Wrapping Up PIGs .... For Now
Since I don't just want to be thought of as some PIG-hating obsessive lunatic, lets wrap this thread up for the moment. Quick recap: The traditional likelihood-consequence matrix (PIG - see original post) is not particularly useful when dealing with aviation safety. Why? Because a graduated consequence scale fails to recognise the perilous nature of aviation and consequence as a dimension isn't particularly useful when evaluating latent conditions remote from the ultimate outcome (death by aviation).
Alternate approach: Instead of scoring the consequence directly, I've offered two alternative dimensions under the generic title of influence1 - proximity and pathways.
In wrapping this up, I thought I would discuss what I think is the rationale behind this approach of using slightly off-centre indicators.
Obviously, it would great to have a complete and high-fidelity model of aviation accident causation. Something which showed all the risk conditions, variables, relationships, etc. A model to such a level that the ramifications of the slightest trend could be calculated automatically. Unfortunately, it doesn't seem to exist or at least, I don't have one.
The implausibility of such a model is why we have risk management. After all, risk is "the effect of uncertainty on objectives".
That is why the single score approach contained in most PIGs seems a contradiction in philosophies. To me, it attempts to apply certainty without telling us where the uncertainty has gone. I'm not sure that makes sense but please go with it for a moment.
What I'm trying to say is that using the traditional PIG, I attempt to assign single score X to condition A. Where did the uncertainty go? In short, it is still there and that is the root of a few of the problems I've mentioned in my last couple of posts. Especially, the problem of what to score - most likely, worst credible, worst case, etc.
What I've attempted to do is retain the uncertainty but keep it out of the scoring process. The proximity and pathways scales are, of course, indirect indicators of something bad happening. There is no guarantee that a risk condition directly connected or with a significant number of connecting pathways to the ultimate outcome will lead to utter catastrophe - but they are variables worth considering.
The uncertainty exists between the scale and the reality. The scoring can be carried out with some degree of confidence according to the scales chosen and the definition of the accident scenario.
Obviously, there may be plenty more such scales. The above two are just the ones that came to mind first - if you can think of any others, I'd love to hear your ideas - please comment.
There is more work to do on this idea. Such as, what other variables are required to support the decision-making process and is likelihood, probability or frequency the best indicator for presence of a risk condition? And so on. But I didn't want this blog to be all about PIGs or matrices or risk management necessarily.
Next week? My page is blank, I hope I don't get writer's block.
1. I might change this label. I really suck at naming things except my kids, their names are awesome ;)
