Content provided by IBM and TNW.

When Hurricane Harvey hit Southeast Texas in 2017, it caused $125 billion in economic damage. A recent review of local businesses in the area found that 90% lost revenue in the five-figure range due to employee disruptions, lower customer demand, power outages and/or supply chain issues. Those who suffered property damage experienced greater losses, with parts of the business shutting down for weeks and months at a time until repairs could be made.

Since 2017, there has been an average 17.8 weather/climate disasters per year only in the US. In fact, there have been 9 weather/climate disasters in 2022 alone with losses exceeding $1 billion each.

Greetings, Humanoids

Sign up for our newsletter now for a weekly roundup of our favorite AI stories delivered to your inbox.

Rising temperatures, floods, droughts, wildfires and other offshoots of climate change pose major challenges to economies and communities around the world. As a result, companies are feeling the pressure to adopt new strategies to reduce their long-term environmental footprint. But many have yet to prepare for the impact that climate change can and will have on their operations.

Many companies are already feeling the heat, experiencing climate-related asset damage and supply chain disruptions. According to a recent report of the World Economic Forum, global heat waves and other extreme weather events could also spike the cost of raw materials for manufacturing, inevitably leading to massive revenue losses across all sectors.

With such a high risk, the question is, why have so few companies prepared for the potential impacts of climate change?

The complicated world of climate data

While an overwhelming majority of companies have plans for cyberattacks and Covid-19, the World Economic Forum Global Risk Report 2021 found that extreme weather, failure of climate action, and human-caused environmental damage are in fact the top three most likely risks to businesses in the next decade. Yet many still lack clear strategies and risk assessments to guide decision-making.

“One of the biggest challenges facing overall business operations is that companies are still becoming familiar with the many variables involved in collecting climate data,” said Miguel Modestino, an assistant professor and director of the Sustainability Institute at New York University. .

Indeed, keeping track of climate data requires historical weather data, sensors, intensive manual work, computing power, as well as in-house climate and data science skills. Even if you can capture this data, the problem lies in being able to combine and compare all the different variables to get one big picture of what’s happening on the ground.

Geospatial analysis is key to unlocking the potential of climate data.

According to Hendrik Hamann, Chief Scientist for Future of Climate at IBM:

For example, to understand the economic damage of a flood, one has to combine information about flood risks with information about roads and elevations, or many other types of information to understand the overall impact on business.

Once you capture climate data, the next challenge is understanding how to extract valuable insights from this information and actually apply it to your business.

An EY study found that only 41% of organizations conduct scenario analyzes of climate-related risks. This means that, in the increasingly likely event of a weather-related disaster, many organizations do not have a clear picture of what the potential risks, costs and action plans would be. Without this understanding, prevention measures, budgeting and other critical decision-making become a gamble for business leaders who must present this information to investors and other stakeholders.

“We’re sitting on this mountain of information, but we’re just looking at the tip of the iceberg. All this valuable data is available, including observations about our planet Earth, but we don’t use it to make better decisions,” explains Hamann.

Reducing climate impact with new technology

Geospatial analysis is key to unlocking the potential of climate data, but these insights are based on vast amounts of complex and disparate data types, including satellite, GPS and historical weather data and images. The use of AI and machine learning has great potential to help companies access and analyze these datasets in a way that is more manageable.

“AI also allows companies to develop advanced models that use machine learning to very quickly calculate the environmental impact of a given set of business activities,” explains Modestino. “Having efficient machine learning models can help optimize their operations to maximize profits while maintaining a certain climate target.”

IBM recently launched its Environmental Intelligence Suite (EIS) that brings together a wide variety of weather, climate, AI and operational technologies into one software-as-a-service offering that businesses can use to better plan and respond to climate risks.

Map out the potential risks of your business activities.

A unique capability within this suite is a geospatial analytics engine developed within IBM Research, which helps provide insight into complex geospatial data sets in a way that is more easily accessible and can be combined with broader business technologies and data. This can help companies efficiently understand and analyze geospatial data to predict the risk and potential impact of emerging climate and weather threats on their business.

“When we think about satellite observations of the Earth, we think, ‘how can it be analyzed?’, or ‘how can we understand natural phenomena such as tree growth, vegetation growth, and how much carbon is stored in them,’ Hamann says.” This is all covered. by geospatial analysis.”

For example, if a utility company has tens of thousands of substations that are used to supply customers with electricity, the climate impact could raise the following questions: Which of our asset locations are most at risk? How can those sites be prepared to withstand the impact? How are the investments distributed? The ability to analyze geospatial data keeps companies informed of potential risks and prioritizes them while making actionable business decisions.

How to start?

Clearly, developing clear strategies for extreme weather and climate change is no longer just for a rainy day. They will become the key to enabling companies to function, operate and even grow.

The first step is to identify the potential risks of your business, from resource scarcity to the potential for logistical disruption.

The next step is to consider the possible opportunities. How can changing your sourcing/manufacturing/distribution strategies lower your risk of climate change disruptions and improve your bottom line? How can these changes also contribute to your company’s longer-term sustainability strategies?

As it continues to affect populations around the world, it is also becoming increasingly clear that a warming planet poses an imminent threat to business operations. Advanced technologies and methods, such as geospatial analysis, are still in their infancy and therefore we expect much more room for innovation in the coming years.