We recently did a project in the health care field. The overall goal
was to improve the usability of a data collection app that was
supposed to accurately record every step of a detailed, half-hour
long medical procedure. The problem was that for some reason, there
was a unusually high rate of error in the data being entered into the
app by the care giver.

Now, these same users had been complaining to customer support and
account teams -- your normal user listening channels -- about many
aspects of the interface. But fixing those never seemed to fix the
inaccuracy problem. Wasn't until we conducted ethnographic research
that we discovered that the users were hiding a very important issue.
They actually weren't entering data at the time it was collected --
they were waiting for a couple hours, then entering data from (a
sometimes faulty) memory.

They did this for a variety of reasons relating to the interaction
design of the application, and fixing those issues did end up solving
the problem.

But because the users were ashamed to tell us how they were actually
interacting with the app in the field (I think it was a violation of
FDA rules, to some degree, and they felt bad about taking shortcuts),
our client's user listening channels weren't able to provide the
critical insight needed to fix the problem.

I suspect that as long as people are subject to cognitive bias, user
listening alone won't be able to diagnose all usability problems. 


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Posted from the new ixda.org
http://www.ixda.org/discuss?post=24074


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