In this era of unprecedented uncertainty, many factors are coming together to cause a revolution in the research and insights sector. These factors are coming together to influence Lean Research that is experiment-driven and focused on setting up experiments to see what consumers will do in response to an offer, a new product in their hands, or another behavioral way to test the critical assumption.
These factors are coming together to influence Lean Research that is experiment-driven, and breaks down the proposition into the riskiest pieces or assumptions, and tests those in order of riskiest to least risky. This prioritizes research time spent and gets ideas to market faster, or conversely, helps teams identify ideas to abandon more quickly because they haven’t been fully built out and brought through the launch cycle before realizing that they aren’t able to meet key hurdles of desirability, viability or feasibility. In this video, we unpack more about experiment-driven research and the testing of critical assumptions. Behavioral science advancements have caused the second mindset shift: as researchers, we’re responsible for looking at what people do, not what they say they’ll do. With this mindset, tests can be set up to see what consumers will do in response to an offer, a new product in their hands, or other behavioral ways to test the critical assumption.
As we talk with innovation and insights leaders, these shifts in research paradigms have provoked lots of questions about how exactly these types of experiments come to life, and what principles to follow when thinking about what sort of experiment to construct to test your riskiest assumption.
Coming from the traditional research world where specific methods are qualified for testing specific objectives, this experiment-driven research world can feel like a bit of a “wild west” where anything goes. Early on, everything in Lean Startup revolved around developing an MVP, or minimum viable product. That was a pretty linear solve; go make a low fidelity version of the product that a consumer can interact with and insert that prototype into their life to see what they do with it. While this is a great experiment type, it’s important to note that it’s only one potential experiment type. Things felt off for us at The Garage Group pretty early on in MVP thinking when building an MVP didn’t actually give data for the riskiest assumption, and/or building an MVP meant over-building and taking too much time or money, when another experiment type could have been leaner and still high rigor.
Here is a core set of principles that give guardrails when thinking about what sort of experiment to construct to test your riskiest assumption (or biggest risk to your business model’s desirability, viability, or feasibility.)
“You are looking for clues that help confirm or deny your assumptions….your goal is not to compile statistically significant answers. Instead you want to look for patterns that will help you make better decisions.” – Giff Constable
We’ll be back next month with another install into this Lean Research series: examples of types of experiments that we’ve run with clients over the past several years.
We don’t want to leave you hanging, though! If you’re on a BigCo team and are working to implement this experiment-driven Lean Research, check out our research capabilities to see how we might be able to help!