202201061619 Treating a business model as a scientific model

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A business model is, in essence, an approximation to reality in pretty much the same way a scientific model is. Models are built with partial knowledge and try to predict the future, they are based on hypotheses, and have a certain degree of uncertainty.

Apparently, entrepreneurs that treat their business models with a more scientific approach show a slightly better performance at pivoting to new ideas. This means, they identify the problems with their original plan earlier. Surprisingly, there's no clear evidence that they stop their process earlier.

Having a scientific approach to validating ideas means that one should establish thresholds to define success/failure earlier (avoiding the post hoc ergo propter hoc fallacy). It also helps identify biases in sample selection (for instance, asking only friends), and help plan the proper experiments ( experiments for idea validation )

An interesting idea is that since most startups fail, there's a large number of false positive observations in the processes.


On the other hand, false-negatives would be ruled out since those companies would automatically not exist. But the authors do not comment on that

It must also be reminded that the scientific method pushes its own biases and limitations (for example: citations make science conservative ) which may permeate into the business validation process as well.

An interesting derivation from the model is the opportunity for learning that the scientific method enables. A properly conducted experiment that returns negative results, is still valuable from the perspective of pivoting into a new direction. This idea correlates with the observation that scientific entrepreneurs pivot more quickly.


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Aquiles Carattino
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