A recent smart shipping survey found that, while most maritime industry executives see digitalisation and Big Data as a transformative force, only 8.7% currently see it as a major part of their operations. If you’ve been a regular attendee of trade shows and events, this might come as a surprise. Since around 2014, it’s been a routine feature of pretty much every speech and presentation.
For years, we’ve been told that not adopting Big Data is leaving money on the table. So why is only one owner out of ten taking it? On the flipside however, nearly one in ten owners might actually seem high. For most owners and operators there are other, more pressing priorities.
It’s easy to see how the day-to-day reality of running a business in what is still a tough, and rapidly changing market can prevent them from investing in Big Data – particularly when Big Data solutions are often expensive, time-consuming, and don’t provide a clear ROI – particularly for small and medium-sized owners and operators. With 90.3% of the market left to convince, and win over, whoever can get out there and prove that they can get the job done is going to find themselves in an enviable position. However, this is where the issue gets thorny. Just what jobs do we need data to do, and how can we prove that it’s worth doing?
The rise of Big Data has given us the opportunity to rush out and digitalise practically every aspect of vessel performance, from trim, to engine management, to hull and propeller performance. However, with a bewildering array of options on the table, there are several pitfalls to avoid. Firstly, there’s the temptation to focus on what’s easily measurable, rather than what matters. If you ask most data providers what the key to unlocking better performance is, the chances are that they will tell you it’s whatever they are currently measuring.
For owners and operators, there are competing temptations to either collect data on and digitalise everything, or simply bury one’s head in the sand and hope it all goes away. This certainly does not lead to a healthy relationship with data, as the 8.7% figure shows. Much of these issues stem from the fact that data providers and shipping companies are failing to speak the same language, and listen to one another.
What’s easier for a company coming into this often confusing and fragmented industry? Either to listen to ship owners and understand the issues that are most central to their businesses? Or to find something easy to measure and focus on that, promising to ‘scale up’ later? The more difficult, but ultimately more fruitful alternative is to look at the entire voyage, and work out where to apply data optimisation in order deliver the most ‘bang for your buck’ and ROI.
This is the thinking that underpins our current voyage monitoring offering to the market, OTIS (Online Tracking and Information System), which provides weather, security and navigational data. We service over 9,000 vessels, providing highly accurate location data – with up to thousands of locations transmitted every day per vessel, achieved by combining multiple data sources. Collectively, including S-AIS services, we handle tens of millions of positions per day.
This allows us to give owners, operators and shore crew the most accurate picture available of where their ship is and what it’s doing, while minimising the risk to ships and crew from adverse situations such as weather or piracy, and ensuring the voyage is as efficient and as safe as possible. Our experience in tracking and monitoring informs the next phase in our development journey, which is to use the data we already have (and new datasets as they become available) – and to use machine learning techniques to build predictive models based on analytics and data from past voyages.
As well as high level domain knowledge, bringing in SME’s from Big Data, routing and meteorology disciplines, this approach also takes into account years of experience of real life at sea, and the nuts and bolts of what makes a voyage efficient and safe. In creating these models, and the platform that underpins the data, we first look at what makes the biggest difference to the voyage. This is undoubtedly weather. The contribution of weather, the so called ‘weather margin’, is the largest contributor to performance often by orders of magnitude. By comparing some actual voyages against recommended routes, we see the scope of some of the potential savings just from weather routing. In one example, avoiding adverse weather could have used one third of the fuel when compared to the route taken, and still arrived on time.
Looking at efficiency in this way, it’s clear why we need to take weather as our starting point. However, there’s no point stopping there. Taking our inspiration from world-class coaches in sport for example, we must look for how we can generate marginal gains to deliver maximum efficiency. If taking care of the weather is the equivalent of taking junk food out of your diet, and putting in the hard yards on the training pitch, you won’t become a pro unless you focus rigorously on every single aspect of your performance.
The same is true of shipping. This underpins how we create our software – while we’re focusing on the big ticket items, the software we create still needs to be flexible enough to handle multiple diverse datasets. As in all things in shipping, data platforms need to expect the unexpected. We aim to create open solutions that can efficiently index and leverage data from a variety of sources – for instance, hull performance data, mechanical data, trim, etc. This also means that we can find and use links between departments and datasets that might not be obvious at the outset, bringing together more datasets to come up with new solutions. This also requires us to be confident, bold and aspirational when working with partners.
We need to share data. Maintaining a data silo for fear of the competition benefits no-one, and in fact can have a negative impact on commercial success. But no matter how much data a platform is handling, the ultimate question is whether you’re using it to make the day-to- day business of a shipping company better. Working with data is no use unless you’re equally focused on the human element – talking to owners and operators and solving their most business-critical issues.
Building the above flexible platform gives you the means to do this – but it’s only by listening to the owners that this will work in real life. This approach is essential if the whole fleet is to benefit from digitalization. We need to bear in mind that, for most companies, the sparse information available on the noon report can be the best data that we currently have available.
Upgrading from this all in one go is unfeasible. However, there’s no need to necessarily digitalise everything all at once, or chase after every ‘shiny new object’. Ultimately, we should see Big Data as something that augments good seamanship, and experience built up over decades. If we take a pragmatic approach and build products that are flexible, allowing us to focus on the most pressing needs of owners before moving on to marginal gains, perhaps we’ll see an uptake of Big Data in shipping that’s more on par with the wider global economy.
There’s a lot of catching up to do – in a recent survey in Harvard Business Review, 48.4% found that their firms were achieving measurable results from their Big Data investments. How soon we can close the gap depends on how well we tailor our solutions around what the industry actually needs, rather than what’s easy to measure and predict.
Author: Stuart Nicholls, CEO of StrautmFive