Maritime trade has always been the core of global commerce. As an industry founded on the principles of economies of scale, where location and distance are hardly factors in today’s world of manufacturing, ports play a fundamental role in the world logistics chains.
The maritime industry's in-depth operational expertise and long-standing practices have historically enabled ports to navigate through turbulent times with agility and determination. This operational intelligence, built over decades, has been instrumental in maintaining the flow of global trade during crises.
As disruptions become increasingly frequent and complex, the value of this industry-specific knowledge becomes even more critical. Ports serve as stabilizing forces, capable of adapting quickly despite being anchored in traditional models. However, recent disruptions, ranging from geopolitical tensions to unpredictable supply chain bottlenecks, have made it clear that conventional approaches are no longer enough.
According to the Review of Maritime Transport 2023 (UNCTAD), global shipping continues to confront multiple challenges, including heightened trade policy and geopolitical tensions, and is dealing with changes in globalization patterns.
The industry must evolve and find new ways to streamline port operations, cut turnaround times, and enhance cargo tracking. At the same time, sustainability requirements are becoming more demanding, forcing companies to adopt greener practices without sacrificing productivity.
Therefore, we need to empower our business and accelerate the adoption of tools that can facilitate and streamline our decision-making. However, it is not just a matter of implementing technology; it is also necessary to evolve processes and people, planning a strategy for the transformation of the business as a whole.
A well-planned digital transformation strategy can help maritime businesses address these challenges by focusing on operational efficiency, resilience, and sustainability. Moving away from siloed operations to fully integrated digital ecosystems.
How to do it? The basis must lie in the amount of data already collected, the democratization of technology (at the cost level), and the development of new technology that will help to make all these processes more efficient. The hard part? Adapting our business to technology and technology to our business. We need to build that understanding and attack the transformation now.
The gap between current industry challenges and strategic potential
From shipping lines to port operators, logistics providers to customs authorities, all actors in the supply chain face numerous challenges that threaten the efficiency of the entire logistics process.
Shipping lines and freight forwarders, for example, struggle with rising fuel costs, inefficient routing, complex bureaucratic processes, and the need to meet increasingly strict emissions standards. Berthing and stevedoring teams face mounting pressure to improve turnaround times and safety, while marine services and port authorities must coordinate operations more efficiently under growing traffic and tighter margins. Meanwhile, inland logistics and last-mile delivery are being challenged by congestion, lack of visibility, and fragmented planning. All these actors share common challenges: congestion, which turns on delays, and lack of visibility of the rest of the chain (real-time data integration), which makes it difficult to plan staff, timetables, equipment, and even maintenance.
The maritime industry has vast potential to drive the global logistics chain through data-driven operations. However, this potential remains underutilized. Current data analysis in the sector is often fragmented and descriptive, limiting the ability to anticipate scenarios and make strategic decisions for greater efficiency and resilience.
Digitalization isn’t just a trend—it’s a strategic enabler
Technologies like AI, IoT, predictive analytics, and automation are allowing maritime stakeholders to unlock real-time visibility, anticipate disruptions before they occur, and make smarter, faster decisions.
So, the real question is: what should digital transformation look like? In our view, it relies on four key enablers: Advanced data analytics, automated data collection, big data & cloud platforms, and collaborative ecosystems & transformed workflows.
But digital transformation is not a one-size-fits-all journey. It must be grounded in the operational reality and experience of each player. As we've emphasized from the beginning, these elements must be tailored to the specific reality of each organization. It's not just about introducing new technology. It's about transforming the business itself.
1. The power of advanced data analytics and AI
At the heart of this transformation is data. How is the data itself processed? Advanced analytics and artificial intelligence (AI) provide companies with the ability to sift through massive amounts of information and extract valuable insights.
First, advanced analytics and machine learning can find patterns in data and make predictions. Additionally, generative AI and LLM agents can prescribe actions and support operational and strategic decision-making.
For example, predictive analytics can help forecast maintenance needs, reducing downtime and preventing costly breakdowns. Also, AI-driven systems in ports can optimize berth allocation and cargo handling, cutting turnaround times and lowering operational costs.
2. Automated data collection, IoT and smart sensors
To implement advanced data analytics and AI, you first need the data. Data that is diverse, representative, populated, and recurring. Furthermore, the sources of this data must be reliable.
In this regard, Internet of Things (IoT) and sensor technologies (among other innovative technologies) are revolutionizing maritime operations by providing real-time visibility into every aspect of the supply chain. Whether it’s tracking vessels, monitoring fuel consumption, or collecting environmental data, these tools ensure a seamless flow of information. But not only do IoT and transactional workloads help in this aspect, the type of algorithms currently available in the market allow for better capturing complex sources of data, from easily digitizing data on paper to translating images and video into exploitable datasets.
3. Big data and cloud platforms towards Digital Twins
On the other hand, Big Data platforms and their benefits of scalability and flexibility when deployed in the cloud enable such data integration and allow for scaled processing of the algorithms mentioned before. Such technologies allow benefiting from extensive computing power while rationalizing and optimizing costs with their pay-per-use service.
Digital Twins go beyond cloud big data platforms to maximize analytical capabilities. When implemented in a real-time environment, they consolidate the status of the entire infrastructure we manage. This allows us to properly monitor our assets and operations, identify anomalies and issues promptly, and conduct fast simulations. As a result, decision-making is significantly improved, maximising efficiency and enhancing the industry’s ability to withstand disruptions.
4. Building collaborative ecosystems and transformed workflows
Digital transformation goes beyond adopting new technologies and analyzing data; it reshapes how organizations work. And so, it is imperative to talk about processes and people.
We need to understand the business and integrate new technologies into the decision-making process. Digital accelerators can help, but we're dealing with an operational environment where decision-making is driven by the intimate knowledge of how the different parts of the value chain work together.
The specific need and the expected interaction between users and the solution drive the definition of data-related requirements, which heavily influence the analytical approach of the technical solution to be implemented.
In addition to adapting our processes and people to align technology with workflows, these technologies can foster collaborative environments within an organization, ensuring appropriate, strong, and secure data governance policies. They streamline data sharing across departments, easily breaking down silos. Beyond internal collaboration, it is essential to create collaborative environments that integrate all stakeholders in the supply chain. Cloud-based platforms and digital collaboration tools enable ports, shipping lines, and logistics providers to synchronize their operations, making the entire system more agile and responsive.
One challenge, one use case
Based on the enablers presented, a multitude of use cases can be executed to solve the challenges that different industry stakeholders face. The use of advanced solutions, such as artificial intelligence and modern analytical platforms, opens the door to key use cases for decision-making, such as:
Let’s put the focus on 1 use case:
Challenge: inefficient berth usage – Solution: berth optimization
Traditional berth management often relies on manual processes or semi-digital systems, resulting in poor real-time visibility, static and rigid scheduling, extended idle times, and higher costs from delays, demurrage charges, extra fuel consumption, and loss of operational efficiency.
By digitalizing berth optimization, with an AI-powered scheduling based on vessel ETA, vessel dimensions, call size, and real-time congestion, ports shift from reactive, manual handling to proactive, predictive management, achieving agile, cost-efficient, and resilient operations.
Some potential analytical cases to achieve a predictive and dynamic berth allocation:
- Tailored predictive ETA by learning from past travel times, trajectories, weather info, etc.
- Scheduled times calculation based on past behavior:
- Anchorage times based on vessel type and congestion
- Handling and net berthing times based on vessel, cargo type, quay crane usage, etc.
- Downstream scheduled times recalculation (t4, t5, t6, etc.) based on upstream actual times (t1, t2, t3, etc.) and past behavior
- Actual times calculation based on AIS data
- Quay crane allocation based on sensor data, maintenance schedule, and past behavior
It is important to note that each terminal and situation is unique, requiring a detailed study of its own operations, context and environment. While individual companies can spearhead digital initiatives within their own facilities, broad transformation hinges on collective action across the supply chain.
The opportunity of the data-driven logistic chain
Based on the previous, digitalization would benefit all actors in the logistics chain, from port authorities, terminal operators, shipping companies, customs agencies, truck companies, to maritime insurers and customers. Digital transformation will help improve operational efficiency, reduce costs, enhance sustainability, and increase safety and security:
The road ahead: Key priorities for the maritime sector
The question is no longer whether the maritime industry should embrace digital transformation; it’s about how quickly and effectively companies can integrate these technologies into their operations. A successful digital strategy in the maritime industry should include:
- End-to-end integration: From strategic planning to AI-driven execution, companies must ensure that digital solutions cover the entire supply chain, providing real-time tracking and visibility.
- Data-driven decision making: Real-time analytics and AI should be at the core of operational improvements and risk mitigation strategies.
- Collaborative networks: Strengthening partnerships across the supply chain to create a seamless, interconnected system that boosts agility and resilience.
- Sustainability and compliance: Leveraging digital tools to meet environmental standards and regulatory requirements while maximizing efficiency.
However, the road to achieving all of this is a long one and will require a lot of work, so solutions will have to be implemented one step at a time.
Even if an holistic value chain optimization, tackling multiple stages of the value chain at once with a growing transversal framework is possible, a targeted pain point resolution, addressing specific inefficiencies first, building toward a broader framework over time, it is possibly the best option to implement the digital transformation of the maritime industry.
With this context, ALG positions itself as a strategic partner for any company looking to enhance its digital transformation. ALG maritime-data hybrid profile experts need to understand how our client’s business reality—current technology, people, change resistance, and data—can leverage new technologies to support their strategic goals.
- Phase I - Conceptualization and feasibility of AI use cases: We assess the business challenges, framework, and prepare Use Cases of Data Science, AI, or Business Intelligence based on our client insights. We propose an analytical roadmap to the client, prioritized according to value and with clear enablers.
- Phase II - Accelerated development of AI use cases: In this phase, ALG team accelerates the development of the demonstrator, with customer participation in agile ceremonies.
Digital transformation in the maritime sector is not just about acquiring or deploying technology. It is a paradigm shift in which organizations adopt the new digital rhythm of technology, constantly adapting their business to new dynamics and ensuring the most appropriate composition of human and technical capabilities.
The ports and logistics operators that are successfully embracing digital tools today are not replacing their know-how—they’re enhancing it. By combining decades of expertise with the power of data, the maritime industry can not only overcome today’s challenges but also build a more resilient, efficient, and sustainable future.
The challenges are clear, and the time to act is now.
About the authors
Victoria Manget
Civil engineer with a double MSc degree, specialized in management, project finance, transport, and urban planning. Senior Consultant at ALG, contributing to projects related to the digital transformation of the maritime industry.
Núria Alsina
Aeronautical engineer with specialisation in air navigation and systems, certified in project management and scrum methodology. Principal at ALG and head of digitalisation and advanced analytics in the Transportation practice.
