In most professions, process is a dirty word. Process usually indicates a top-down, autocratic set of gates that have been arbitrarily prescribed—steps that are imposed to keep people in check and to keep the industrialized machine humming. But in design, nothing could be further from the truth. For designers, process is the language of rigor, and a particular process nearly guarantees a desired outcome. Often, that desired outcome is innovation. I challenge my students to target appropriateness.

The process I teach my students is simple, and it looks like this:

  • Conduct immersive, ethnographic research. It's a bit of a paradox: The first thing to do when starting a design project is not to design. Instead, it's to seek to understand and empathize. The most direct path I have found to achieve this goal is through a form of participatory ethnography. Simply put, leave the design studio and enter the context in which work and play are done. Designing for the homeless? Go spend time with the homeless. Trying to improve community agriculture? Go spend time with farmers and gardeners. There is both an art and a science to conducting qualitative research effectively, but being there is one of the best ways to get started.
  • Synthesize the research to arrive at the "big rocks" of innovation. An insight is a provocative statement of truth about human behavior that may be wrong. A two-hour research session will generate more than a hundred discrete utterances, and so research with 10 participants will create a thousand pieces of data. By marinating in this data—literally embedding and immersing yourself in a war room of quotes, pictures, artifacts, and ideas—you will start to form connections that are otherwise hidden. You'll identify behavioral anomalies that fit outside your worldview. And by constantly asking and answering the question "Why?", you will arrive at these "big rocks" of innovation: statements about the future to hang your design hat on.
  • Sketch lots and lots of scenarios that introduce new products, systems, or services. The new insights describe design constraints, implicit in the context of the opportunity space, and so they act as artificial requirements: They provide a container to help you describe "good" and "bad" design ideas. Narrative—both written and visual scenarios—then pushes new ideas through the filter of these insights. Stories humanize technology and serve to emphasize the subjective qualities of value. When you tell a story, you bring a new idea to life. And when you tell lots of stories, you encourage divergent thinking—you identify a wide net of possible outcomes.
  • Visualize the "designed touchpoints" in real artifacts. Create things, because things make ideas tangible. If your stories identify a service ecosystem with digital artifacts, a physical wayfinding system, and a set of policies, build things that show digital artifacts, physical wayfinding systems, and a set of policies. This might be a flash prototype, a series of signs made out of foamcore, and a written document of rules and regulations. The process of artifact creation forces down-selection of ideas, where ideas that best conform to the artificial "big rock" constraints become more real.
  • Test the results with real people. Take your artifacts and have people use them to achieve their goals. You can test artifacts with even the most simplistic level of fidelity; people are able to get past duct tape and hot glue, and a low-fidelity representation of an idea will generate high-fidelity data for revision and further understanding.

There is nothing overly unique about this process: It's the same process I learned when I was in college, and it's the same process designers have been describing as far back as the 1940s or 1950s. But I've found students of this process are skeptical, and so they don't trust the process. Instead, they attempt to rationally argue why the process won't work. The arguments, and my responses, typically fall into two large categories:

  • The process won't work because I don't have any good ideas. Having a good idea is tremendously intimidating. When prompted to "be innovative," most people become anxious or shut down entirely. The corporate hierarchy of many organizations adds pressure to senior staff to have the best ideas, or to produce ideas faster than junior staff. But this process is not about having the best idea; it's about having lots of ideas. And because the criteria to determine "best" and "worst" are embedded in the process of synthesis, an artificial sense of objectivity is created by the team itself. The insights act as vetting criteria for ideation, so title and rank become irrelevant. Ideas emerge as natural extensions of the problem space, and the process allows the ideas to emerge in an intuitive and almost unpreventable fashion.
  • The process won't work because it's biased; the process won't work because our sample is too small. Eliminating bias is fundamental to conducting an objective survey or experiment. Participants should be randomly (not conveniently) selected, and enough participants should be selected to ensure the sample is statistically representative of a larger population. But our process is not intended to indicate a broad sense of want, need, or desire. Instead, the design process is (perhaps counterintuitively) about celebrating the extremities. We want to understand and relate to the peculiarities in the lives of our participants, and we want to observe their extremely local, unique, and discrete workarounds or strategies for dealing with technological complexity. We go out of our way to observe a small group of people, selected precisely because of their unique traits, and we don't minimize our bias—we actively celebrate it. Design isn't about predictability: It's about provocation. And innovation is risky precisely because we're creating something new. Attempting to minimize risk by seeking broad applicability forces a regression to the mean, blanding away new design qualities in favor of established, commoditized old practices.

The process of design is rigorous, methodical, and most important, dependable: It will always produce design results. Trust the process, and after you've arrived at a solution, reflect on the inevitability of that particular solution to emerge from the process you followed. In hindsight, the artificially established design insights create a powerful pseudo-objectivism, and within the constrained design space, designers find both innovation and appropriateness.