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Sounding the Alarm: Early Warning Systems to Build Nature-Positive and Climate Resilient Businesses

January 30, 2023

By Sanjay Podder, Shalabh Kumar Singh, H. James Wilson, and Giju Mathew

Last summer’s heatwave in the UK and other European countries put a significant strain on the power sector.² It also lowered water levels in the areas’ rivers and canals, further exacerbating supply chain challenges. These waterways move more than a ton of freight annually for each EU resident, accounting for about an $80 billion contribution to the region’s economy each year.

That’s a significant number. And with life- and business- threatening climate events projected to increase in frequency and intensity, we see a growing urgent need for governments, companies, and other entities to leverage early warning systems (EWS) to help them prepare for these events and mitigate their damage. The need for urgent action was reinforced in the recently concluded UN Biodiversity Conference (COP15), where countries committed to the ’30×30′ goal to protect 30% of Earth’s land and sea by 2030.³

These tech-driven systems use state-of-the-art predictive models of climate change in concert with local weather pattern forecasts to help users make informed decisions in advance and react well to unfolding events in real time. These systems can be invaluable assets in the battle for climate-related resilience.

Yet according to a 2021 UNGC-Accenture survey of 1,232 CEOs across 113 countries and 21 industries, just 7 per cent of CEOs say they have mature early warning systems in place. And only 8 per cent are advanced in the practice of forecast-based scenario and investment planning for climate-related risks.⁴

What’s the holdup? Our research indicates that one of the key barriers to tapping the power of EWSs is a lack of understanding of the specific ways they can be deployed.
With that in mind, we offer a primer. Specifically, we explore, below, how EWSs can guide leaders’ actions to offset facility, supply chain, and regulatory risks of climate-related events in the short term, with wide-reaching sustainability implications over the longer term.

Facility risks

EWSs help facilities managers address location issues, adjust key production sites and infrastructure, people, assets, and planned construction locations, and build event-specific evacuation protocols.

Addressing facility risk begins with collecting sensor data to generate a smart map of a company’s physical assets and then combining the physical map with predictive climate models. The combination of these data sources feeds a predictive tool that forecasts which extreme weather events pose the greatest risk to a company’s facilities now and in the future, and how the facility will be impacted when such extreme events occur. The forecasting tool is driven primarily by AI simulations, in which the system treats each at-risk component of a business, such as its people, facilities, infrastructure, or utility providers, as an agent. The tool then uses artificial intelligence to model the potential impact of the forecast weather on each agent and then feeds the damaging scenarios and potential solutions to cross-functional teams of decision-makers. In fact, companies can use digital twins and metaverse technologies to create environments in digital form to better understand the impact of any possible environment catastrophe. For example, One Concern has developed a digital twin platform that allows enterprises to run climate models and simulate the impact of extreme weather and climate change on business operations. They combine trillions of data points with AI and machine learning, working with scientists to create virtual models of enterprises to get ahead of climate risks.⁵

To monitor their forests, Ingka uses aerial imagery and real-time mobile data uploaded to a GIS platform. Their location technology guides decisions about when and where to harvest their resources.

Endeavour Energy, one of Australia’s primary electric utility providers, is a prime example of how early warning systems can leverage intelligent technologies to bolster climate resilience. In March 2021, when Sydney was inundated by an unprecedented flood, Endeavour was plagued by customer outages and tremendous damage to their power infrastructure.⁶ Endeavour was already using a digital twin to accelerate its design process and fast-track ratings studies, but when the flood hit, they implemented a floodwater simulator to predict and monitor potential hazards before emergency crews were sent into flooded areas.

Once Endeavour realised the short-term predictive power of their technology, they began thinking about how their digital twin could serve as a climate early warning system. Working alongside their technical partner Neara, Endeavour used LiDAR (light detection and ranging) to discover hundreds of discrepancies between documented and actual locations of assets across their network. After updating their digital map, Endeavour used Neara’s physics-enabled software to simulate which assets were most at risk from extreme weather events such as high wind, extreme heat, flood, and wildfire. The analysis provided granular insight into details such as how cables might sag in hot temperatures, which feeders might be impacted first by flooding, and which poles were most likely to fail in high winds. Endeavour used the targeted insight to harden their network and continues to use their digital twin as a short-term and long-term early warning system as dynamic weather threatens their grid.

Supply chain risks

EWSs help chief supply chain officers (CSCOs) protect nature and biodiversity, create transparency, build resilience, support existing suppliers, and build a network of suppliers.

Artificial intelligence can also provide insights into a company’s supply chain risks. It helps companies track and predict disruption events across their operations and take proactive action. Before a crisis hits one part of its supply chain, a company can activate alternative locations or suppliers.

Rather than reactively transitioning as climate regulation falls into place, companies can plan for regulatory changes by combining AI simulations and natural language processing.

IKEA relies on more than 700 million cubic feet of oak, pine, birch, and beech every year – natural resources that take decades to reach maturity in tree form. Over the past five years, Ingka Investments, part of the Ingka Group that operates IKEA stores, has added geographic information system (GIS) technology to collect, monitor, and preventatively act on threats to the forests that it has acquired in the US, Romania, and the Baltic region.

The technology uses a wide range of climate data to track the health of tree and animal species, predict wildfire-prone areas, identify portions of the forest vulnerable to invasive insects, and manage the many other complex dynamics of growth and harvesting over lifespans that stretch to 140 years. To monitor their forests, Ingka uses aerial imagery and real-time mobile data uploaded to a GIS platform by field agents. Their location technology guides decisions about when and where to harvest their resources while protecting high-priority conservation and natural regeneration areas, reducing the risk of compliance issues. Ingka presents the information as a smart map, which distils the many variables and their interactions into a tool for decision-making and an illustration to create transparency for stakeholders. It also helps Ingka meet its biodiversity goals, such as obtaining certification from the Forest Stewardship Council.⁷

Asset and regulatory risks

EWSs guide compliance officers to build the funding reserves they will need to address regulatory transitions, and better address transition risks by taking actions geared towards compliance in advance.

Rather than reactively transitioning as climate regulation falls into place, companies can plan for regulatory changes by combining AI simulations and natural language processing. Using internal audit reports and press releases as inputs, intelligent tools can help forecast potential compliance risks that lie ahead. For example, the AI-based Event Watch platform from Resilinc Corporation, a supply chain resiliency solutions provider, identifies more than 25 different types of disruption events, including government regulatory actions.⁸ Early adopters of emerging climate regulation will not only reduce transition costs by making preemptive purchases of necessary resources and technology, they will reap the reputational benefits of a climate-minded organisation opting into sustainable business before it is required of them.

Effective use of natural language processing can also help a company comb the internet for press releases, news articles, and other documents that offer insights into their suppliers’ risk factors and regulatory challenges. As information that threatens a supplier is revealed, the system can forecast the impact and suggest ways to shore up a supplier’s resilience or help identify alternative suppliers. These forecasts can be updated in real time and customised to the needs of the user.

Partnering to multiply good outcomes

partnering

Individual company and government efforts to develop and deploy EWSs will build resilience against climate risks. However, the potential for economy-wide resilience expands exponentially when the EWS evolves through ecosystem partnerships. Bringing together businesses, startups, non-profits, academia, and governments is critical to share data and best practices.

A combination of data sources feeds a predictive tool that forecasts which extreme weather events pose the greatest risk to a company’s facilities now and in the future.

Consider: London-based Cervest’s climate intelligence product EarthScan helps enterprises, governments, and financial service providers to quantify asset-level climate risk at scale, helping them align their decisions and investments with a comprehensive view of climate-related risks. The company offers on-demand insights on hazards including flooding, drought, heat stress, wildfire, and extreme temperatures across multiple climate scenarios that look as far ahead as 2100. Importantly, Cervest has also established a Climate Intelligence Council that brings together experts from science, policy, finance, technology, and business to share knowledge and best practices and build resilience across economies.⁹

Climate change is a clear and present danger. There is no way to escape the consequences of past actions. The time to act is now. Businesses must prioritise the development of early warning systems to prepare for the challenges ahead. Mitigating the risks requires leveraging the power of technology and collaborating with ecosystem partners to build resilience against future crises.

The authors would like to thank Chase Davenport and Regina Maruca for their support.

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About the Authors

Sanjay Podder is managing director and the global lead for technology sustainability innovation at Accenture.