Figure 2-5 : Swiss Cheese model . ( Source : BenAveling CC BY-SA 4.0 19 via Wikimedia Commons . 20 )
By understanding hazards and performing risk analysis it is possible to categorize and prioritize risks , determine which risks are practical and cost effective to manage , and to communicate and address hazards with a defense in depth strategy of elimination and mitigation .
Despite the benefits of risk analysis in various industries there still have been catastrophic events that were not anticipated or prevented through the use of such traditional risk management . The reason is that it is very difficult to anticipate all possibilities in complex and dynamic systems , especially when considering events that are low probability and high consequence . Complex systems also allow losses to occur for which there is no single root cause or initiating event .
There are many new pressures on organizations creating new hazards as businesses rely on computer technology , data , and analytics as never before . These pressures increase the difficulty of performing timely risk analysis and raise the risk of low probability and high impact events . The pressures include :
1 . The increasing pace and interdependencies of business , increasing complexity and the speed with which harmful consequences can occur .
2 . Digital transformation which also increases complexity and scale . This includes new technologies ( data analytics , cloud , big data , AI , digital twin and IoT technologies ).
3 . The increasing reliance on data and algorithms to create ‘ smart ’ systems that operate at speed and scale .
4 . The rapid pace and necessity for change and adaptation , including new business models , intense global competition , climate and sustainability concerns .
5 . Emerging systemic economic pressures including those related to supply chain reliability .
There are also technical difficulties :
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