In the drive towards a green supply chain, much emphasis has been placed on the use of green fuels including hydrogen, ammonia and methanol to be the main drivers in reducing emissions and meeting mandated global targets. Supply chain decarbonisation refers to reducing CO2 emissions by establishing a net-zero carbon supply chain. Decarbonisation is part of a company’s overall sustainability performance, which has become a key priority following the United Nations’ Sustainable Development Goals.

While ‘Net-zero carbon’ or ‘carbon neutral’ refers to balancing the anthropogenic carbon emissions produced so far by removing or reducing future carbon emissions to limit global warming by a specific target, e.g., by 1.5°C, which means that companies across the globe should become carbon-neutral by 2050.

The big switch in moving away from fossil fuels is already underway, but in the interim, there is an alternative that will enable all players in the global supply chain to improve operational efficiency and reduce costs and emissions throughout the supply chain. To achieve the net-zero carbon target, all carbon emissions produced along the supply chain must be kept to the minimum through the application of effective sustainability strategies and any emissions that remain must be offset through carbon emission removal techniques via green technology.


Effective resource management can minimise carbon footprint by monitoring product movements and data-driven decision-making, thereby contributing towards the net-zero goal.

Big data refers to datasets with a large volume, high velocity, diversity, veracity, and value, which becomes an invaluable resource for supply chain decarbonisation. The use of data to achieve improved efficiency and drive down emissions has been discussed for many years, but now as technology improves there is a real opportunity for collaboration across the supply chain.

In shipping, the process is already underway with the Green and Digital Corridor project launched by the Port of Rotterdam and Singapore’s Maritime Port Authority (MPA). The critical factor in this venture is the agreement to share data.

The sharing of data, electronic documentation and standards serve as a platform for future initiatives to reduce emissions in the maritime industry. The project is a great example of how collaboration and data sharing can drive efficiency and sustainability, explained Dr. Mark Yong, Managing Director of Asia for Blume Global.

By sharing data and electronic documentation, ports and shipping companies can optimise their operations and reduce waste, emissions and costs. For example, by using real-time data on vessel movements and port operations, ports can optimise arrival times, reduce waiting times, and minimise the idle time for vessels, significantly reducing emissions.

Moreover, the adoption of standardisation and protocols for data sharing can streamline operations, and reduce errors and inefficiencies, which can ultimately lead to greater sustainability and cost savings.

‘Overall, the Green and Digital Corridor project is a promising initiative that demonstrates the potential for data sharing and collaboration to drive sustainability in the maritime industry. The model can be expanded to other ports and regions, leading to a more sustainable and efficient shipping industry globally,’ said Dr. Yong.

Big data can be of great benefit to container terminal operators as well. By analysing large amounts of data, terminal operators can gain valuable insights into their operations, which can help them make more informed decisions and improve their overall efficiency.

Aggregation and analysis of data can help to reduce emissions in shipping and land transportation in several practical ways. Port operators can identify the most efficient routes for containers to take through the terminal, help reduce congestion and improve overall throughput.


Standardisation can also facilitate collaboration and knowledge sharing across different ports and stakeholders, which can accelerate the adoption of sustainable practices and technologies in the industry.

On March 2023, Hutchison Ports signed a nonbinding memorandum of understanding (MoU) to enable paperless trade with shipper Saudi Basic Industries Corporation (SABIC), carrier COSCO SHIPPING Lines (COSCO SHIPPING) and port operator PSA International (PSA); led by Global Shipping Business Network (GSBN), an independent not-for-profit technology consortium, to build a trusted platform designed to redefine global trade.

The five-way MoU will see all signatories leveraging the electronic Bill of Lading (eBL) for export shipments. Structured data collected from the eBL issued via GSBN’s data infrastructure, will also be used by Cargo Release to enable a fully digital solution, which connects everyone involved at the ports of import to enable the secure and paperless release of containers.

The GSBN platform also facilitates even closer collaboration between the carrier and ports by breaking down data siloes between them to unlock the power of digitisation, as well as enable new value to customers. The objective of the MoU is to boost efficiency and reduce the environmental impact throughout the shipping process.


 By analysing data on vessel movements, cargo flows, and port operations, shipping companies can optimise their routes and operations to minimise fuel consumption and emissions. For example, they can avoid congested seaports, adjust vessel speeds, and choose ports which are more efficient in terms of vessel scheduling and productivity in loading and unloading cargo in real-time.

By monitoring and analysing the data on fuel consumption and emissions, shipping and logistics companies can identify areas for improvement and implement measures to improve fuel efficiency. Such as using low-carbon fuels, retrofitting vessels with energy-efficient technologies including scrubbers, and optimises engine and propulsion systems.


 By analysing data on cargo availability and demand, logistics companies can reduce empty running and increase the utilisation of vehicles. This can reduce emissions by minimising the number of vehicles required to transport the same amount of cargo.


 By aggregating and sharing data on supply chain operations, companies can identify inefficiencies and implement measures to reduce emissions. Like reducing the number of intermediaries in the supply chain, using more sustainable packaging, and implementing circular economy practices.


By tracking emissions data and setting emissions reduction targets, ports, shipping and logistics companies can hold themselves accountable for reducing their environmental impact. They can use these data to identify areas for improvement and track progress towards their targets over time.

Supply chain data platforms are now playing a bigger role as can collect and analyse data from multiple sources across the supply chain. These platforms provide a neutral service, ensuring that commercially sensitive data is secure and not shared with third parties or competitors.

By leveraging data and analytics capabilities, supply chain partners can also help to identify opportunities to reduce emissions in shipping and develop more sustainable logistics solutions. They can provide data on alternative transportation modes and routes, which helps shipping companies make more informed decisions on how to reduce emissions.

Data companies can utilise these valuable data on supply chain operations, such as inventory levels, demand patterns, and warehouse utilisation, to help companies optimise their logistics operations and reduce waste and emissions.


In the last two years, more than ever, rate and volume volatility in liner trades means that there is a constant need for shipping lines to change proforma schedules to match the cargo flow.

Matching ever-changing supply and demand has become a difficult endeavour for planners, given port and canal closures, blank sailings and extreme weather. All these factors impact the amount of fuel used and the corresponding emissions.

Today, Artificial Intelligent (AI) optimisers can make calculations, process data and automate reasoning, which allows shipping lines to make more accurate and informed decisions with regard to the deployment of their vessels in their service network with big data.

This ensures the right vessel is allocated at the right time to the right port pair combination, to yield bunker optimisation, schedule reliability, reduce charter costs and maximise profitability and critically reduce emissions.


It has always been a challenge for shipping to unpredictable weather patterns which affect safety, schedule integrity and the amount of fuel consumed during its voyage.

As the weather becomes more volatile due to climate change and vessels more frequently meet adverse weather conditions, such as highly significant waves, strong winds and currents, the ship must output more power which consumes more fuel to maintain its speed for stability and safety.

With the aid of specialist weather forecast algorithms take weather conditions into account and combine the data collected with statistical speed loss calculated by vessel type. The algorithm then recommends the vessel sail at a certain speed which stabilises the ship, enabling the vessel to run at optimal power, reducing fuel consumption and lowering greenhouse gas emissions throughout the voyage. The algorithm is composed of data being collected from thousands of vessels over time, so it is constantly improving.


As the United Nations emissions targets for 2030 and 2050 impact all supply chain companies through increased carbon taxes and mandated restrictions on burning fossil fuels there are opportunities to leverage data platforms, AI and optimisation algorithms to reduce the amount of CO2 and greenhouse gases released into the environment.

This will provide the shipping industry with another channel to incrementally reduce its carbon footprint while waiting for the transition to green fuels to gain traction.

Big data will allow many industries to open up to more ways to reduce carbon emissions in a smarter way, it also identifies decision-making factors that can help companies to prioritise data collection and processing. Applications such as Industry 4.0 technologies, including AI through deep learning and neural network techniques will also help companies make informed decisions about supply chain decarbonisation.