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Do You Think Risk Management Is Too Difficult To Consider?

By David Vose

A common misconception is that risk management is only for big companies and banks, with high-powered mathematicians building sophisticated risk analysis models. In fact, we all do risk management in our daily life:

  • We will leave early to get to an important meeting
  • We keep extra rolls of toilet paper in the cupboard
  • We buy fire insurance
  • We keep a spare tire in the back of our car
  • We check the sell-by date on our food

I got up at 5am last Tuesday to be sure to get to a meeting in time. I imagined that there would be traffic around Antwerp (there was none), roadworks in the Netherlands (there were none) and that I would have to sit through a 15 minute safety video at the site (I didn’t). So I was an hour early, sitting in a waiting room, thinking about that extra hour of sleep I could have had.

Risk analysis is all about trying to make a better decision in the face of uncertainty. If I’d been bothered to collect some data, I would have realized that I could have had an extra 30 minutes sleep last Tuesday and still have been in plenty of time for my meeting. No mathematical model was needed, just a clearer picture of the problem through a bit of research.

For toilet paper, I just keep a stack of them because the cost is small and the impact of running out is significant. It’s a no-brainer.

Fire insurance gives me peace of mind, but the terms of my mortgage mean that I have to buy it anyway, so I’ll shop around for the best deal. The insurance company does have high-powered mathematicians writing fancy risk analysis models (some of them using our ModelRisk software) because they need to figure out a price to charge for insurance that is competitive but covers the risk they take on. The insurance market is very competitive so their pricing has to be precise. Backed up by their database of past claims, a fancy risk analysis model can provide them with the accuracy they need to arrive at a sustainable pricing.

We’re currently helping a client to figure out how they can ensure that the refurbishment of their enormous petrochemical plant will be completed within the (very short) planned time. In this industry, refurbishments very often overshoot the delivery time by 30% or more, and that is very expensive. Situations like this, where an awful lot is at stake, demonstrate the value of taking as much care to estimate risks and uncertainties as precisely as possible, because it gives us the best chance of adapting the project plan in a way that meets the goals. In this case, the schedule model itself will be pretty simple mathematically – the biggest part of the work is the practical thinking that will help us figure out the bottlenecks.

We completed a risk analysis last year on the amount of foodborne illness caused by a bacterium called Campylobacter coming from chickens. The analysis had to evaluate the risk for every member state of the EU and take into account everything that happened to the chicken between leaving the farm and ending up on your plate (and that’s a lot of different, rather gruesome things). The model involved a lot of fairly complex mathematics because there were a lot of data we wanted to make use of.

Risk analysis can be very simple, and certainly should be simple if you don’t have much information. However, sometimes there is a lot at stake and sufficient knowledge to warrant a more precise (and probably more complex) risk analysis. If it’s worth doing, it’s worth doing well, so my advice is to hire a seasoned risk analyst rather than attempt to learn the field yourself. You’ll save yourself time, money and have a lot less worry.

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