I’ve had some interesting conversations recently with Professor Fred Piper regarding risk probability. The discussion started because I was concerned about assessments of risk probability, as one might routinely use to populate a risk heat map or risk register.
What’s the problem? For me, it’s the fact that, as the probability of an incident occurring approaches 1.0 or 100%, we have no scope to differentiate between an event that occurs only once, and another that’s likely to occur a thousand times (over a specific period).
I can get around this (as I do) by replacing the word probability with the term likelihood and using a simple ordinal scale to measure the relative likelihood of a risk.
Fred is an expert on betting odds, so I thought that we need something equivalent to odds-on for those incidents that are near certain to occur many times, which might enable unlimited extension of the scale. Bookmakers understand odds-on. (Though you could argue that they don’t seem to understand is the opposite, as recently illustrated by Leicester City football club winning the UK Premier League at 5,000 to one.)
But betting odds are a different kind of assessment from probability, reflecting the views of a party (e.g. a person, organization or community) on how likely an event is perceived to happen. Odds-on just means someone thinks the event is highly likely.
But what this illustrates is the need for more precise language to describe properties of risks, as well as realistic scales to position risks. Risk assessment is far from being a precise science, but it should at least be grounded on a more rigorous basis.