We all love trucks a bit too much.
The world we live in today relies heavily on road transport to deliver goods and services right across the globe.
In the past decade, there has been a significant increase in its utilisation, which means more trucks, more drivers, and the potential for more accidents. The cost goes beyond human life too - there’s big business at play - as soon as a truck stops it is costing someone money.
Seeing Machines is a talented, global technology company who heard the call. They built a product - a device that (aside from tracking the usual telemetric suspects like location and speed) uses video monitoring in addition to a healthy dose of machine learning and artificial intelligence to successfully detect driver fatigue.
Not everything was crystal.
Let’s imagine you’re one of Seeing Machines’ larger clients with 8211 trucks making their way across 43 countries at any given time. Now consider the sheer volume of data being captured and sent back to base every single second.
Seeing Machines needed a smart, robust system that could help make sense of all that data, presented back to the user in a digestible way.
They had started building their own digital platform internally but needed help to implement a modern product design and development approach to get the right information, in a better way, to users.
Fatigue interventions rolled out in just the last 12 months.
Then we got a ticket to the party.
Seeing Machines initially reached out to us plug some holes in their development team, however we were soon trusted to reimagine their digital solution.
We embedded our digital team into Seeing Machines to design an approach that would allow for incremental change to the product development process over time. Our product team of agile coaches, experience designers and developers, worked in partnership with Seeing Machines to apply a modern product design and development approach to their web application that connects to Seeing Machines tech.
Our agile coaches helped Seeing Machines plan work and understand upcoming issues. Our designers helped focus attention on user needs and create end-to-end solutions that customers would love. And our developers installed design systems and new testing practices that drastically improved developer output.
Aye aye Capt'n
We underpinned the project with Agile methodology. Using product storyboarding techniques we created a new product roadmap, outlining where the project was up to and what was still left to build. With a new delivery date set to suit the reality of the work remaining, feature groups were established in Jira as epics and features broken down into key components, with a process established to first design a feature, before then building it in the following sprint.
05.The finer details
Let’s talk tech for a sec.
Our design team completely reworked the interface design, focusing on key areas such as access management, visualisation and complex multi-step forms received special attention to address key customer research findings from early user testing. The team created interactive wireframes to display functionality we then transferred the assets to developers in a seamless way. A design system was deployed, improving the seamless and perpetual flow from design to development and transforming the efficiency of the entire project.
One of the key challenges was the immense volume of data to deal with. The large amounts of video footage coming in every second from all around the globe needs to be stored, recalled instantly, and visualised with the utmost consideration for prioritisation and drill-down-ability.
If a driver is falling asleep, his or her safety quite literally depends on this design work and the efficiencies it created.
From a build perspective, our developers integrated early into the Seeing Machines team. We focused on first changing the theming approach, introducing reusable components and a set of standards for building up pages. As the component library was built up, a living style guide was created, allowing developers to visualise all components available in the platform and simply ‘repurpose’ them into any new feature being built. This approach built up large savings in execution time for new features, allowing focus to be shifted onto other key areas in preparation for the product to be released to market.
Kilometers of driving data has been logged using the Seeing Machines Guardian Live system.
06.Outcomes that matter to humans
Alongside the design and development of the Guardian Live software, Seeing Machines engaged us for one extra gig - to map out their Aftermarket service offering. The objective was to work out how they currently delivered value to their customers, and how they might improve that service delivery in the future. With open books, we viewed the organisation. We unpacked every single interaction at every single touch point for every single user. This service ecosystem mapping allowed us to identify key pain points and take a human-centred approach to the design process
This process has transformed Seeing Machines’ digital ecosystem. To date, Seeing Machines’ Guardian system has tracked over 8 billion kilometres of driving, and detected more than 11 million distraction events in this time. Just in the last 12 months of use there’s been more than 230,000 fatigue interventions rolled out to drivers. To say this one is having an impact is an understatement.