Another form of assignment I use is intended to develop craftsmanship.
Meet someone who has completed four years of design education and ask them to reflect on their education, and they’ll likely tell you stories of the dreaded foundations assignments. These craft oriented projects focus narrowly on a single “core” of design, like color, or line, or texture, or shadow. I remember some of these projects from my color theory class. We were to select a magazine layout, pin it to a board, and examine it. And then, our task was to recreate the layout, exactly, using tiny 1/8” square pieces of colored paper. It took forever (my memory of freshman year is a bit tired, but I recall it taking close to 100 hours), and at the time, we all questioned the point. What on earth could we learn from such a menial and monotonous activity, and how was this a good use of our really expensive education?
In fact, the foundational year of design education is full of activities like this. Paint a hundred color blocks a single color, but with a complete spectrum of saturation. Draw every letter of a single typeface, as realistically as possible. Sand a perfect sphere out of a cube. Sand a hundred perfect spheres out of a hundred cubes.
In a word, these projects were intended to teach craftsmanship, and many have historic roots in Bauhaus education, or pre-Bauhaus arts and crafts approaches to the production of artifacts. By focusing on a simple, contained, and tedious task, students form tacit skills necessary for visual communication. Specifically, these projects offer some specific benefits to students.
First, Craft-oriented design projects help develop learned behavior related to visual acuity and fine motor skills. By performing a task over and over, we can focus attention and increase speed, precision, and the “automatic” quality of an action. A sense of fluidity and ease is developed during the process, and students gain confidence in taking visual action without introspection.
Additionally, craft-oriented design projects force students to “look closer”, and encourage them to consider the details. Details are individually small and insignificant, but in aggregate, detailed design decisions contribute to a sense of thoroughness, completion, professionalism, and refinement. Students learn what a material can and cannot do, and are able to see how they can both respect and control a given material at a detailed level of precision.
The craft of strategy, interaction design, and entrepreneurship is not the same as the craft of more traditional design disciplines, like graphic design or industrial design. We already discussed foundational skills like contextual research, synthesis, service design, usability evaluation and product management. Craftsmanship in these contexts is in inference.
We don’t typically think of an inference (a leap in logic) as something that requires craftsmanship. But this is one of the fundamental skills of strategic design work, and it’s something that can be practiced and refined over time. Inferences are important to the design process because, to create something new, we need to leverage incomplete (and often conflicting) data.
When they are first instructed to make inferences, students struggle. They’ve been trained, often from early stages of grade school, that making leaps in logic is a bad way to think about the world. It’s sloppy science, and most of our education is rooted in a scientific, logical, rational approach.
The positivist way of thinking that they’ve learned is appropriate for learning science and trying to understand and explain natural phenomenon. But it doesn’t make sense in a creative field, where our goal is to make new things.
Our profession is not a science, and we aren’t trying to prove theories and hypotheses. Instead, we’re often trying to provoke creativity. This provocation comes through the process of synthesis we already described: combining ideas in new and unexpected ways, developing insights from research data, identifying places where behavior can change, and creating simple visual models and diagrams of complex ideas.
When instructed to make inferences, students push back and demand more data. They constantly feel that, no matter how much research they have conducted, they don’t have enough to prove that the ideas they develop are good ones. They are scared. How can they be sure that their designs will work?
Simply, they can’t be sure. They can minimize risk through testing and iteration, but the success of an innovative new product, system or service is unknown because of its newness.
Craftsmanship here means making “good inferences.” They don’t always have to be believable, but students need to become comfortable “dialing up or down” the inference to match their intended level of innovation risk. Plausible leaps lead to less risky, but less exciting, new ideas. Larger leaps are less believable but drive towards more disruptive concepts. Understanding how to think about the impact of a leap on creativity is fundamental to establishing craft in inference. And, like any other craft-based skill, this requires constant practice.
We practice this skill each time a student goes through an ideation or prototyping cycle. I constantly push them to make their ideas more and more far-fetched, and to leap away from the gathered data and towards the realm of the unbelievable. And then, we discuss how to pull these ideas back. They sketch the crazy, but they also sketch the more believable. We compare their ideas to the research data. Can they track a direct line from the data to the idea? That’s a tame idea. Tame doesn’t mean bad. Often, successful innovations are incremental, and slight inferences are more appropriate.
This leads to a conversation of context. We review and consider the social and behavioral context for their work, to discuss the appropriateness of new ideas. For example, in the context of a new government service, students may have conducted research with government employees and citizens, and as they synthesized that data, they developed a series of insights about the behavior they observed. Some of the insights are believable, because they map one-to-one with the user data they observed. Some insights can be more readily challenged, as they make larger inferential leaps from the data. And some insights are outright unbelievable.
I can help students realize that government is typically a staid and conservative environment. If the level of inference is directly tied to the level of disruptive innovation, this is not a context that benefits from larger leaps—these will likely be met with skepticism, and their new products and services will be less successful.
Students need to explore different contexts to juxtapose different levels of speculation. This means that we assign a number of different styles of project, including civic engagement/government work, consulting-style visioning projects, and more traditional corporate work. This helps students practice craft through inference. Over time, and through this practice, they become more and more fluid and comfortable with this skill. They become more crisp in their inferences, just as they would become more and more detailed in sketching through repetitive practice.