How life sciences companies are using analytics to ensure their risk functions are on the frontline of the battle to reduce costs and enhance value. Life sciences businesses face huge pressure to become more efficient Supply chain disruption, manufacturing complexity and economic headwinds such as high inflation all loom large. Tighter monetary policy has increased the cost of capital. Against this backdrop, saving money and enhancing value is a crucial priority for life sciences leaders. |
By Neil Emerson | GB Practice Leader – Life Sciences at WTW Risk analytics could be a golden opportunity. At first sight, insurance spending looks an unlikely candidate to deliver the additional value that life sciences companies are searching for – at least not without increased hazard. Reducing insurance cover may well result in lower premiums, but it will typically expose the business to additional risk; that may not be something that risk managers are comfortable with. However, that seemingly obvious catch only applies when the business – as is common – looks at lines of coverage individually. By taking a portfolio approach to risk instead, it may be possible for life sciences businesses to identify hidden opportunities to unlock value. This isn’t something that businesses in most industries have traditionally been good at. Insurance spending decisions are often siloed, with individual risk managers in different functions and different parts of the business acting in isolation. However, by taking a step back and thinking holistically about the risks that the business is exposed to, life sciences companies may be able to achieve something counter-intuitive: it may be possible to restructure lines of insurance so that at the overall level, both cost and risk start to fall.
The portfolio approach to risk management To make that adjustment, think of your risk management activity as analogous to investment management, where considerations such as correlation and diversification are routine. The goal here is to apply the same techniques to risk management – diversifying across risks and choosing combinations of transactions that deliver the best value. This will enable you to deploy your risk capital more effectively and efficiently. To take a simple example to illustrate the point, imagine a scenario in which a life sciences business is facing higher property and casualty (P&C) premiums. In siloed organisations, the P&C risk manager then faces the difficult choice between increasing insurance spending or reducing coverage. A holistic business, by contrast, may be able to identify other lines where premiums offer better value; increasing coverage there will offset reduced coverage of P&C risk and maintain overall risk exposure, perhaps even lowering total spend. Similarly, organisations can miss opportunities to benefit from the relationships between different types of insurance. Some risks are highly correlated – that is, an issue in one area that results in losses is very likely to be accompanied by an issue elsewhere that amplifies the problem. Equally, other risks are highly uncorrelated – they rarely occur at the same time. Identifying these relationships creates opportunities to manage risk accordingly, maximising value. Moving to a portfolio approach also enables better-informed conversations about time horizons for risk management. Life sciences companies with a holistic view of insurance may, for example, be able to identify risks that rarely occur consistently. In which case, traditional annual insurance in the commercial insurance market may not be the right solution. In short, the goal of this new form of risk management is to think much more intelligently about connected risk. Your business should be able to move beyond the conventional insurance playbook – with multi-line, multi-year risk management, say, to embrace concepts such as parametric cover, or a better-informed debate about retained risk. And in doing so, there is significant potential to unlock value.
Why analytics is the key The goal should be to secure a more granular and precise understanding of the inter-connectedness of your total exposures and costs. That work means calculating for each line both the cost – premiums and retained losses – and the exposure in terms of what is retained and what is transferred. Modern analytics tools then enable life sciences companies to model different approaches – to assess overall cost and exposure for an almost limitless number of different combinations of individual risks. What emerges from such analysis is effectively an efficient frontier of insurance – a dashboard of where variances from the line will result in either higher cost or increased exposure. It provides a holistic assessment of the risk management combinations that deliver the greatest value. Different life sciences companies will naturally take different views of the conclusions of such exercises. Some may be more comfortable accepting risk in a particular area of the business than others. Some may be more focused on cost. Analytics won’t provide a one-size-fits-all answer to risk management; rather, this work provides business leaders with connected risk intelligence – much more sophisticated insights as the basis for decision-making.
Theory into practice However, armed with the connected risk intelligence generated by modern analytics tools, life sciences companies will be in a much stronger position to challenge brokers and insurers alike. They provide a means to put value at the centre of the conversation - at renewal, certainly, but on an ongoing basis. Indeed, there’s another benefit on offer here too. Using analytics in this way will help align risk with finance, particularly as the whole business starts to see the function as driving value rather than managing cost. This is about contributing to overall organisational resilience. |
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