Nautilus Labs helps ships reduce their carbon footprint by making data accessible and understandable.
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Nautilus Labs wanted to deliver operational insights about fuel efficiency from the sensors onboard. Most of the analysis products on the market required highly technical software that only specialised roles could understand. This made it difficult to access and use for real-time decision making.
As the founding Designer, IĀ helped the team identify opportunities to help Shore-side Operators and Captains make sense of crucial performance data so they could save money and reduce environmental impact.
When I began talking to ship owners, shore-side operators and captains we learned that there were many ways we could approach this. We knew we could recreate various industry artefacts with higher quality data and remove the legwork of manual reporting but realised that still wouldnāt address the real pain points many of our users were experiencing.
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Ship operating profiles are presented in overly complex reports that are difficult to understand. We discovered this resulted in low accountability around vessel performance related issues, not because people didnāt care, but because they didnāt have the right tools to be proactive.
Through speaking with shore-side operations teams we found that important insights about barnacle growth on the hull were buried in multi-page reports of fine-grained, unnecessary information that needed to be requested from another department entirely, often getting lost in email threads and quickly becoming out of date.
Similarly with engine performance we found that the sought after information was stored in clunky, complicated software and therefore was left to the use of a select few that had been trained on how to access it. This led to siloed information between departments and a lack of transparency.
When we asked various customers to share how these reports and information were used we discovered everyone cared about the same handful of thingsāthe impact on fuel consumption, how it would affect arrival windows and knowing when maintenance needed to be scheduled.
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We also discovered an interesting workflow where Operators and Technical team members were taking screenshots of trend lines as a way to figure out what was going on and we saw an opportunity to bake this into the product and create more transparency between departments.
We were able to learn the story the data was telling by creating quick models and visualizations in a Python notebook.
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Once we validated the usefulness and understandability of the data with our users, we brought the visuals into the product. This allowed us to layer in rich information into easily decipherable trends and KPIās that anyone across the organization could use.
We created a platform that supports and promotes collaboration by surfacing anomalies and performance deviations in one place. Teams are also given the ability to comment, assign and resolve events that require attention. We were able to take important matters outside of siloed email threads and complicated reports and funnel into a single, consolidated workflow.
