How Can Emerging Technologies Catalyze the Decarbonization Journey?

Digital technologies are one of the best hopes in the effort to achieve net zero by 2050 and offer businesses the opportunity to bridge the gap between net-zero ambitions and actions.

The use of Internet of Things (IoT) devices, the cloud and Big Data analytics can target improving efficiency and lowering the emissions of factories, buildings and other energy-intensive assets. Digital twins, artificial intelligence (AI) and machine learning (ML) can also support minimizing carbon footprints across industries.

Organizations continue to be inundated with new technologies and the infinite possibilities they present, but experts warn that businesses risk being lured into the hype cycle. Businesses must make critical decisions about where and how best to deploy these technologies, and avoid getting distracted by “bright and shiny” things, says David Rae, Partner, Climate Change and Sustainability Services at EY.

Rae urges business decision makers to buy solutions—not just technology. “The focus should be on what challenge you’re trying to solve and why. Emerging technology is part of the answer; it’s not the answer. It’s about thinking bigger,” he says.

Sean Jones, Microsoft’s Chief Sustainability Officer in Germany, explains that the biggest challenge to decarbonization lies in an organization’s impact beyond its factory and office walls, known as scope 3 emissions.

“Addressing this requires decarbonization at a systemic level, including renewable power replacing fossil fuels; advances in hydrogen and battery technology; the electrification of every business, encompassing e-mobility, steel, cement and chemical manufacturing; and integration of digital technology to securely manage the energy grid, balancing supply, storage and demand,” says Jones.

The use of technology is critical to ensure that what matters is measured and that the right data is shared, emphasizes Gunther Rothermel, SAP’s Co-GM and Chief Product Officer for Sustainability.

“Businesses that aim to decarbonize must measure and report scopes 1, 2 and 3 emissions with accuracy,” says Rothermel. “Managing diverse emissions across a supply chain with different data quality is a challenge for any one company. Industry coalitions empowered by a sustainability data exchange enable the transactional carbon accounting needed to reach substantial decarbonization across supply chains.”

Digitalization and sustainability initiatives promote deeper, broader transformation when they are successfully combined. By processing data more efficiently, identifying challenges faster and testing solutions immediately, even hard-to-abate sectors can become agile and responsive.

“So many sustainability initiatives are good for both the planet and profit. The data used by businesses today is only the tip of the iceberg,” says Christina Shim, VP and Global Head of Product Management and Strategy, IBM Sustainability Software.

Digital tools are now available to help companies connect to data at the source and standardize it on a common data model aligned with globally accepted standards, such as the Greenhouse Gas Protocol for emissions, ESRS and GRI standards for water and waste and the WBCSD Pathfinder for Product Carbon Footprint.

“Centralizing and standardizing data according to these standards is accelerating progress and bringing greater accuracy to reporting and, ultimately, to the progress companies can make toward their sustainability goals,” says Brandon Potter, Microsoft Principal Group Product Manager, Microsoft Cloud for Sustainability.

What was once emerging tech is now everyday table stakes to inform and drive business and sustainability goals. IoT sensors have multiple use cases across industries, including agriculture, farming, manufacturing and transport. AI, in particular, has the potential to integrate with all other technologies and help organizations make better, faster decisions that hasten progress toward low-carbon and net-zero goals.

AI can translate collected data into actionable insights and feedback loops to make insights more useful over time. Collecting and analyzing data from sensors and GPS trackers helps manage resource-intensive tools essential to many industries, increasing productivity and identifying efficiencies that can reduce operational impacts.

For example, a new foundation model being developed by IBM and trained on public, NASA-collected geospatial data could convert satellite data into high-resolution maps of floods, fires and other landscape changes. Such a model could potentially help businesses with planning, operations and risk mitigation, or be further fine-tuned to a specific need.

“Every day, my team works with customers around the globe and across industries. Ultimately, the common issue facing all of them is a data issue.” says Potter. “True and accurate emissions reporting requires data from all aspects of the business. Today, this data is siloed and not in a common structure.”

While experimentation is encouraged, one of the biggest risks to progress is blindly committing to immature technology. This is why EY’s value-led approach reframes how businesses consider how they create and derive value from sustainability.

Many investments related to wind and solar power, battery technology and e-mobility have reached a level of maturity where experimentation is no longer required.

“The goal here is to think through what a long-term commitment to specific innovation paths looks like, and allow that to grow organically,” says Ben Taylor, Global Strategy and Markets Leader, Climate Change and Sustainability Services at EY.

Early adopters risk failing fast—but not usually in a way that favors agile startups. After securing board-level buy-in, failing to deliver can lead to writing off technologies that may have potential later in the business journey. Taylor cites an example of a consumer products company that was looking at technology to reduce the density of plastics in bottles.

“The technology had several benefits, from cost-effectively reducing virgin plastic to carbon incentives. But the technology just wasn’t mature enough at the time,” says Taylor. “They rolled out the technology for about three years before giving up on it. Now, the technology is more mature, but it has a bad reputation within that specific business.”

The bottom line, according to David Lindop, EY Global Consulting’s Chief Data Officer, is that many emerging technologies that were considered science fiction just five years ago have matured at an unprecedented rate and are now ready for application.

“Sustainability may be the first use case as a driver for change, but these technologies will have an impact way beyond decarbonization, such as on cost, efficiency, waste reduction and, ultimately, business resilience,” says Lindop.

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