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Case study


One company used a 10 x 10 risk matrix in their risk assessment process. The main advantage they saw in this was that it lent itself rather nicely to estimating probabilities in percentage terms.


During one risk assessment session they discussed the likelihood of a lengthy power failure, which for one reason or another was known to happen on average twice a year at their office.


The approach they took was to say that, as there are 365 days in a year, two occurrences in a year represented a probability of approximately 0.5% – in other words, extremely low.


But the fact was that they’d had two occurrences that year and two the previous year, and it was almost certain that they’d have two the following year if they didn’t implement any mitigation measures. In reality this risk had a high probability, not a low one.


The discussion went round in circles for some time but finally they concluded that being overly scientific or statistical wasn’t necessarily the best approach to risk management.


Then they went away and looked into the cost of installing a generator!


The next step is to add the risk rating (which, as we now know is a combination of the likelihood and impact) to the final column for each of our risks. This is simply a case of multiplying the likelihood and impact values, or alternatively referring to the risk matrix we saw earlier.


It’s common practice – in fact it’s common sense – that a “rule” is adopted whereby any risk over a certain rating (in this case we’ll say 8 or more), or falling in a red square if we’ve colour coded them, must be dealt with in some way.


50 CHAPTER 3


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