Hi Michael, et al, I helped formalize persona creation methods while I was at Cooper, and I recently spoke on the subject of some common persona misconceptions with a current Cooperista, Steve Calde. Please see http://www.devise.com/further_reading and look to the bottom of the page for an embedded version of our "Death to Personas! Long Live Personas!" presentation.
But I sure wish you'd posted your concerns about personas before that presentation was authored, as the three you raise make for interesting topics of discussion. :) It seems to me that what's missing most here is a grounding in their formal practice. (For that, we can all look forward to Kim Goodwin's upcoming book!) But here goes a quick pass at addressing your concerns, especially the first one which nobody's really targeted yet in this thread: 1) Frankenstein. The persona creation methodology does not involve one "combin[ing] the various data points into some mock person". Instead, each individual's characteristics are mapped against specific dimensions of interest discovered during field research (ideally!!). Then you'll do it again for another dimension, and another and another. For example... if a key dimension of interest is tech-savviness, you'll map the place of individuals A, B and C on that spectrum, and then you'll map their place against another dimension of interest such as concern-about-security. And then you'll see what kind of pattern has developed by (for example) seeing that B & C are both tech-savvy and unconcerned about security and are also grouped on a variety of other dimensions. And A is an outlier who's not tech-savvy and is concerned about security, and also isolated on a variety of other dimensions. Voila, you have identified two separate user archetypes, one fed by B&C data and the other by A (this being a simplified example, of course); they are proto-personas who represent patterns in your research data. They are not an artificial combination of disparate body parts, to refer back to your proposed monster. ;) 2) Efficiency. How efficient is it to share a bunch of numerical data points, versus how much more efficient is it to map those data points onto a consolidated graph? The unification of research patterns into a single, narrative user archetype is fundamentally an efficient method to model one's ethnographically-inspired research. It's similar to making graphical models of complex workflows, or diagrams of contexts of use. Models are inherently more efficient than discursive texts or indexes of findings. The narrative form of a persona description can be taken too far, however, and this is a problem discussed in our presentation. Overly biographical and life-goal-oriented personas can be distracting and are indeed inefficient for teams to consume. It takes some practice to find the right level at which to document personas, and often for me still involves fine-tuning for the audience at hand. 3) Variability. Hopefully my quick elucidation about the original persona creation methodology helps you to see that the mapping of individuals to dimensions of interest is a relatively scientific method. There are occasional disagreements in the research team about where to place an individual on the scale of a dimension, but such disagreements tend to be resolved quickly and usually indicate there are multiple dimensions of interest in that one area. And having taught the Cooper U Interaction Design Practicum course, I can attest that different classrooms filled with fresh attendees have no problem with repeatedly mapping and identifying the archetypes originally discovered in the research data. I look forward to learning more about the relationship between validity vs. reliability from that document Josh sent around. This morning I did quickly peruse the Chapman-Milham Personas piece. It's probably statistically true that "as features are added, the overall probability of a composite decreases". That's why it's utterly crucial that personas be created and then utilized within a specific domain -- one should not re-purpose personas from a research conducted around virus software, for example, to a design problem on cloud computing; to do so would expand and re-consider their characteristics using fiction, not fact. As for their repeated points about it being "unclear about what data underlies these"" personas...well, yeah, that's what you get when you write an academically-inclined paper far removed from the research & design process. ;) The data was there for the team to use but it generally isn't passed along to the client. Still, I think their proposals for future research are excellent; and to their first suggestion, about creating a set of customer data and giving it to independent teams -- that's what I've seen done at Cooper U with repeated validity. Personas are not any kind of be-all end-all method, so don't misconstrue my points. They can, however, be a powerful tool in a designer's toolkit. And it's essential to remember that no design process stops with personas...they are a most helpful input to a scenario-based approach to design. Hope this helps! Cheers, Liz Vice-President, IxDA CDO, Devise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Posted from the new ixda.org http://www.ixda.org/discuss?post=35624 ________________________________________________________________ Welcome to the Interaction Design Association (IxDA)! To post to this list ....... [EMAIL PROTECTED] Unsubscribe ................ http://www.ixda.org/unsubscribe List Guidelines ............ http://www.ixda.org/guidelines List Help .................. http://www.ixda.org/help
