Near the end of my last post, I used the Swiss-cheese model to highlight that many risk conditions1 worthy of attention are not necessarily proximate to the ultimate outcome. I also hinted in the post before that, that I thought this to be only half the story. To tell this story, let me introduce another accident causation modelling technique. It is called an AcciMap and it is gaining popularity because it offers a way of representing the relationships between events (these being things such as decisions, functions, tasks, actions, etc.). An AcciMap is set up in two dimensions with vertical lanes separating system levels of increasing generality as you move up and the horizontal axis having no fixed dimension or scale. The system levels begin very specific to the accident in question with equipment and actor activities making up the first two levels. The higher levels relate to organisational, regulatory authority and government policy and decision making.
Here is a poorly drawn adaptation of an AcciMap:
If proximity was the only consideration then the top event and the limited emergency response equipment would be highest risk conditions. They are sitting right next to that big "ouch" so they must be the biggest problem.
But what about those inappropriate budget cuts? A decision like that has wide-reaching effects with most of them hidden until it is too late. I've started thinking about risk conditions such as this as having multiple pathways to the ultimate outcome. Therefore, they are just as important as those risk conditions which are in close proximity to the ultimate outcome.
Influencing Outcomes through Proximity & Pathways
So, where I'm going with this? I am recommending that instead of a straight consequence dimension, those conducting safety risk evaluation within a complex socio-technical system use an influence dimension made up of two scales - proximity and pathways. These scales can be defined as:
- Proximity - relating to the number of discrete risk conditions between the condition being evaluated and the ultimate condition.
- Pathways - relating to the number of pathways, via which, the risk condition being evaluated may lead to the ultimate condition.
Having multiple scales on one dimension isn't unusual but the above approach is a little different.
Where as the typical implementation of a multi-scaled dimension consists of different types of consequences (political, economic, reputation, etc.), the above approach is solely about the safety consequence. Therefore, you can't really stick these two scales into a common matrix as they sit at a different level to the standard scales.
They also differ in that they relate to the risk condition and not the potential outcome. As the outcome has already been defined as utter catastrophe, the focus has been turned toward the risk condition. And to me, that seems quite intuitive and reasonable.
These differences mean that when combined with some form of frequency or likelihood dimension2, we end up scoring the risk inherent to the risk condition. Of course, you can show this is a matrix but I think there is more to this story.
Hopefully, next time, I'll get this under control and tie it all together...
1. I am loathed to just say risks. To me whenever one uses the word "risk" it should be followed by "of" - for example "the risk of a runway excursion is high due to high crosswind, poor surface friction and large jet aircraft". It is always difficult to discuss a concept without a strong standardised lexicon and the last thing we need right now is another term introduced by some opinionated blogger but... I can't help it. People refer to a variety of, what I have come to call, conditions when they describe risks - they mention events, hazards, situations, mental states, failures. My intention is to accommodate all these under the one name, risk condition.
2. I'm not sure which to use yet. That problem is for this week's idle moments