Frictionless Trade: how new technology will power international trade is a new report on maritime digitalisation written by Startup Wharf founder and chief executive Leonardo Zangrando and Antares Insight founder and chief executive Nick Chubb
The report was constructed from primary research, telephone interviews and from the dataset maintained by Startup Wharf. The aim of the report is to describe the state of play in the maritime digitalisation sector and in trade tech in particular.
The term trade tech is widely used in the report and means any technology that can be applied to make maritime processes more efficient and reduce bottlenecks in the flow of goods around the world.
Trade tech is the digital innovation that is mainly taking place in trade, shipping and customs technology. The trade tech sector could grow to be worth £12.8Bn (US$16.3Bn) by 2030. Trade tech can be broken down as:
According to the authors, the UK maritime sector is one of the best placed to make efficiencies through trade tech as it is the biggest handler of UK trade. The report notes that in January 2017 the Yiwu-London freight train service commenced operation. This service runs from Yiwu, near Shanghai via the Channel Tunnel to the UK. The Channel Tunnel limits the rail capacity to 1.2M tonnes per annum.
Airfreight is useful for time-sensitive goods, but only makes up 3M tonnes per annum of UK trade.
The rest of UK trade in 2017 was some 482M tonnes, according to the UK Department for Transport, and was traded through UK ports. Of this figure, 60% were bulk cargoes and rest was unitised cargo such as containers. According to a 2014 study, a simple shipment of a container of avocados from Mombasa can entail 200 communications involving 30 parties. Multiply that by the number of containers being offloaded, loaded and transhipped from a 20,000-TEU container ship and there is clearly huge potential for efficiency gains.
However, the authors note that the barriers to entry are high. It takes a high level of skill, experience, knowledge and above all capital to enter the shipping space. The sector is below the public radar – except when there is an oil spill. On the plus side, shipping regards out-of-date business methods as a positive and should be an ideal candidate for disruptive practices.
In the container sector, the recent round of consolidation has left 82% of the fleet under the control of the top 10 companies. These companies are highly reliant on legacy programs, such as the electronic data interchange (EDI) which was introduced in 1987. In almost any other industry, a 1987 technology would have long been superseded but in the container sector EDI, phone, email and personal friendships are the main tools of business.
So why do legacy systems exist in modern shipping? The main reason is fear of change. The people at the top of the organisations have got there by understanding the mechanics of the organisation. It is not in their interest to make sweeping changes. Nor are there mechanisms in place to take on innovations. Therefore, most organisations are self-sustaining and resistant to change.
This is the opposite of how trade tech start-ups operate. These employ the OODA loop of observe, orient, decide, act. A small start-up can identify the problem, built, test, iterate and adapt new ideas to optimise products. Using cloud computing, an idea and product that hits the mark can be quickly scaled up.
But the maritime trade tech start-ups cannot operate in isolation. Close collaboration is needed with the industry, but at the same time the industry needs to be aware of the creative processes involved.
The report points to the use of start-up incubators and accelerators, such as the SparkUp challenge initiated by Wärtsilä.
During an average port call there can be 30 to 60 point-to-point interactions by email and phone. At the highest level of disruptive technology, Rolls-Royce produced several autonomous ship concepts and Kongsberg is committed to having its first fully autonomous ship Yara Birkeland, operational by 2020.
Case study: Sea Machines Robotics
Sea Machines Robotics is a Boston-based start-up that recently opened a European headquarters in Hamburg and has launched a remote-control system for small vessels. The system can be retrofitted or installed new as in the case of the Maersk ice-class container ships. These will use computer vision, LiDAR and perception software in live situations to augment and upgrade vessel operations.
Case study: Teqplay
Three-year old Teqplay is the result of the formation of a task force composed of the stakeholders in the port of Rotterdam. The Teqplay team has created Pronto to provide stakeholders with a shared operational view and a joint platform to exchange information about port calls.
Case study: PortX
Founded in 2016, PortX is a joint venture between vessel tracking platform ShipX and global tug boat operator Kotug International. The start-up can track vessel movements across almost every port in the world which allows them to offer comprehensive performance reporting, port call benchmarking and strategic advice to their clients. As well as benchmarking performance, PortX can proactively optimise the dispatch of port-related assets like tugboats, pilot boats and linesmen in real-time using proprietary forecasting algorithms.
This includes pre-port arrival paperwork and cargo preparation, unloading and loading. Cargo stowage computers have been around for many years for container ships and bulk carriers. The tech trade challenge in this area is to move away from relying on VHF radio and to improve efficiency through digitalisation of the monitoring process. There still needs to be the physical movement of goods but there is scope to create a digital twin to increase stakeholders’ awareness of the location of goods.
Case study: Portchain
Danish start-up Portchain aims to eliminate the manual process used by port planners. The start-up has €1.4M (US$1.6M) in funding from the EU’s Horizon 2020 project. The first product is Port Call Plan, which is claimed to reduce port planning operations by 1-2 hours per day. A second project, Berth Optimization Engine uses AI to generate berthing scenarios to preposition cranes for moving containers.
Case study: CargoMate
CargoMate is a just-in-time algorithm that uses a hand-held smart device for crew to log cargo operations as they happen. The data is then transmitted to CargoMate’s platform in real-time where it is fed into machine learning algorithms that predict the earliest time the ship will be able to leave port. Predictions and port productivity data can be displayed on a stakeholder dashboard or fed into other collaborative systems using an API. By saving one hour per day in port, it is estimated the system could produce significant fuel savings by allowing container ships to steam slower and still make schedules.
The heavy reliance on codified documentation such as the bill of lading is seen as one of the areas in shipping that has the greatest potential, but at the same time is fraught with pitfalls due to the historical legal framework that surrounds such documentation.
The disrupter to break into this area is widely seen as blockchain, which would break the need to courier documents around the world.
Case study: Marine Transport International
Marine Transport International (MTI) has developed a digital register of packed container weights (VGM). The need to weigh every container was introduced after MOL Comfort broke in two, in part due to poor design, but also due to incorrect declaration of weight. The law was changed to require shippers to declare container weights before they are loaded to a ship. This was a highly manual process, forcing shippers to manually calculate individual container weights and submit them to carriers. Solas VGM, which has recorded tens of thousands of transactions to date, allows shippers to digitally complete this process, reducing the cost and the administrative burden that came with the new regulations.
Case study: Concirrus
London start-up Concirrus uses data to improve the marine insurance market. Founded in 2012, Concirrus uses large datasets such as vessel statistics, movements, local weather, machinery information and traditional demographic data to improve how insurers view risk. By combining their datasets with historical claims data, Concirrus can use machine learning to identify the behaviours and conditions that correlate to claims.
The customs authorities have two main aims. The first is collect the due tariff on the goods entering the country. The second aim is to control the goods coming in, from firearms to herbs.
The challenge is that the main system for recording and controlling customs and tariffs was developed over 20 years ago. The new Customs Declaration Service (CDS) has been developed by HRMC and will launch in 2019. However, CDS was designed before Brexit and can handle around 100M custom declarations. Post-Brexit, the number of custom declarations is expected to reach more than twice that number.
Case study: AiDock
A portfolio company of theDOCK, Israel’s maritime innovation accelerator, AiDock has developed an automated customs clearance platform that reduces the admin burden on freight forwarders and speeds up the customs process. AiDock’s system uses artificial intelligence to process and analyse documents and generates customs clearance files automatically.
Case study: INLT
INLT is a US-based start-up looking to redefine the role of the customs broker in the supply chain by creating a central hub for stakeholders in the customs process.
By offering a cloud-based customs broking platform, INLT provides shippers, receivers, and agents with real-time updates, eliminating the back-and-forth communication usually associated with the process. As well as communication, INLT’s platform stores documentation in a single, secure place for 24/7 access, and display shipment tracking data in a single dashboard.
The main aim of a port is to move goods through the port as quickly as possible. This requires a complex port management system, made even more complex where automated equipment is moving around the yard. This can include 40-tonne cranes and remotely controlled straddle carriers.
The challenge is to build a data picture of the port to show where the goods, cranes, trucks and people are, and where they are going.
Case study: Octopi
Octopi has developed a cloud-based terminal operating system, which is cheaper to purchase and run than systems designed for very large ports. The target consumer is the smaller port needing help with moving cargo in and out of the port faster. Octopi also integrates with accounting software to facilitate invoicing and billing. Through Octopi, invoices are automatically generated from events recorded by the platform and logged to the accounting system, massively reducing the burden on admin staff.
Border and port security
Smuggling has long been a problem in ports and can reach truly epic proportions as in the case of the illegal fuel oil being sold in Italy. Security in the maritime sector is governed by the International Ship and Port Facility Security Code (ISPS), an amendment to the Safety of Life at Sea Convention brought into force by IMO in 2004 as a response to the 9/11 terror attacks. ISPS sets out minimum standards for security procedures in port facilities and on board ships engaged in international trade. Among other things, it requires that all ships and ports conduct training, have a security plan, a company security officer and a ship security officer.
The trade tech challenge is the reality of making a port and ship secure. The only way to have full security is to search every item and person entering and leaving a ship or port. Using secure internet of things (IoT) to track individual items and people is a step closer. In the case of containers, an IoT sensor could reveal tampering from changes in humidity and temperature within the box.
The second challenge is cyber crime and the ability to hack into ship and port systems. The June 2017 NotPetya ransomware virus took down the entire Maersk IT system and is estimated to have cost the company between US$250M to US$300M.
Case study: Calipsa
Calipsa has developed cutting-edge deep learning software capable of monitoring and analysing CCTV videos in real-time, with multiple applications in transport and infrastructural sites. There are close to 250M cameras in the world today and the traditional operating model still relies on human analysts to monitor and interpret these video feeds. The Calipsa system can be connected to police networks. A Calipsa system is on trial with the French Ministry of Transport.