Getting Ready for the Next Wave: The Digital Future
In a recent report, McKinsey looked at the prospects for the next 50 years of cargo shipping, marking 50 years since it first reported on the potential impact of shipping containers on the industry. The new report predicts that digitalization and the use of big data in shipping will be just as disruptive to the market as the introduction of containers was in 1967: “Advances in the use of data and analytics will bring further step changes in productivity. Shipping companies could heed the example of today’s state-of-the-art aircraft, which generate up to a terabyte of data per flight. Coupled with the introduction of more sensors, the better usage of the data that ships and containers generate would allow enhancements such as optimizing voyages in real time (by taking into account weather, currents, traffic and other externalfactors), smarter stowage and terminal operations and predictive maintenance. Data could also improve the coordination of arrivals at port—a major benefit, since 48 percent of container ships arrive more than 12 hours behind schedule, thus wasting the carriers’ fuel and underutilising the terminal operators’ labour and quay space.”
The shipping industry is keenly aware of the need for digitalization, and the potential risks for those who fail to keep up. Recently, ex-DVB bank shipping boss Dagfinn Lunde warned that there is a “digital tsunami” on the horizon that threatens to “wipe out” owners and banks who ignore the effect of digitalization on the maritime industry. This state of affairs can lead to a rush for some to digitize everything possible—and others to bury their heads in the sand and hope it all goes away.
Instead, we at StratumFive argue that while it’s necessary to embrace digitalization, there’s no need to rush blindly toward it. What’s needed is a pragmatic approach. One that looks at maximizing the benefit to seafarers and to the owners and operators who support them, and focusing on the elements that make the biggest difference to the voyage, e.g., voyage monitoring systems that provide weather, security and navigational data. Such systems give owners, operators and shore crew the most accurate picture of where their ship is and what it’s doing. This minimizes the risk from adverse situations, such as storms or piracy, and makes sure the voyage is as efficient and safe as possible.
Companies looking to capitalize on digitalization should focus on giving users the biggest “bang for their buck,” delivering the most value in terms of the impact of the data available for analysis. Weather and navigation are among the biggest factors here. No matter how well optimized a vessel’s engine or trim might be, if you can’t avoid adverse weather or risky situations, this becomes obsolete. Systems that allow hyperaccurate monitoring and analysis of the minutiae of vessel performance are important, but to answer the most pressing questions that seafarers and shipowners have, we need to focus on the bigger picture.
The next phase in the development journey should be to use data sets to build predictive models, using machine learning techniques, based on analytics and data from past voyages. We can already see the examples of this analytical ability in the field of security. One such example is interactive heat maps that highlight the relative risks of piracy in different areas. Using this methodology can find relationships that might otherwise seem counterintuitive. For instance, one might guess that light levels, speed and weather will play a part—but not the day of the week. As it turns out, the risk of piracy is actually higher on certain days. In Somalia, Fridays are days of prayer. Pirates can be divided into two groups: less experienced, opportunistic “part-time” pirates and hardened “professional” pirates. The former group will observe their holy days, while the latter will venture out regardless. So, if a pirate attack occurs on a Friday, it is more likely to result in a hijacking.
This exemplifies a crucial advantage of big data and machine learning. As in all things in shipping, data platforms need to expect the unexpected. The goal should be to create open solutions that can efficiently index and leverage data from a variety of sources. This means we can find and use links between departments and data sets that might not be obvious at the outset, bringing together more data sets to come up with new solutions. This requires us to be bold and adventurous when working with partners. We need to share data. In reality, maintaining a data silo for fear of the competition benefits no one, and, in fact, can have a negative impact on commercial success. With a collective experience that spans decades at sea, and in the fields of meteorology, software development and data science, it’s clear we need to work in a way that enhances good seamanship. At the outset, digital solutions providers need to listen; to ask what shipping and seafarers need to know, rather than creating solutions in search of problems. Through listening, and adopting a pragmatic approach, shipping can master big data and digitalization, rather than drown in their wave.