Following this, we quantified the wide-ranging but site-specific climate risks the manufacturer faced and measured the impact of mitigations on these risks, building a portfolio view of risks and how the organization could optimize them.
The work called on our Loss Probabilistic Impact Quantification (Loss PIQ) framework to evaluate future risks using climate change indicators. The framework generated actuarial forecasting of likely losses under long-term time horizons accounting for different climate change scenarios.
We then used our Connected Risk Intelligence (CRI) portfolio optimization analytics to identify how the manufacturer could mitigate physical climate risks over the next 25 years.
CRI gave the business a framework to scrutinize the costs and impacts of mitigations in a data-driven and interactive way, evaluating risks and how to address them optimally over time. It generated strategic insight that set a path to cost and risk savings on both new and existing manufacturing sites, better protecting financial performance from climate risks.
Key findings included:
- A potential 54% increase in cost and a 12% increase in risk by 2050 under an adverse climate scenario
- Some risks were on a downward trend, and therefore could spare the business from unwarranted investments. For example, while one site was at risk of flooding, this threat was set to diminish in the medium-term, enabling the business to redirect resources away from flood mitigation at this location
- A key manufacturing site was highly resilient and existing mitigations the business had already deployed were efficient.
The 6-step process we worked through with the organization:
01
Previous engagements
The existing work completed by WTW was consolidated, including the impact of climate change on the business's risk (Risk Registers), the Climate Adaptation Guide, and risk engineering reports.
02
Questionnaires
Questionnaires were produced based on the previous climate change risk register engagements. These were shared with sites to validate mitigations and help quantify risks.
03
Gross Loss Modelling
Utilising natural catastrophe models, climate quantification modeling and actuarial modeling techniques, gross loss forecasts were generated for all risks and time horizons being analysed.
04
Mitigations
Mitigations identified in the questionnaires were applied to the gross loss models to find the residual risk after mitigation. These have an annualised investment spend associated with them.
05
Insurance
The current insurance structure in the business was then applied to the risks being analysed. This meant we could see how the mitigations impact the risk with transfer mechanisms in place.
06
Connected Risk Intelligence
A cloud of alternative portfolios was generated, which combines all of the different risks and the possible mitigations. By looking at millions of different combinations recommendations can then be made.
The impact: Lower costs and risk, better long-term financial performance
Decision-makers now have a framework to pinpoint effective mitigations to strike the most efficient tradeoffs between implementation costs and anticipated reductions in risk. The business can identify where it should allocate resources for the most financial impact.
Crucially, the framework for helping the multinational achieve its financial objectives through data-driven insight is both repeatable and auditable. The business can look ahead to allocating resources more proactively, efficiently and with greater confidence, because it calls on data and analytics and a robust methodology.
Our collaborative approach to the initial study has supported more effective internal communication and a shared risk-aware culture. Different business functions, including sustainability and risk management, now have a united view of both critical risks and the most effective steps to address them.
The ability to present a cohesive, data-driven strategy is also enhancing investor communication on both the manufacturer’s approach to climate risk and protecting financial performance.
Next steps: Wider data-driven risk governance and strategic resource allocation
The multinational organization is now looking to apply the data-backed decision-making framework across its global operations, potentially integrating it within its core risk management protocols. This will help the organization take wider advantage of data-backed risk governance, regardless of changes in climate, trading conditions or leadership.
We continue to work as a trusted partner, with the organization now looking at using outputs from the CRI framework to better communicate risk management strategies to external stakeholders, including investors and employees. It aims to build deeper trust by demonstrating an auditable commitment to long-term sustainability and protecting profitability from climate change impacts with our ongoing support.
The outputs of the work we have undertaken form a key aspect of a broader enterprise resilience dashboard encompassing climate and other strategic risks the client is working on.
To better identify, quantify and manage your risks and opportunities, speak to a Willis Risk & Analytics specialist.