Shipping is a relatively archaic sector when compared with other parts of the economy, but there are signals that this is changing. One of the key elements accelerating the pace of change is better data collection, and the use of analytical technologies. How might maritime companies create and leverage this data to become more efficient, and what are the learnings for other sectors? How can data help industry understand the shifting supply chain and how to serve customers more efficiently?

Despite being part of it, I’ve always acknowledged that shipping and the maritime sector are rather conservative. There isn’t a great deal of visionary thinking, as radical change within such a mega-sector has been classed by many as ‘too difficult’.  It took a change of career direction for me question myself about the future direction of shipping. With other sectors embracing transformational change, whether through electric autonomous cars, drone delivered parcels, or the Internet of Things turning products into services, it became clear – it’s shipping’s turn now.

The shipping environment is as tough as anyone can remember, and there’s no end in sight. For ports, as well as ship owners, managers, brokers and charterers, there are many threats to their financial health and ongoing viability. Recent news from Amazon, Walmart and Alibaba, who may be looking into chartering their own ships and leasing their own terminals, suggests that structural change is on the way. It’s uncomfortable that the traditional ship owners face such challenges but, overall, such change is somewhat inevitable.

Over 90 percent of world trade goes through ports, yet the last significant innovation in the maritime sector was the introduction of the ISO container – in the 1950s. For too long the industry has opted to wait out the storm, with competitors nervously switching their gaze from their own navel to any movement others might make. Unsatisfactory margins and many organisations’ inability to respond quickly enough to an ever-changing world is for everyone an unsatisfactory status quo. Cathartic change is needed.

Shipping remains a remarkably inefficient business model, with hugely expensive assets and massive running costs. Owners and operators aim to achieve a modest return, yet their long-term success is almost entirely dependent on world economic trends. The industry is frustrated with cost inefficiencies and leakages throughout the supply chain.

Ports and their operations are part of that chain, and perhaps often unfairly seen as a barrier to trade as much as an enabler. Some would argue that operators need to recognise the pressures and to find ways to evolve their role.  Surely for those ports proactively finding ways to better service their customers’ needs, especially in respect of information supply, there is a huge competitive advantage?

In a sector steeped in history, we still retain centuries old processes and practices. Despite the market risks, and the knife-edge economics wrought by significant vessel oversupply, many owners, operators, and charterers are working without access to the necessary information, not least a full understanding and visibility of all the key data points allowing full optimisation of the entire value chain.

As a Cargo Superintendent in the early part of my career, whenever I came into port, I borrowed the stevedore’s bicycle to ride up and down the quayside. I was looking to see what other ships were in port, what cargoes were being loaded and discharged and nattered with folk to see what the local customs, pilot, transport, labour and crew issues were. I would report this back to head office, as many other Cargo Superintendents would have done. Based on this highly granular information, albeit a snapshot in time, important decisions about competition and future trade opportunities were made.

There is however lots of talk about big data, but while it might be collected, it’s not being used effectively. We should never fall into the trap of confusing a mass of data for big data. New technology will give the maritime sector access to a wealth of such business-critical data analytics, including vessel location, trade flow and cargo availability, port congestion, vessel line up and turnaround efficiency. When innovative data analytics is coupled with insightful, strategic thinking and in-depth experience of logistics management, it’s clear that powerful new tools and methodologies will start to change the face of port and shipping operations.

Progress is also well underway in the development of proprietary technology that utilises machine learning to create maritime geofences that form the basis for us to analyse the spatial relationship between objects at rest, and objects in motion. The key is combining data that is in the public realm, adding our own proprietary data, then looking at what is happening in the real world.

Despite its introduction in 2002, the use of on board AIS (Automated Identification System) data is only starting to be used by operators to examine various elements of the voyage and port performance. Yet now, based upon software patterns, we can go much further and make predictions about what will happen in the future. Imagine running a fleet of 200 ships and being able to accurately forecast ahead for six months, a year or two years. The competitive advantage is enormous.

I shouldn’t be surprised, but early work confirms that machines learn extremely efficiently, with their performance improving exponentially over very short periods of time. Advanced algorithms, powered by significant computing resources, can combine and mine vast sources of data. Every day merchant shipping makes 4,500 port calls around the world, so it would be impossible for a human to accurately identify the numerous data trends applicable to shipping. Yet AI systems are taught to assess this data, spot similarities and anomalies, and create successful patterns through which they can quickly learn.

From a port looking to improve its efficiency, to anyone in the maritime sector wanting to streamline their operations, for example, by having key data covering a voyage rather than last minute ‘adjustments’ shortly before arrival or departure, the benefits of this technology are enormous. I believe that there is now a demonstrable opportunity to leapfrog the evolution in other sectors, to make innovative use of global shipping data, and to bring about wholescale reform.

It’s all about the entire value chain, not only the port, yet the granularity of port data is incredibly important to your customers. We’ve all been on the plane from Copenhagen or Oslo, waiting to get back to London Heathrow, only to be told we can’t take off because we’ve lost our landing slot. Why should it be any different in shipping, where customers send a ship at full steam, only to be held at anchor for days or to suddenly have to slow steam, due to port congestion that could have been predicted many days beforehand?

The success of this data-led approach to operations is however based on the quality of the information that is fed into the system. Many shipping companies currently rely on an already extremely busy port agent or others at the quayside to tap things into a tablet device, at the same time as doing a million other things, and in all weathers. Those of us with any practical experience of working in a port will realise that this is fraught with difficulties. We are therefore now developing ways to collect information automatically, rather than solely relying on human inputs.

More data means greater transparency and for progressive and efficient operators, there is great competitive advantage to be gained. It’s exactly for massive and complex sectors like shipping that data applications should be developed. It’s our time for new thinking and radical transformation.