Cold washing; Mixed linen; Max spin; Start, repeat.
We should be even more skeptical when we want to believe.
The “new wave” of business management and innovation “truths” are mainly about selling a point. They often advertise models, not to help you work with reality and be less wrong, but instead are nice & shiny ideas that have the potential to sell books & conferences and, altogether, help their author gain a place in the pantheon of “those who make authority”, not because they’re necessarily right about anything but because they “convinced” others to believe in them. At least, if it’s not the intention, this is a recurring pattern.
If there is something recent years have demonstrated us pretty well, is that ideas don’t spread based on their “righteousness” or “soundness” (if I may formulate it that way): adoption (quantity) is not, by any means, a measure of quality.
This is unfortunately true for a lot of things.
Business and innovation are these kinds of special places where, despite the common trope that “business people are rational beings” because “they look at the numbers”, we all accept too easily to suspend our disbelief (something better attributed to movies, games, and stories). However, I think that 1) we are often willing to give too much credit to business people; 2) that this idea is inherited and spread (unintentionally) by business people themselves (i.e. Homo economicus); and 3) that on the contrary they are very irrational people, run by emotions, and stick to whatever idea please them the most –spoiler: they are humans after all.
This leaves the space, especially innovation, full of magical thinking and misplaced faith with extra-layer blindness: people in real need are willing to quickly trust anyone with anything that approximate an answer. This is something shared with the overlapping space that is Design, from which things like the (in)famous Design Sprint originated   .
Bigger the claim, greater the need for evidence
A recurring theme in innovation (and design) is that if some companies succeed and many others fail, this is (probably) because the former are doing something better (or differently) than the latter.
This really really really (really) not a new idea.
Now meet Alberto Savoia, an engineer turned innovation coach, whose book is praised by some in the field to be an insightful and novel approach. If you are not familiar with it, I invite you to take a look at this video 👇
Well, I have some issues with the redefinition of “prototype” and the false opposition to the made-up neologism “pretotype” –but apparently, people get hyped with little these days. We have to note, interestingly tho, that a pretotype posses all the characteristics of a prototype (made for test, cheap & quick to build, etc.), except the guy didn’t invent the term so he cannot sell books about it 🤷♂️
Funnily enough, this seems to be a trend these days to re-invent or simply rename and rebrand™️ already well-known things. Guys, it’s cool to be open to new things, but when… they are actually new.
Anyway, we are introduced to the concept of “The Right it”, an ontological proposition of the supposed “thing companies must do to succeed” which is literally the rebranding (again) of the notion that “some companies succeed because they do the right thing and others don’t because they do the wrong thing”.
Well, it has to be said that:
- Even if we accept as true that “some companies succeed because they do the right thing”, it doesn’t necessarily follow that “others don’t because they do the wrong thing” (e.g. this might be that companies that fail are doing the same things).
- Either way, you cannot address the latter with cases that validate only the former. Here we are given the impression that the proposition is backed with research, but the same old selection bias applies: looking at examples that confirm our prior belief tells us nothing about examples that might invalidate it.
- Most often than not, those “research” are mainly based on context-dependent anecdotal evidence (e.g. interviews with C-Suite board members) and provide, at best, a very weak correlation. As a reminder, here’s a simplified graphic of the different levels of evidence.
- Mr. Savoia admits in the video, when talking about products that failed, that he doesn’t know “why it failed or what happened here”.
- This doesn’t prevent him to claim that there is a “Wrong it” and that to avoid it you have to start with pretotyping.
Looping back to this idea of stories (and extrapolating stories from anecdotes) and our willingness to suspend our disbelief, it is interesting how Mr. Savoia praise what Elon Musk supposedly did that made Tesla succeed (causality?), and which should be evidence for Savoia’s proposition, when we actually know that E. Musk did not do any of these things    .
So, here we are again with yet another model (not even original), with no-to-few epistemological evidence to give credence to the proposition. But, hey, at least now you can say that you’re “pretotyping”, as a cool way to say you actually do market research.