Over the past 18 years of my career, I’ve navigated through the intricate world of technology, digital platforms, and data analytics; driven by an insatiable curiosity for innovation. That journey has led me to a mission close to my heart—sustainability. 

At Terrascope, we’re galvanising the very essence of technology and data analytics to tackle one of the most pressing issues of our time: carbon emissions in global supply chains. A recent report by Boston Consulting Group and the World Economic Forum starkly illuminates the scale of this challenge, revealing that just eight supply chains account for more than 50% of global emissions, with the majority embedded in base materials, agriculture, and transportation of goods worldwide This alignment of technology, data, and environmental stewardship represents more than just a professional venture for me; it’s a personal commitment to leaving the planet better than we found it, and to keep the planet habitable for all. 


What is data annotation, and why should startups in APAC care?

The dual nature of technology

Technology may frequently be viewed as an environmental culprit. Data centres consume massive amounts of electricity, and the e-waste generated from rapidly obsolete devices continues to grow. The global IT sector as a country, would rank as the third largest country on emissions, after the US and China, according to a recent report by the Climate Impact Partners. 

But while some may see technology as part of the problem, it’s also a substantial part of the solution. Artificial Intelligence (AI) is pivotal in this context. Its capabilities in data analysis, optimisation algorithms, and predictive analytics can make sense of the complexity that is inherently tied to carbon emissions. Through machine learning algorithms, we can analyse trends in energy consumption and emissions at a scale previously unimaginable, allowing businesses to make smarter, more environmentally friendly choices.

The complexity of supply chains

For businesses, particularly those with vast supply chains, the challenge lies in Scope 3 emissions, often accounting for over 90% of a company’s carbon footprint, according to a recent BCG report. These emissions sources are particularly vexing because they are outside a company’s direct operations yet remain the company’s responsibility to accurately measure and reduce.

The Scope 3 emissions challenge is compounded by data, or more precisely, the lack of data transparency. Large enterprises might have state-of-the-art systems to track emissions, but their supply chains often include numerous small and medium-sized enterprises (SMEs) that do not have such capabilities. This lack of data isn’t just an inconvenience; it’s a significant roadblock to achieving a comprehensive emissions measurement and reduction strategy. 

The Greenhouse Gas (GHG) Protocol provides companies with the ability to use industry averages, proxies, and other data sources for calculating emissions. However, without the right tools and resources, the process of measuring and managing emissions is an extremely complex task that leading businesses still struggle with today.

Fortunately, Artificial Intelligence and Machine Learning provide a bridge to traverse this cavern. These technologies can estimate the likely emissions from smaller players in the supply chain, filling in the gaps in your Scope 3 emissions landscape. By leveraging AI capabilities that process both structured and unstructured data, companies can extract valuable insights about their suppliers’ sustainability practices or lack thereof and establish where to evolve their data collection strategy.

The vital role of baselining

Without knowing where you stand, moving forward becomes a journey without a destination. That’s where emissions baselining comes into play: this involves establishing a reference point for measuring and tracking emissions, which is essential for effective emissions management. Technology platforms equipped with sophisticated emission matching techniques and databases evaluate your current emissions landscape by examining every corner of your business, from product manufacturing, and purchased goods, to transportation.

After baselining, the next logical step is emission hotspot identification. This process involves breaking down emissions by various categories—product lines, departments, purchased goods, geographical locations—and identifying areas where interventions would have the most significant impact. These are your primary ‘decarbonisation opportunities’, where incremental changes could lead to substantial emission reductions. 

Unveiling hidden emission sources

The emissions landscape often resembles an iceberg, with only the tip visible while the bulk remains submerged. It takes robust data analytics to unearth these hidden sources. Often your carbon hotspots are not immediately apparent, and you need to find the signal in the noise. 

We recently worked with a client who discovered that a preservative used across their product line was a significant, yet previously unidentified source of emissions. This revelation is now driving them to seek greener alternatives, effectively lowering their overall emissions dramatically.

If you’re a business that purchases finished products from multiple suppliers, your task becomes even more convoluted. How do you measure the carbon footprint of a product manufactured by another company, possibly in another country, following different environmental standards?

Artificial Intelligence simplifies this quagmire by employing Emission Factor Matching. This technique uses machine learning to approximate the carbon footprint of each product based on its constituents, such as ingredients, manufacturing processes, and even the geographic location of production.

Reduction simulations: The future of decision-making

Modelling the future is no longer the domain of science fiction. With advanced data analytics and AI, businesses can now create multiple forward-looking emissions scenarios by manipulating various factors across their value chain. These simulations empower companies to compare and contrast the potential impact of each scenario on emissions, leading to better decision-making. Companies can now explore different procurement options, test alternative production methods, and weigh the ramifications of these choices on their emissions.

A new era of carbon management

Technology is not merely an accessory to our lives; it’s the fabric that increasingly holds society together. As we continue to innovate, platforms like Terrascope are shaping a new narrative—one that combines technological progress with environmental responsibility. Beyond just managing existing data, our tools offer predictive analytics, giving businesses the foresight, they need for effective carbon management. It is not merely about surviving the challenges of today but thriving in a more sustainable future for everyone.

This commitment to integrating technology and sustainability is not a choice but an imperative—one that I, and all of us at Terrascope, are deeply committed to.

The article titled “Data and technology powering emission challenges in the supply chain” was contributed by Jason Gregory, Chief Product Officer, Terrascope

About the author

Jason has over 18 years of global, start-up, commercial and corporate experience within multiple iconic online companies. He has built a successful career creating and leading innovative commercial and technology solutions in online marketplaces, publishing, digital marketing, search and competitive intelligence.

Jason resides in Singapore as Chief Product Officer at Terrascope, a climate-tech company focused on helping large enterprises measure and reduce their carbon footprint and emissions via a smart carbon SAAS platform.

Jason has a strong track record of delivering world class products, improving productivity and scale to drive growth locally and globally, with a focus on Product Management, Strategy, Innovation and Commercial Development. Jason is passionate, driven, and is inspired by leading multi-disciplinary and diverse teams in the online sector, solving complex problems.

With a strong ability to operate in an agile environment and communicate at all levels in an organisation, he is often sought out as a team collaborator and personal mentor.

Jason holds a Bachelor of Business (Marketing) and is an active member of the Product Management community.