Data-driven insights are key to managing climate risk

Combatting the effects of climate change is largely considered to be the most pressing challenge of our time. More intense heatwaves, rising sea levels, more frequent floods and droughts are some of the perils that societies, governments, and industries must prepare for if they are to protect their people operations now and into the future. 

And, according to the C40 Cities Climate Leadership Group, an organization of cities around the world focusing on fighting the climate crisis, the future may not be particularly rosy with regard to climate conditions and their impacts on communities. The group says that more than 200 million residents across 350 cities around the world are experiencing summer temperature highs of over 35°C (95°F), and that number could grow to 970 cities with 1.6 billion people by 2050. 

As climate risks become more interconnected and complex, they require more comprehensive analysis, planning, management and reporting. To create the insights needed to meet those requirements, organizations must rely on high-quality data to assess the climate threat. 

Climate data, which is starting to be incorporated more regularly into risk management strategies, helps businesses identify and assess risks across the organization and prioritize adaptation measures that can strengthen resilience against potential natural hazard events, at high-risk locations. Basing such decisions on reliable data increases confidence in the efficacy of efforts and investments made to reduce the organization’s greatest climate risks and vulnerabilities.

Moreover, high-quality data will support in developing the forward-looking scenarios that show organizations how their exposure to different climate perils may evolve over time. That information can be modelled on different scenarios developed by the Intergovernmental Panel on Climate Change (IPCC) to reveal best- and worst-case outcomes. These are the types of insights necessary for developing adaptation strategies.  

The increased focus by regulators, societies and global institutions on climate risk and adaptation actions, and the continuing development of reporting requirements also create demand for high-quality climate data. The regulatory burden is widening, as the European Union, for example, calls for the number of companies required to comply with the Corporate Sustainability Reporting Directive (CSRD) to more than quadruple by 2025. 

Managing a company-wide risk 

While sustainability managers may find themselves at the front lines of sustainability reporting regulations, the responsibility for strengthening resilience is organization-wide, and therefore requires strategic management in order to embed into the day-to-day business operations and future planning. Insurance managers, for example, must ensure that adequate coverage is in place, while investments in sustainability have to pass muster from the finance department. Operations, supply chain management and site managers all have a role to play, as does the C-suite, where, ultimately, the responsibility lies for the long-term success of the business. 

Using forward-looking data as part of an integrated approach to climate risk, that spans all business functions, makes the outcomes relevant multiple stakeholder groups, and is a must-have tool to manage climate risk not only strategically but also operationally. The challenge is understanding the climate data, and how to incorporate this in the risk analysis to generate insights necessary to build resilience.  This calls for data that incorporates the following attributes to allow for confident decision-making throughout the organization: 

• Consistency
  Businesses have to consider the risks as they are today, as well as their evolution with time under the different climate scenarios. Consistency of data that includes the latest observations and modelling to assess current natural hazards, and their evolution in the future, provides a comprehensive view of physical exposures to climate change comprising both present-day and future risks.
• Transparency
  When businesses make use of climate data to understand and respond to their climate risk exposures – whether driven by regulatory pressure or strategic decision-making – they need to understand that data. This provides context and enables clarity when evaluating different sites and options for adaptation measures. By providing transparency on how the data was formed, assumptions that are made in the methodology, and any limitations to the data, organizations can be more confident that money is well spent before adaptation measures begin to be implemented.
• Flexibility
  The climate data should accurately capture the complex relationship between risks. Certain hazards may necessitate the use of multiple metrics to evaluate their effects on various aspects of the value chain. For instance, when assessing the impact of heat, distinct indicators should be employed to analyse its potential impacts on processes, employees and equipment.

The importance of data quality

Alongside climate data, high-quality data related to the organization’s assets, suppliers and other factors is required for insightful analysis, enabling an effective assessment of climate-related risks and a clear understanding of the most efficient mitigation measures.

The risk assessment process is iterative, with additional data added with each iteration, allowing a more complex view of risk. While it may be relatively straightforward to source data relevant to the organization, determining the relevant natural hazards and climate change data can be quite complicated.

Conventional tools are being adapted to consider climate change implications, but forward-looking, or scenario-based data cannot predict what an extreme weather event will look like. Forward-looking climate data is produced by running climate models that are driven by assumptions about future global emissions and land use. These assumptions are used to develop scenarios describing the future state of the world. Because of the uncertain nature of these assumptions, which are influenced by human behavior, geopolitics, and technology, it takes multiple scenarios to understand the plausible range of risks that could evolve. 

Climate data is not perfect. In fact, there is inherent uncertainty in it, due partly to assumptions in the evolution of global socioeconomic factors and how they may affect emissions. In addition, models have limitations, as scientific understanding of climate risk is ever evolving. Climate data is best used for assessing risks in comparative and hypothetical terms – to understand trends in climate risks in particular areas, to compare locations for adaptation needs, and as the basis for better informed scenario analyses. 

To help businesses meet these climate risk challenges, Zurich has developed its own climate data set which is used by the insurer to manage its own risks. The team at Zurich Resilience Solutions combines this with our customers’ data to carry out a climate risk analysis of their global asset portfolios, as well as site-level risk assessments that include scenario analyses and recommendations for adaptation solutions.