Welcome back, once again, to Project Medusa. This final installment in our three-part How-To series aims to illuminate the last phase of any design research project: what are you to do with all the information that result from your brilliant effort? How do you decide what's relevant, and what's not? Needless to say, it can be a bit complicated. Many of the considerations introduced earlier are also helpful at this stage: remember your goals, and understand your audience (which shifts now to whoever you're preparing the research results for.) Confused? Visit Part 1 for a more thorough introduction. If you recall Part 1 but missed Part 2, now's your chance to catch up.
While there are no right or wrong answers in design research, not all data is equal. Assuming you've carefully prioritized your goals and outreach, it's now time to prioritize results. At Ziba, we use a four-part process to synthesize the data research yields.
1. Aggregate the data.
This could mean digitizing handwritten responses, stacks of sticky notes stuck to a wall, dozens of photos printed, or whatever works for you and your material. You'll need to be able to see the data—and ideally search through it efficiently—before you can plunge ahead.
2. Sort for theme(s).
Like goes with like, and making logical groupings of related information will help you identify the trends and anomalies within your data set. Embrace the granular: this is most likely the only time you'll look at each and every survey question, listen to every minute of recorded discussion, and squint at all those doodles. Stop worrying about your goals, momentarily, and evaluate your results as honestly and objectively as possible. Everything is allowed to be interesting, at this stage. If, on the other hand, you feel overwhelmed with the amount of data you're confronted with, the sorting process will allow you to reduce complexity.
Themes emerge as you connect the strongest trends in the data to your hypothesis or hypotheses. Think of it as a naming exercise, if you're stumped: with the data sorted into buckets, each bucket needs a concise handle. There may be some hard choices—fascinating but quirky individual responses sometimes need to be cast aside if they fail to play well with other, larger groups of more typical answers. Force yourself to make decisions about what's meaningful and what can actually have an impact on the work to come.
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