A couple of articles caught my eye today because they tie in well with my Intuition vs. Science in design post from yesterday. In Design and uncertainty Ellen Beldner writes about an essential characteristic for every designer: acknowledging that your assumptions will be wrong more often than not. She also makes a great case for usability testing:

The problems come when you don’t admit, as a designer or product person, that intuitions based on your mom or yourself may or may not extend to what most other people actually do. So a designer who seems like a hotshot Howard Roark out of college may be great for that one particular project. But when you ask him or her to work on a design for a domain that they don’t “intuitively” understand (since they don’t have years of experience being within that particular community) they’ll flail if they don’t know how to turn to research and data to inform their opinions.

I also love John Lilly’s advice to design like you’re right; listen like you’re wrong:

You should always design the product you think/believe/know is what people want — there’s a genius in that activity that no instrumentation, no data report, no analysis will ever replace. But at the same time you should be relentless in looking at the data on how people actually use what you’ve built, and you should be looking for things that show which assumptions you’ve made are wrong, because those are the clues to what can be made better.

This all comes back to that necessary balance between science (hard data) and intuition. Usability testing and contextual research help us understand unfamiliar domains enough to kick off the design process. Intuition lets us meet those users’ needs in creative ways. And analytics, combined with qualitative user research methods, help us figure out where we got it wrong and how we can do better.