by Jeff Humble
Dear Reader,
Sometimes, that research phase just doesn't fit.
What can you do when everybody says no to the research phase?
Perhaps they have a reason for saying no. In many tech companies, a traditional research process can slow down the learning speed.
Upfront, traditional discovery research isn't the only way to do research. You can evolve beyond this problem-then-solution process.
Process models like Design Thinking and the Double Diamond make designers think that discovery always has to come first. Force-fitting a research phase at the beginning of every project won't earn you a trophy. In fact, it might be showing your managers that you don't understand how your company prefers to learn.
With a mental model of "research first," you may think your only option is to hide time for research in your projects while trying to meet your deadlines. Sure, there are ways to squeeze discovery in (see continuous research), but you can't always find the answer upfront.
Sometimes, users don't know enough about the context to provide useful feedback...especially when the idea is totally new.
You can conduct research while you deliver. But first, you must let go of the idea that research always starts projects.
Rapid experimentation is another way to research that starts with solutions, and it helps you evolve to better research practices in organizations obsessed with speed and numbers.
The experiment doesn't have to be coded or release-ready. It can be a scrappy prototype that tests the value behind your product ideas. The important thing is to test the value, according to the customer, before you jump to implementation details.
Here is what might be new in Rapid Experimentation:
These are the skills we teach in Designing Product Experiments: LIVE, and I've seen dozens of designers turn their design skills into experimentation skills.
Setting up an experiment takes time, but it's much faster than doing 20 rounds of upfront user interviews on an idea nobody understands yet. You can still supplement experiments with more traditional qualitative UX research to understand the "why" behind the experiment numbers.
Some scenarios where rapid experimentation can shine:
Remember, when an idea is new, sometimes the only way to learn about it is to put it in customers' hands and watch.
Everything is an assumption until it's in the hands of a user. Find ways to test your assumptions early and often. Testing can potentially offer more realistic insights than traditional research can provide.
What do you think? Is rapid experimentation worth a try?
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Until next week, be rapid experimenters! 🔬🏃♂️💨
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