We all get excited by what new technology can do: our expectations are raised and we become keen to experiment. Frequently, though, businesses aren’t fully ready to go through the process of adoption. So are we viewing technology in the wrong way – taking a solution and searching for the problem, or – even worse – problems? Or is there another way?
Peaks and Troughs
Every year, Gartner publishes its annual report known as the “Hype Cycle”. Looking like a big-nosed man lying on his back, it features some of the hottest emerging technologies and their rates of maturity and adoption. All the usual suspects are there, including artificial intelligence (A)I, blockchain, IoT, autonomous vehicles and deep learning. Curiously, most of them congregate in the window of “peak of inflated expectations”.
This might be because we’re in the early stages of maritime’s great technological leap forward, and many organizations aren’t prepared or lack the resources to fully embrace it. For example, only 3% of shipping companies have a CTO; the Global Maritime Forum’s Issues Monitor found that AI is the issue the industry is least prepared for. Or it might be because we are viewing technology in the wrong way – looking at industry-wide solutions (‘AI for shipping’, or ‘Blockchain for trade’), rather than as an enabler of very specific business objectives.
Deep Not Wide
So perhaps the right approach should be vertical? Instead of taking a technological promise and going wide to find problems to solve, what if we started with one problem and went deep to find the right solution?
The British government in 1714 followed this approach when it needed a simple and practical method for the precise determination of a ship’s longitude at sea. It created the Longitude Prize. It was won by one John Harrison, who solved the problem with his invention of the marine chronometer.
For a more modern example, take energy majors and commodity traders. They are behemoths with intricate, multi-faceted operations that turns over hundreds of billions of dollars a year. It’s tempting to set up small armies of engineers to bring in innovation across the board. But what should their core focus be? Most of the revenue of these companies comes from buying and selling cargos. And within that operation, physical shipping is only one part – albeit a key one – in the supply chain; a key challenge is to compete more effectively for more cargoes. So, in addressing this specific issue, could we use AI specifically to safely vet twice as many vessels for work, thus boosting their availability, and enabling the energy company or trader to compete for more cargoes?
Another critical success factor is to ensure that they trade on the right side of the law. Recent U.S. government advisories mandate that every bank, trader, bunkering service provider and other parties actively screen for vessel behavior This means that, for the first time ever, it’s not enough to merely input the various sanctioned blacklists; companies have to look at how all vessels are behaving.
With that in mind, HSBC is reportedly considering using big data to assign a financial-crime-risk score to each customer. Sujata Dasgupta, head of financial-crimes compliance at Tata Consultancy Services, sees compliance staff moving into “higher-quality investigations”, with AI bots used for “more rule-based, repetitive screening tasks”. So for compliance professionals, the one metric they can influence is the quantity of cleared parties they can do business with, and the speed at which they’re cleared.
Searching for the Metric That Matters
Learning from these examples, we see they have one simple thing in common: they start by defining one key metric and then searching for the answer. They’re proactive, not reactive.
One of the most important traits you’ll find in successful organisations and their leaders is clarity. Clarity when it comes to knowing and understanding their business better than anyone. And clarity when it comes to understanding their clients, their culture, their people and their mission. The real challenge is to find the metric that matters – and let your organization’s talented people do the rest. After all, they’re the real intellectual property.
Once we acknowledge this, the technology question stops being ‘build vs. buy’ and instead shifts to revolve around collaboration and opportunities for partnerships. You start by bringing the one metric that matters to you, your leadership and the proprietary data you have, and then search for the right partner for the journey. That partner should be one who has the expertise to communicate effectively and truly understand your business objectives. But they should also have the capacity to adopt the mature technologies and platforms that already exist to enable you to meet your goals.
The most game-changing technologies for the maritime world are already in the mature stage of development. Rather than find yourself in Gartner’s Trough of Disillusionment, perhaps we should move onto a different AI – that of Adoption & Implementation.