How to navigate risks and win the race

On the slopes, athletes must make split-second decisions to avoid hazards presented by everything from ice to unexpected moves from competitors. In a rapidly changing world, businesses must also be decisive and react quickly when risks emerge.

First person perspective of navigating your route while skiing.

The scale of risks currently facing corporates can feel overwhelming, but the world of snow sports holds a surprisingly simple blueprint for effective risk management: prepare rigorously, analyse all the available data and train often. It’s a process that enables split-second decision-making when hazards emerge and holds important lessons for businesses.

Companies have been taking risk management increasingly seriously because of the growing impact and financial losses caused by everything from devastating hurricanes to Covid-19. Changes to the risk environment have been accelerating, putting climate, geopolitics, cyber and a host of other risks firmly at the heart of the exec’s agenda.

As a result, the risk management strategies of some leading companies now reflect those seen in elite sports. Global pharmaceutical company Takeda discovers and delivers life-transforming treatments, guided by its commitment to patients, its people and the planet, which improve the quality of patients’ lives. Pam Joshi, Head of Insurance and Risk Management at Takeda, says the company’s approach and processes for managing risk align closely with those of high-performance sport:

1. Preparing rigorously

Alpine skiers prepare their bodies in the gym for the rigours of ski racing, but also ensure their equipment is tuned to perfection. Takeda takes a similar approach to building its resilience and preparedness. Takeda’s culture discourages silos and encourages a smooth flow of information through the business. There are a number of individuals managing risk across the organisation, and its Global Insurance function manages a large insurance programme and operates a captive insurance company to assist with the transfer and management of Takeda’s risks.

2. Analysing all available data

Elite snow sports athletes gather data to help them navigate the hazards of racing and perform at their best. Takeda gathers data for the same reasons and uses it to model exposures such as cyber and supply chain risk. “When it comes to taking calculated risks,” explains Joshi, “you’re as good as the data you have. So, being in a position where our data is as accurate as possible to enable a deeper understanding of risk, through qualitative and quantitative analysis, prepares us to make informed and better decisions about risk.”

3. Training often

Skiers train regularly to test their performance and reactions in a variety of situations. Similarly, Takeda frequently tests a number of scenarios to identify, understand and manage critical risks. Joshi explains: “We have to factor in emerging threats such as climate change. Climate impacts will continue to change, so we regularly bring climate-related (topical) scenarios to the table. We select scenarios based on the current/emerging risk profile.”

These three steps ensure snow sports athletes are agile enough to deal with the risks of the race but can also do the same for corporates. Joshi explains: “Skiing is very reactive to the environment you’re in and therefore you have to make very, very quick, timely, measured and accurate decisions. Similarly, if you’re operating a large global values-based company, you have to remain agile enough to navigate through the risks very quickly. So, decisiveness is key.”

Making the most of data

Catherine Tillyard leads the catastrophe (Cat) modelling team at McGill and Partners, having completed her PhD in Volcanology and modelling the volcanic risks to small island states in the Caribbean. Cat modelling gained traction as a way of identifying the impact of natural hazards following events such as Hurricane Andrew in the early 1990s. It has since evolved to include risks such as cyber, terrorism and pandemics.

In the same way that video analysis and ski models help athletes make their preparations for the snow sports season, modelling enables companies to understand the likelihood of an event taking place and the likely financial loss so they can make better informed decisions about their insurance cover. Tillyard explains: “It’s about doing the groundwork and that preparation so that when you’re on the slopes, or when a hurricane is about to hit, you know what you are doing, you’ve got all the information to hand, and you can act decisively.”

There are some key similarities between how athletes and businesses make the most of data:

1. Understanding the course

Athletes and their coaches gather data not only on weather and snow but information specific to the course they’ll be on. Risk modellers take the same approach, modelling risks for specific assets in specific regions. McGill and Partners worked with Renew Risk to develop the first commercially available Cat models specifically for offshore wind farms. Tillyard explains: “There were concerns about insuring wind farms in regions like the coast of Taiwan, where seismic and cyclone risks are significant. However, once those risks are quantified, they become manageable and can be priced accordingly.”

2. Informing real-time decisions

Skiers use data to build their understanding and underpin the split-second decisions they have to make during a race. Tillyard explains: “Data plays a key role, whether it’s training analytics for athletes or hazard modelling for insurers. Snow sports are very much based on real-time responses, which is where cat modelling is now heading. Skiers have to read the weather and terrain and make split-second decisions. Equally, we can increasingly provide real-time analytics for businesses and insurers, so that they can make more informed, live decisions.”

3. Modelling weather impacts

Skiers collect data on snow type, temperature and weather, which are all variables in ski racing that can affect their performance. Corporates gather data to tackle their own climate challenges. Tillyard explains: “The changing climate is altering the frequency and severity and the geographic spread of natural-hazard events. The science is evolving and cat models need to evolve to keep pace and reflect that. They are often built on historical data, however, clients are increasingly asking for forward-looking projections to understand what a future loss might be.”

Like athletes, Cat modellers have access to huge amounts of data, and AI and machine learning are transforming the way they can process and learn from those data sets. It presents the possibility for real-time modelling that enables companies to see what’s happening during an event, take mitigation steps early and direct resources to the right places in the immediate aftermath.

Mastering risk

There are many parallels between a skier navigating a treacherous slope and a board navigating a volatile market. The principles of rigorous preparation, deep data analysis and frequent scenario training are no longer confined to the ski course; they are essential for businesses to survive and thrive.

As exemplified by Takeda's proactive risk culture and the evolution of real-time catastrophe modelling, businesses have the tools to not only anticipate and quantify risk but to react with the same agility as an elite athlete. By embracing this mindset, learning from every run, adjusting to changing conditions and making decisive, data-informed choices, the corporate world can not only manage risk but turn it into a competitive advantage.

Pam Joshi

Head of Insurance and Risk Management, Takeda

Catherine Tillyard

Partner – Treaty Reinsurance, McGill and Partners