Form A Hypothesis
One of the most valuable assets in the scientific world is a hypothesis worth testing, and since research suggests that they’re only getting harder to come by, they’re only getting more valuable. Consider this: even if a hypothesis is wrong — as they often are — the learning process that a clearly-stated hypothesis activates is priceless in itself. As Thomas Edison triumphantly declared to his friend Walter Mallory, who wrongly assumed Edison was discouraged by his many failed experiments, “Results! Why, man, I have gotten a lot of results! I know several thousand things that won’t work.”
The truth is, knowing that something won’t work is hugely valuable: it enables a team to move on, to iterate, and adapt. Most teams suffer from a lack of the conviction required to pivot — from a lack of “results-via-failed-experiments.” The critical question is, how to go about clearly stating a hypothesis worth testing? This is one of the primary benefits of the design thinking approach to innovation: it’s a systematic approach to hypothesis formation and testing.
I’ve noticed that, for whatever reason, folks in the design space tend to shrink away from scientific language. Perhaps it’s because the skepticism inherent to the scientific process grates against design’s (faux) promise of unbridled optimism? In my opinion, designers have a lot to learn from scientists, the foremost of which is a healthy appreciation for hypotheses.
When we’re empathizing with users and synthesizing problem statements, what are we doing? We are hypothesizing problems to be solved. When we’re generating ideas and embodying solutions into low-resolution prototypes, what are we doing? We are hypothesizing ways to solve the problems we’ve framed.
The shift I’m recommending isn’t a trivial, merely semantic one.
What’s special about calling the early outputs of the design process “hypotheses” is that such vocabulary reminds us to assume a posture of humility: we might be wrong. In fact, we probably are! But for whatever reason, when folks don’t explicitly acknowledge the guesses they’re ushering into the world and call them hypotheses, they’re far less likely to remember they’re likely wrong.
They’re far less likely to welcome “adverse” results as enthusiastically as Thomas Edison did.
Related: The Looming R&D Mystery
Related: Be Skeptical
Related: Talk To Real People
Related: Solve The Right Problem
Related: Humble Yourself
Related: Get Scientific
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Growth mindset expert Diane Flynn shares insights and advice for a more experienced generation of workers who might feel somewhat hesitant to embrace the collaborative superpowers of GenAI.