Rise Science came to IDEO with a challenge. The young startup had built a robust data platform for college and professional athletes to track their sleep and adjust their behavior so that they played at peak performance. But for the players, the experience was challenging. Rise expected athletes to look at data-driven charts and graphs to determine what decisions to make next, but players struggled to find those insights. Rise was convinced they just needed easier-to-read charts and graphs.
What Happens When Data Scientists and Designers Work Together
How a sleep app became something users really wanted.
March 05, 2018
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Summary.
Instead of walling off your data scientists to crunch numbers all day, integrate them with your design team. A human-centered approach to data science is essential for developing smart new products that consumers can actually use. Instead of a version of data science that is narrowly focused on researching new statistical models or building better data visualizations, a design-thinking approach recognizes data scientists as creative problem solvers. We’re not suggesting that the disciplines of data science and design merge, but rather that if practitioners work together and learn each other’s art they will produce better outcomes. Many of the techniques used in design thinking approaches — such as user research, analogous inspiration, sketching and prototyping — also work well with data-driven products, services, and experiences.