Better Decisions with Lean Data

When it comes to improving our health, a common starting point is the humble bathroom scale. Beyond just measuring weight, smart scales can analyse body tissue in surprising detail to indicate muscle mass, body fat, bone density or water percentage in the body. Although all these data metrics are an indication of health, they have to be put into context to be understood correctly – this is especially true for weight. For people who have an active lifestyle and practice a sport on a regular basis, weight loss is not always the main goal.

Many sports exhibit a particular relationship to body weight and composition, which accounts for athletes being weight-sensitive for a variety of reasons. Sports like boxing require athletes to be under a certain weight to compete in a certain category. In endurance-based sports such as running or cycling, body weight is instead optimised to maximise efficient energy use and metabolic load.

In the case of cycling, weight is not all about lighter = faster. It’s about finding the optimal balance of power to weight for the type of cyclist you are, the types of races you race and the goals you set. This includes a considered training plan that varies throughout the season as well as balanced nutrition and hydration to suit the goals of your desired type of riding.

Cycling offers a variety of touch points for people to engage with the sport on different levels – from picking up the bike to get to work, to using the it as a means to escape hectic city life on the weekends.

Cycling has become one of the most data-driven sports in the world. Compared to other sports, cycling is unique in that the average rider can have access to the same data tracking devices as professional cyclists. For competitive cyclists, data analysis can take the guesswork out of many traditional training methods and help them to train smarter. But for the ambitious non-professional rider who – contrary to the pro cyclist – obviously does not have a team of data analysts sitting in a truck during their ride, it is easy to obsess about the mountain of data and let gadgets take control of the experience rather than supplement it. On top of that, social networks for cyclists such as Strava are now commonplace, allowing them to track their athletic activity via satellite to later upload and share their activities online. Strava recognised the basic human urge to improve and added a few playful motivations for people to ride.

How can less data help us make better decisions when it comes to health and fitness?

At Takram, we run internal “open calls” for short research & development projects in which a small team can freely explore new ideas and technologies, producing a tangible outcome. During one of these projects, we took on the challenge of demystifying our relationship to health data in the context of sport. Looking at cycling as a case study, our aim was to create a product concept that changes the way we interact with smart health devices.

The first step was to understand people’s motivations, goals and challenges. We conducted interviews with cyclists of different levels of experience to understand how they are monitoring their health and training. Quite early on, it became clear that there is no one-size-fits-all solution. People have different motivations to cycle and set their own personal goals. Some cycle for fitness and performance while others enjoy the social aspect, riding for coffee and cake.

Through researching and testing current tools, apps and services ourselves we noticed that there is almost no limit to what people can track. Health trackers like smart scales or smart watches offer continuous monitoring to endlessly gather more data about the user’s personal health ecosystem.

The problem is that all that fragmented information can be misleading and distracts from the bigger picture of overall well-being. We realised that we have to take a different approach in order to make data more useful.

A case study for lean data

The starting point for our design process was a product that is present in almost every household: the bathroom scale. We designed OTO, a concept for an integrated health platform designed for cyclists to balance fitness, performance and well-being. Against the current trend of big data and the quantified self, OTO is based on the approach of Lean Data and explores how less data can help us make healthier decisions – on and off the bike.

OTO captures all the metrics that a usual body analysis would as well, but instead of displaying your weight, OTO encourages you to use it in a way that visually presents your body metrics. What is unique about OTO is not the individual components (namely, a body analyser, health tracker, weather forecast, and training plan) but how they connect to each other to create an experience that supplements your lifestyle, rather than dominating it.

Project film

Sharing insights and making ideas tangible is key. At Takram, we believe that the design process starts with the research. We created this concept film to share our process.

During the research and prototyping of this short design project, we discovered many new possibilities for creating meaningful interfaces between us and our data. Besides the context of sport and cycling there remains a whole range of exciting, unexplored opportunities.