misleading and make logic seem less intuitive, leaving end users to blindly accept results without understanding what those results mean
Qualitative Risk Matrix
- Treats the risk matrix as a mapping table
- Has a heavy reliance on workshopping with senior leadership and subject matter experts
- Intuitive and hence ideal for most risk end users
- Useful for grouping a large number of varying risks
- Easily adopted by workers
- Pitfall: Sometimes the linkage to numerical values can be weak
Semi-Quantitative Risk Matrix
- Combines aspects of Quantitative and Qualitative design
- Useful for varying types of risks and users
- Pitfall: Can be difficult to implement correctly