Do you own a smart watch or fitness tracker that you haven’t used in a while? Several studies indicate that between 20-35% of users stop wearing them within the first six months. Furthermore, over a half of devices eventually end up in a drawer.
As development teams start to design the next generation of apps for wearable devices, UI experts and researchers are studying what it would take to have users wearing devices for longer. Gamification, financial incentives, points, levels, badges, and statistics are just some of the ways companies try to keep us engaged with their products. But so far, it looks like all that R&D effort is trying to provide answers to questions that may not exist.
The largest and most successful data-collection platforms we know today didn’t start out by developing a data-gathering product and then figured out how to entice users. Instead, they took the opposite approach. They provided something valuable to users first, and then collected data from the product.
I remember the amazing value I perceived when using a search engine for the first time. There was no doubt I would return to the service again and again. The search engine was the initial value proposition, but what those companies have evolved into now is quite different.
A decade later I joined some of the large social media platforms, like over 2 billion of us have at some point. They made connecting with new friends during my time at university easier. Because of this and the many other benefits of using social media, I unwittingly gave away vast amounts of my personal data.
We find ourselves in the current situation because the value these services bring is so utterly undeniable. They have become integral components of the internet and harvest the world’s information. So, we keep returning to their services daily, click after click, tap after tap.
So where does that leave a designer at McLaren Applied Technologies, working with possibly some of the most potent real-world data analytics capabilities? I say real-world data because we deal with quantifying the physical realm. Instead of clicks, searches and page views, we deal with context, position, forces, and time.
Decades of experience and expertise gained from capturing data through advanced sensors on our race cars has allowed us to explore how we can use data to improve human life.
For an example: The NHS, which recently celebrated its 70th birthday, is a wonderful service which has undeniably helped millions of people, but hasn’t kept up with modern technology. Users complain of a service which is slow and not tailored to their individual needs, doctors and nurses are overworked, and there are clear inefficiencies with the service.
Are we asking the right questions to improve it? What do patients actually need during recovery after surgery? How could we lessen the burden on nurses? How do doctors want to visualise data to make better decisions? Solving those questions first, before rushing into technical development work will ultimately make the service perform better. This will in turn make the data gathering substantially easier.
Our preferred approach is to keep user-centred design in the loop with technology and business throughout a project, from start to finish. Design research is a powerful tool for quick fact-finding and setting product strategies into motion. Ideas can quickly be assessed against user preferences, technology feasibility, and business strategies. This gives us an initial steer towards different outcomes.
For me personally, the real core of how to make good products that get used is what happens after the initial planning stage. Everyone working in product development has seen great ideas get diluted. Project teams can change composition, technologies can be updated, and business plans can shift focus.
We keep design in the loop precisely for this reason. The role of product design at McLaren Applied Technologies is to generate ideas, but also importantly to protect them. When we manage to deliver a product that is true to the initial value proposition, users will see their data as part of a fair transaction, and we can keep delivering value with the next product, informed by real-world user data.