Predicting the future used to be sciencefiction. But many in the business world already know the value of this kind of future. Big data, and the analytics it drives helps us to predict where problems may occur before they do. And for businesses this means that they don’t need to experience a disaster in order to understand its potential impact and evaluate what steps can be taken to reduce their exposure.
For many industries, an unexpected problem or incident can cause havoc. Those in high-hazard industries, such as power generation, will be all too aware that the failure of one piece of key equipment can cause an entire facility to shut down. Machinery, like turbines are under almost constant stress. Should a breakdown occur, it can quickly escalate. Fires and explosions can follow, with these secondary incidents able to cause extensive damage to a wider facility.
For businesses like power generation operators, an extra layer of difficulty comes in losing a major piece of equipment. Replacements can take months or even years to come, with a vast amount of productive time and associated revenue lost. So, being able to accurately predict what’s most at risk, where the vulnerabilities are, allows vital steps to be taken to mitigate damage.
Not all predictive analytics are alike though. Analytics relies on data, and there is a big difference between using lots of data and quality data. At FM Global we conduct approximately 100,000 client location visits every year resulting in more than 7 million individual data points. The consistency of data collection means that we can provide more accurate loss scenario predictions.
Our suite of predictive analytics tools provides a powerful picture of the exposures a business may face. We’re able to show our clients how predisposed their facilities are to
a specific incident, like machinery breakdown. Or
we can pinpoint a single plant in a global company that is most likely to be under water when a flood strikes. Our data shows that locations which fall in the top 2% most likely to experience a breakdown, do in fact suffer losses at 15 times the
rate than those not within that list.
We’re also able to identify which equipment is most likely to suffer a breakdown within a client’s business. We’re therefore able to help clients direct their risk improvement at the equipment which most needs it. As equipment that is most at-risk tends to suffer losses at ten times the rate, and with five
times the impact, there is huge value in knowing where to direct risk prevention efforts.
This value is important now and may become increasingly so. With fears that the world economy could slow in 2020, there could be even stiffer competition for capital expenditure within businesses across industries. Risk managers might face constraints on
capital spending for risk improvement,
making it more important than ever that
funding is targeted at where it can make
the most difference.
Predictive analytics, driven by quality data, can help businesses reduce their exposure to disasters before they happen. It allows targeting of resources to address the biggest risks. It can provide competitive advantage in the context of spending constraints on capital expenditure. Fundamentally, predictive analytics shows that vulnerability can be mitigated if we build resilience against potential threats.
For more information:
Account Engineer, Frankfurt Operations
FM Insurance Europe S.A. filial Luxembourg
Birger Jarlsgatan 27, SE 111 4S Stockholm
20. Box 3169, SE 103 63 Stockholm
Phone: +46 (0) 8 453 92 60
Mobile. +46 (0)70 64 53 262