On Dec 31, 2008, at 5:39 AM, James Page wrote:
What challenges me in what you say about your Data-driven Personas
is best answered by Chapman and Milham see:-
http://cnchapman.files.wordpress.com/2007/03/chapman-milham-personas-hfes2006-0139-0330.pdf
Their opening abstract shows that their lack of experience with real
data-driven personas:
"We believe personas are likely to lead to political conflicts and to
undermine the ability for researchers to resolve questions with data.
We suggest potential research to evaluate the Personas method more
thoroughly. Until the methodological issues are resolved, it is best
not to consider personas to be a means to communicate data.fictional
individuals."
Personas actually avoid political conflicts and are a key artifact to
communicate the data for researchers. So, their assumption, or
abstract is quite mistaken.
They are correct that there is no systematic approach to evaluating
personas, that the industry differs in their approach and attitude
towards personas. This is one of the reasons I started making data-
driven personas. I would agree that we need better rigor with the
approach, however, they seem to be throwing the baby out with the bath
water here.
They also assume that because there are only a handful of personas,
they can't possibly be effective, because some people might fall
through the cracks:
"Given several personas, there is no good way to assess whether the
group of personas appropriately represents the population of interest.
How many users does a given persona describe? How important are those
users for the project? If several personas represent several slices of
the population, how many people fall between those slices?"
Well, that's the point—80/20.
Several years ago, we did research for large grocery store chain. We
studied a few representative markets around the states and found that
people shop grocery stores one of three ways and create lists for
their groceries one of three ways. Over 300,000,000 people in the US
and they all fall into 1 of 3 methods (except for singles, who fall
into their own method, which makes 4 total).
Do some people fall through the cracks? Yes, but that's the point.
You're not designing for 100%. Designing for 100% will ALWAYS fail.
Designing for 80/20 has a much higher degree of success.
I'm a researcher first, designer second. I appreciate and advocate
rigor in research work. But the problem I have with academia's
approach to research is that often times they dismiss anything that
doesn't have 95-99% statistical significance, when frankly, in the
real world, that's rarely realistic or needed.
When you need 95-99% statistical significance, then do it. But know
when you do and don't and act accordingly.
Finally, they have some good suggestions:
* Have some teams create a product w/o using products and others
create the same product w/personas and see which one is more usable
(albeit I would change this to better, because usable is only part of
the equation).
* Give the research data to multiple teams, have them create personas,
and see if they create similar personas.
Based on their paper, my expectation would be that they have very
little actual hands on experience with creating, validating, and using
personas in practice. Their paper is much more theoretical than
practical.
My experience has been much different than what they speculate.
However, that could be due to the amount of rigor we put into our
personas at Messagefirst, the fact that they're data-driven, and that
we continually evaluate and evolve our methods.
The problem with personas isn't personas, it's the lack of knowledge
people have with creating personas based on data. Fix that and we'll
address the theoretical problems discussed in this paper.
Cheers!
Todd Zaki Warfel
President, Design Researcher
Messagefirst | Designing Information. Beautifully.
----------------------------------
Contact Info
Voice: (215) 825-7423
Email: t...@messagefirst.com
AIM: twar...@mac.com
Blog: http://toddwarfel.com
Twitter: zakiwarfel
----------------------------------
In theory, theory and practice are the same.
In practice, they are not.
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