Op-Ed: How Formula 1 can help vessel efficiency

Angus Whiston, Communications Director at DeepSea

by Angus Whiston, Communications Director at DeepSea

UMAS recently published a report which stated that, while the IMO’s GHG debates have mostly centered on the fuel transition, absolute emission reductions required this decade can mostly be unlocked by simply increasing vessel efficiency. Given that these targets are aligned with industry regulations, this should come as good news to the industry.

It’s well-known that the lowest-hanging fruit when it comes to boosting vessel efficiency, both from a cost and implementation point of view, is to focus on voyages—most of which are still sailed in the same way they have been for decades (if not centuries). Regardless of whether you’re operating to maximize TCE, on a fixed schedule, or somewhere in-between, logic dictates that there is one, single, optimal voyage plan to achieve your objectives.

Formula 1 has acknowledged this reality since its genesis. Finding that single best route and speed plan is the primary objective when the wheels hit the track. But, critically, there can be no ‘tried and tested’ plan for each course. Instead, it is a complex and dynamic formula involving the characteristics of each car, the particular weather conditions, and how the two factors interact. And the responsibility to solve this formula certainly doesn’t rest with the driver—or captain—alone.

Modern F1 teams have a “high-definition” understanding of their cars—harnessing over 300 sensors to find the winning answer. Christian Horner, CEO of Oracle Red Bull Racing, says, “Data is in the team’s lifeblood. Every element of performance—how we run a race, how we develop a car, how we select and analyze drivers—it’s all driven by data.” The analysis includes numerous approaches—but most recently it’s AI that is driving a new wave of disruption—allowing an unprecedented level of vehicle modeling and simulation to uncover new ways to boost efficiency and cross the line first.

Shipping must adopt this sort of approach. And the primary reason why is not regulatory. As in Formula 1, it’s purely commercial. This approach makes you win.

And yet, shipping continues to function in a state of “low definition” when it comes to data-driven thinking. The majority of the world’s ships still communicate with shore via one, manually-compiled email per day. Perhaps the one or two sensors that are correctly calibrated are used for basic reporting.

Shipping’s vessel behavior models—critical to finding the optimal route and speed plans—are usually basic fuel tables which aren’t used for this purpose, or generic models which don’t capture the individual characteristics of each vessel. Shipping’s charter party agreements are set up according to this reality: performance clauses (and the mountains of claims they inevitably generate) are a product of a lack of understanding and visibility regarding vessel behavior. This can all be summarized in one word: inefficiency.

Shipping urgently needs a high-definition revolution, and those companies that are to win the race in the coming decades (not just by overcoming regulations, but also by boosting profits) have already started on this journey. The pathway is now well-understood: collect high-frequency data from your vessels; create high-resolution performance models of each one; and harness those models to generate truly optimal voyage plans.

The costs are accessible: the data-as-a-service market is becoming highly competitive, and prices have dropped almost tenfold over the past decade. And most importantly, the results are proven—as our work with Wallenius Wilhelmsen, amongst others, has demonstrated beyond doubt.

Shipping and Formula 1 have a lot in common. Shipping may currently be well behind in the technology game—and vessel efficiency optimization a more multifaceted problem—but adopting the same principles is a sure-fire way to get yourself to the front of the grid, and cross the line first (rather than being forever stuck in the pit lane).