A Method to the Reason

crop faceless multiethnic interviewer and job seeker going through interview

One of the meanings listed by Dictionary.com for “reason” is to think through logically as a problem; [to infer or conclude]. The capacity to reason is one of the things that separates humans from other life forms and has impacted everything from philosophy to science to medicine to math and on and on. Over time philosophers and scientists have come to classify reasoning into 4 types.


  1. Deductive Reasoning – This is the process of reaching an inference or conclusion based on widely accepted facts or things already known. An example would go something like this: a. All golden retrievers are dogs b. My dog Bodhi is a golden retriever c. Therefore, Bodhi must be a dog.

  2. Inductive Reasoning – Drawing a conclusion from a set of observations. This is the type of reasoning used with Qualitative Research and has important implications for Product Research I’ll explain later. An example would be: a. The sun has always risen in the east up until now b. The sun will rise in the east tomorrow.

  3. Analogical Reasoning – Finding commonality between 2 things such that information known about 1 of the two things can be applied to or explain the other. a. Elon Musk is a businessman and a mortal. b. Jeff Bezos is a businessman. c. Jeff Bezos is a mortal. While I love a good analogy for explaining or teaching, I don’t necessarily like it as method of reasoning. It generally uses too small of a “sample size” to be reliable. As an example: a. Kelly Slater surfs and is a male. b. Bethany Hamilton surfs, therefore Bethany is a male.

  4. Abductive Reasoning – Similar to Inductive but not quite the same, abductive reasoning involves seeking the simplest conclusion without positively verifying it. As an example, suppose you find a red marble near a bag of red marbles. You might infer that the marble came from the bag. This type of reasoning has important implications for machine learning and artificial intelligence.

Scientific work, whether Normal science or Revolutionary, normally takes years or decades even. The truth is gleaned from a meta analysis of dozens or more sets of research. In the “real world”, we simply don’t have time. That’s where Product Research diverges from scientific research. Product Research is built around Grounded Theory which is a form of inductive reasoning. If we wait until enough evidence exists to consider it as conclusive as deductive reasoning, we will likely have long missed our opportunity in the market. Grounded Theory provides a basis to draw conclusions from qualitative research. The onus is then on the researcher (the interviewer) to uncover what is really going on and what is the problem we might solve. This is one of the reasons it’s so important to start broad, stay openminded and attempt to avoid bias. It’s also the reason that the ability to test and fail both ideas and assumptions is so important. We know this reasoning method isn’t perfect so we must be good at revealing when it leads to an invalid conclusion. This method is not as deterministic as a deductive exercise but give maximizes our chances of going fast and innovating. I’ll end with a quote from Thomas Kuhn who wrote The Structure of Scientific Revolutions: “Truth emerges more readily from error than confusion.”

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