How data is playing a central role in reducing supply chain emissions

Tackling climate change has become a central priority for governments worldwide, and industry is feeling the pressure. Thanks to sustainability goals and changing consumer attitudes, companies cannot afford to sit on the sidelines when addressing climate change. Indeed, environmental, social and corporate governance (ESG) is no longer a cost center but a business imperative.

Supply chains are the key to fighting climate change, since the emissions they generate dwarf those from the rest of the typical organization. Research from Accenture highlights that supply chains generate 60% of global carbon emissions. 

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What’s more, this figure is likely understated, due to the difficulty of measuring “Scope 3 emissions,” those generated indirectly up and downstream in the value chain by other parties. Transparency is the real issue here, as companies lack insight into their own ripple effects.

Based on the recent rush of signatories such as shipping giants Maersk and Ocean Infinity to Amazon’s Climate Pledge, yielding a 600% growth in the number of signatories, we can thankfully see changing attitudes even within the logistics industry. These actions cannot come quickly enough. A 2021 Canadian National Inventory Report revealed that freight transport emissions have increased by 154% since 1990.

But how can they possibly make good on their pledges? Data collection and analysis is increasingly playing a role in helping companies lower emissions and conform to industry and regulatory standards. Novel data use cases are springing up every day, pushing industry leaders to question how they can use their data better.

Extrapolating datasets to minimize carbon footprints

Condition monitoring data offers a fascinating example of local datasets with a global impact. Typically, IoT devices track package conditions and transmit them to logistics teams and stakeholders in the supply chain. 

At first glance, this information seems like it would be only useful on a local and package-specific level. However, data extrapolation is delivering a significant impact. Stakeholders are using freight condition data to draw conclusions about vendor performance and reveal route-related inefficiencies. 

For instance, packages that routinely arrive close-to-acceptable-condition thresholds during transport can reveal problems with route planning procedures. Customs sheds and storage facilities along the route can be inadequate. Excessive traffic along the route might be sabotaging storage conditions and increasing emissions. Deeper pattern analysis can answer such questions as, will the shortest route create a significant volume of emissions and create additional ESG costs down the line? For instance, the shortest route might incorporate emission-heavy modes of transport or storage facilities that draw inordinate levels of energy, increasing that route’s emission implications.

“Especially given the ongoing bottlenecks, supply chain predictability is becoming more important by the day,” says Niko Polvinen, CEO of Logmore, a condition-monitoring solution provider. “Shipment location and condition data reveals how efficient each step of the supply chain is. Not only can you monitor package-level data, but you can also draw conclusions about vendor service quality and route efficiency.”

When linked to ESG initiatives, condition-related data significantly reduces a company’s supply chain footprint. “Let’s say you have a vendor that routinely delivers goods in an unacceptable state, or that gets stuck in transit for weeks on end,” says Polvinen. “You’ll incur additional shipping costs to replace those damaged products, ultimately doubling your carbon footprint. Condition monitoring data can tell you who is performing the best, helping you reduce costs, while lowering the emissions that are attributed to your shipments.”

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By applying creativity in the data analysis process, companies are able to draw unconventional conclusions about the state of their emissions. But it isn’t just supply chain companies that are paying close attention to data. Governments are getting in on the act too.

Speeding up emission curbing goals

Governments are waking up to the power of data analysis to curb emissions. Recognizing the role of supply chain companies in this task, the government of the Netherlands mandates that logistics companies of a certain size share their data with a national database. The idea is to help stakeholders build emissions-related knowledge and leverage data for further analysis.

The transparency that such initiatives bring played a role in a Dutch court recently ordering petroleum giant Shell to speed its emissions curbs. As data analysis techniques become more powerful, the court reasoned that original timelines needed revising.

Data analysis is also having effects on carbon trading markets. Thanks to better data governance processes and design, these markets are helping companies purchase the appropriate amount of credits to offset their emissions. 

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A study by the EU’s Proceedings of the National Academy of Sciences revealed that the EU Emissions TRading System (ETS) saved 1.2 billion tons of CO2 between 2008 and 2016 (3.8%), relative to a world without carbon markets. This amount is half of what EU governments promised to reduce under their Kyoto Protocol commitments, mind you.

Better operations, practical and artificial

Data is also speeding the advancement of technology that promises to disrupt the supply chain. The rise of smart vehicles has prompted supply chain firms to explore self-driving trucks and incorporate tactics such as platooning. Autonomous trucks can follow each other closely for long distances, reducing drag and fuel consumption, essentially forming a platoon. 

Pilot programs conducted by USPS and TuSimple found that these tactics generated 13% fuel savings over 160,000 miles in Arizona. This is an unheard of level of savings.

Greenifying fuels is also a major focus area for suppliers. While full electrification is at least a decade away, the rise of alternative fossil fuels such as green methanol points to the impact that the combination of data and ESG initiatives have had on the industry. Shipping giant Maersk currently runs 12 ships on green methanol, drastically curbing emissions.

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Carbon Recycling International CEO Ingólfur Guðmundsson says, “Producers of synthetic materials are beginning to capitalize by gradually shifting to renewable raw materials like eMethanol, competitively offering greener products.” He adds that such measures allow producers to achieve outsized environmental and economic benefits compared to costs.

Data crunching is also helping firms train AI algorithms to incorporate emissions-related goals when designing processes. The investment is worth the cost. A study by PWC notes that AI can potentially reduce emissions by 2.4 tonnes (2.65 tons) of global annual CO2 equivalent emissions by 2030. For the sake of scale, that number is equal to the projected combined emissions of Australia, Canada, and Japan in that year.

Leveraging AI to assist in analytics blind spots, such as Scope 3 emissions and developing an emissions baseline, is the way forward. It will require significant investment. However, the cost savings from reduced emissions ought to remove any concerns companies might have. AI can also demystify sources of emissions created by the decentralized nature of most companies’ supply chains. 

Data-backed conclusions from such initiatives will increase collaboration amongst industry peers, which is key to creating sustainable change.

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Data is leading to a green future

Data underpins every advance the supply chain industry is witnessing. Soren Skou, CEO of Maersk, is aware of the size of the challenge and reflects the commitment of his supply chain peers. 

“To drive the massive scale-up of green fuels, we all must move now and take action,” he says. “If we are meant to see changes this decade, we cannot afford to wait, and in that context, we look forward to joining The Climate Pledge, an opportunity to team up with some of our major customers, learn from them, and share best practices and solutions.”

Ralph Tkatchuk is the owner of TK DataSec Consultancy.