change to survive. We can’t continue our practice on the current trajectory, pretending the environment around us is static. If our research methods don’t currently feel outmoded, they will within the next five years. These trends are not mere “blips” on the radar, but structural changes to which we must adapt to avoid being pushed aside. While the core principles of usability are universal—active user involvement, iterative and multidisciplinary design, appropriate pairing of users and technology—our techniques and methods need to catch up.

Looking more broadly, the usability community must find ways to embrace these trends, rather than hide from them. Certainly, there are obvious steps we can take to revise our methods, retire outdated models, and retool our own skills. But these trends also push us away from artificial testing and toward richer and more realistic data. The growing pains are hard, but if we capitalize on these trends, we can drastically improve the user experience. Even better, we can also increase our market influence, making us better predictors of user behavior, better advocates for true user needs, and better critics of design work.

To our credit, there are glimmers of hope, where usability has shifted to address the new computing environment.

• Revising our work to fit with agile. There are significant efforts toward “agile usability,” to address the challenges of rapid deployment. Online giants like Google and Amazon deploy design alternatives, review the results, and then revise the products (often without custom-

ers realizing they were part of a “user test”). Groups like 37signals and A List Apart offer recommendations and guidelines for adapting user-centered design within fast engineering cycles.

• Using ubiquity to our advantage. Researchers are beginning to reuse artifacts from the “always on” culture for design purposes. Public photo-sharing sites like Flickr can be mined for photographs (and timelines) surrounding specific events or topics. In our MAYA work, we used Flickr to identify what visitors photographed at trade shows (i.e., to determine what content was engaging and what was ignored). Flickr provided insight into many different trade shows, users, and patterns that would have been impossible with other methods.

• Breaking our labs into pieces. There are significant efforts to break down usability labs into smaller, configurable components. Hardware costs have dropped significantly, and lightweight testing suites like Silverback have drastically reduced the price of data collection and analysis. Companies are shifting toward the “lab in a bag” model, where teams are dispatched with a prototype, an augmented laptop, and a video or still camera. The lab can travel to the participants and their context, rather than trying to squeeze participants (and their whole external life) into the lab.

• Making our methods contextual. Guerilla methods continue to evolve, improving the data while reducing the overhead. Many of those methods are contextual, helping to move research closer to the field. There are evolving

methods for “quick turnaround testing” (with a focus on speeding up the analysis process), “ listening labs” (which employ contextual, user-driven tasks), plus a ton of revisions and extensions to paper prototyping. These lightweight methods are designed to fit into smaller time frames, deal with looser requirements, or make the testing mobile.

• Embracing users as designers. Lastly, there is a growing push on collaborative research and participatory design. The users work closely with the usability and design team through diary studies, repeated interviews, and in-home testing. At MAYA, we’ve used long-term participatory design to develop a home monitoring system. We sent users “product kits” that they used to augment their home with “ sensors” (made from Post-it notes). We asked users to document the sensors with notes and photographs, and then we would page the users with contextual alarms (e.g., potential leak in the basement) and discuss their response (e.g., needing to call a plumber). This “usage data” helped us to identify unmet needs in the market, before we even began to prototype the system.

ABOUT THE AUTHOR
Katie Minardo Scott is a
designer and researcher at
MAYA Design in Pittsburgh,
Pennsylvania. Her work
focuses on organizing
complex information for user understanding
in domains like intelligence analysis, situa-
tional awareness, medical diagnostics, and
engineering research. Scott holds a B.F.A.
in design and a master’s in human-comput-
er interaction, both from Carnegie Mellon.
She is also a contributing editor for this
magazine.

May + June 2009

DOI: 10.1145/1516016.1516018
© 2009 ACM 1072-5220/09/0500 $5.00