How Lean experimentation is just a sexier approach to modern science

How Lean experimentation is just a sexier approach to modern science

I've been working on innovation for a while now. At VEON, as freelancer, as startup founder and as coach for Innoleaps. And all that time I've felt that to innovate is to setup an academic research project. Like writing a thesis. In the past few months, I hear more people mention the resemblences between the two. Here's my take.

Modern science

So let's start at the beginning. Galileo is considered by many as the father of modern science. In all Galileo did, he focused heavily on experimentation. He and others like him either observed an event - in academia known as deductive reasoning - or philosophized about a fictive event - known as inductive reasoning. My professor explained it by distinguishing between to observe a black swan and wondering "are there more black swans out there?" (deductive), and observing only white swans and wondering "are there any non-white swans out there?" (inductive).

And before you know it, you have a research question formulated. In today's world you then easily perform, way easier than back in Galileo's time, desk research. Google "black swan", read through Wikipedia and Britannica, maybe even a journal or two. You define a smart hypothesis that allows you to reject or accept it upon analyzing collected data and then start collecting your data. Which can take many forms; from interviewing biologists to observation and tallying. In the end you write down your conclusions. Done.

Lean experimentation

Now let's look at what Eric Ries and Steve Blank are telling us about how to innovate. At the core they emphasize going through a quick, iterative Build, Measure, Learn loop to validate ideas. If - as a startupper or corporate innovator - you have a new idea, something to overcome a pain, make sure you focus on validating others experience that same pain. Experiment. Get to a research question through deductive or inductive reasoning, define - again smart - measurements and formulate a hypothesis that can be accepted or rejected with collected customer feedback (data). Then, just like in academic research, there are many ways to collect the data you need. You can conduct user interviews, run surveys or measure engagement from a social media ad. Anything to confirm that other people out there feel the same pain you expect them to experience.

With data collected, you'll know whether people have the problem you identified, and you will have learned about their current ways of coping with it, their willingness to pay and directions for a solution to overcome the pain. Allowing you to decide to move forward to measure problem - solution fit and eventually product - market fit or leave your idea alone and move on (which only few people can, different story...).

See the resemblence? How in both cases we ideate through reasoning? Get a first sense of things by conducting desk research? And then collect data to help us decide on whether we are on to something or not? In academia a great finding leads to starting a PhD track in the same field, in business we register our domain name and build our first MVPs.

I often wonder why so few people apply what they learned in university in their daily jobs. People often mention the disconnect between university and our professional careers. Pretending that the educational institutions are outdated. But from where I'm standing... That seems like the other way around.