Minimum Viable Research
So you have a new research question. You’re reading a paper, or a book, or a news article, and a hypothesis forms in your head. Or you have a new idea for resolving an important conundrum in your research.
What do you do?
In startup and business culture (or certain segments of it, at least), there is the concept of the minimum viable product. This is basically the smallest version of a product, stripped down to its barest essentials, to see whether it would gain traction in the market. Create a minimal product and iterate quickly instead of spending a year building something that might not take off.
I think this concept is instructional for research. Minimum viable research would be to ask yourself: what is the simplest thing I can test to see if this idea might go somewhere? Rather than spending a week doing data analysis, is there a 1—2 hour way to see if it might work, or if it is trivially falsifiable? Can you structure your research inquiry so as to fail fast, to not spend excessive time trying to fit a model that just won’t work?
Producing the final research results, paper, or thesis will still take a substantial amount of time. It’s also easy to take this line of thinking and fall into the least publishable unit trap. And important results can come about when some persistent soul spends an inordinate amount of time trying something that others don’t think is promising — for example, it’s my understanding that Yitang Zhang’s recent progress on the twin prime conjecture was based on an approach that was generally considered unpromising.
But I think it’s still a useful mode of thinking. For one thing, it allows you to iterate quickly on research ideas. To try a bunch of things, find a few that aren’t immediately false, and spend your time pursuing those with abandon.
Wizard-of-Oz studies are one common example of minimum-viable-research thinking. Rather than build a full product, build an interface and fake the computationally hard (or impossible) parts to study how people would interact with and use it.
The final form of my help search project is the result of learning some of this. I had grandiose ideas for things to try, but my collaborators and mentors at Autodesk wisely pushed back and encouraged me to design a simpler experiment. The resulting study was both possible to actually complete in the course of an internship and a more straightforward approach to validating the ideas I wanted to try.