In an era of quickly evolving technology, the adoption of UX design for life sciences will benefit greatly.
FREMONT, CA: Analytical software for life sciences with poorly designed user interfaces can lead to unproductive research and can be very time-consuming, tedious, and frustrating. UX (user experience) design possesses great potential for scientific software that handles big data.
The best pharmaceutical companies wish for their scientists and data analysts to have the most effective tools possible. As an industry, life science is vast, and the industry collects and leverage vast amounts of data. The technologies behind these complex data are highly robust and getting smarter by the day.
It is sometimes easy to forget that the real users will have to handle this information. Interfaces and user experience act as the conduit between technologies and the user. A user-focused approach to understanding users’ needs leads to informed decision-making about what data must be shown and the best ways to display that information.
Understanding User Experience (UX)
Big data will be complicated as ever, but that doesn’t mean the user experience must be complex.
UX methodology is a collaborative and iterative process that debilitates innovation to solve a problem. UX design helps to maximize the user’s satisfaction when using a product. When creating software, it does not matter how powerful and robust the back-end system and the product data are, if rendered by an inaccessible and unintuitive, unengaging UX.
User Experience (UX) Principles for Life Science
Prioritize information- Crucial information should be at the top of the screen because this is where the user’s eyes are more likely to be drawn. This will give the user a quick overview.
Logical layout- Layout should be easy for the user to understand and follow—consistent formatting and design throughout the application. If the dashboard contains several tabs, each tab should have a similar format, styles, and layout.
Think through users’ mental models- With software applications, users expect a specific sequence of events. When dealing with big data sets, it is essential to align the software’s conceptual model with its mental model.
Oversimplify functionality- It is essential to show functionality clearly and not to hide any vital feature under drop-downs. When creating an interface, less is more.