By utilising vast amounts of real-world port data, we make it easier to better predict things like laytime, terminal costs, and other factors that could impact the bottom line.

The old chartering tool created friction right at the start. It asked for too many details before showing anything useful, including the name of a terminal that users often don't know!
I redesigned PortSearch to remove friction at the start and help users get to answers faster. It’s built for speed, clarity, and exploration without demanding too much upfront.
Start broad, then refine: Users could now search using just a port. Instantly returning an average cost and time estimates. Port Search then suggested likely terminals to help refine results.
Switch ports without rework: Users often compare nearby ports. We let them do that from the same screen, keeping trade details intact and reducing repetition.
Faster access to large datasets: We removed pagination and added virtual scrolling, making it easy to scan thousands of port calls. Filters supported batch selection for more accurate cost modelling.

Port Search replaced the old tool with a faster, more usable system that supports exploration and unlocks value without the heavy data entry.
A cost benchmark was the most-used screen, but it no longer fit how users worked as their processes evolved. They still relied on the table for transparency but needed faster ways to spot issues like towage costs, contract impact, or volatility without digging through rows of data.
I ran a 5-day design sprint to explore how we could surface key concerns without disrupting the table’s role. We introduced a “traffic light” concept: subtle indicators to flag risks in context, which users could expand for more detail.


Users valued the added insight but didn’t want interference with their scanning flow. Even lightweight overlays caused friction. Later iterations moved to on-demand alerts triggered by the user, not the system.
The solution didn’t ship in its original form, but it directly informed the approach behind Port Search... proving that clarity, speed, and control matter more than layering on features.
The rain multiplier was meant to help users estimate unpaid time lost to rain, but it had become a source of frustration. Overcomplicated instructions turned a simple task into a slow, confusing process.
I simplified the tool into a quick calculator. Users now enter their port stay duration and immediately see how much unpaid time to expect, based on the current month. They can also adjust for future dates. The result is clear, instant, and doesn’t need instructions.

That last insight became the spark for the Port Search case study. Solving one small tool exposed a wider need: faster, more flexible ways to explore port time, costs, and restrictions.