What makes entrepreneurs entrepreneurial
Authors: Saras Sarasvathy Source: https://www.khoslaventures.com/wp-content/uploads/What_makes_entrepreneurs_entrepreneurial.pdf #literatureonline
Highlights
Effectual reasoning is the inverse of causal reasoning.
Causal reasoning takes a chosen goal and available means and attempts to map the two to one another via some set of strategy, tactics, and plans. In this sense, causal reasoning is like trying to figure out the functional form and parameters of a model for turning known X into chosen Y (a la supervised learning).
Conversely, effectual reasoning assumes only a given set of means (X) and then allows the goals (Y) to organically emerge out of the primordial soup of means (like in unsupervised or self-supervised learning). Thus known X is mapped to unknown Y, and the mapping function and it’s parameters are jointly determined with the Y itself.
Said differently, causal reasoning is a way to figure out how to get what you want, while effectual reasoning is a way to determine what you want in the first place (along with how to get it), as articulated by Taylor Pearson in Effectual Reasoning: The Little Known Method Entrepreneurs Use to Figure Out What They Want.
The set of means available can be roughly bucketed as:
- Who you are
- What you know
- Whom you know
Effectual reasoning starts immediately with action based on the means available without significant planning or forethought. Plans are fluid (Don’t plan): emerging and withering away over time, revised as needed based on actions taken and interaction with the outside world. (Confidence grows with action and shrinks with idleness)
Effectual reasoning targets low cost-to-action rather than high ROI
Instead of trying to analyze and identify large markets with high ROI (as critiqued in It’s Impossible To Size a Market), effectual reasoning merely goes after the first plausible, addressable market opportunity in the most direct fashion, in some cases selling the product before the product is even built! The emphasis is on low, affordable costs rather than the ROI of those costs.
The low cost of effectual reasoning is similar to the low cost of unsupervised learning and self-supervised learning. No labeled data is needed; you learn purely off of the unlabeled Xs, making the learning process much cheaper. It is much cheaper to identify and take action on emergent goals than figure out the mapping to pre-existing ones.
Effectual reasoning ignores competition
Given that effectual reasoning doesn’t focus on identifying pre-existing markets, it naturally follows that it also doesn’t waste time analyzing the competitive landscape. With no defined market, there are no defined competitors. Rather than focus on competitors, effectual reasoning identifies strategic partners who can help the founder get to market with low cost-to-action.
For the effectual reasoner, residuals are inputs rather than outputs
For the effectual reasoner, action generates effects, and with enough time these effects generate achievable and desirable goals, the “stepping stones” of Why Greatness Cannot Be Planned. They also generate surprises. Importantly, these surprises are not deviations from the “correct” path but rather they are features of the landscape, and you should leverage these features to determine the path itself. They are landmarks which highlight the path, guiding you forward. They are the input to the next iteration or step of the algorithm.
The logic of effectual reasoning
In causal reasoning, the purpose of predicting the future is to control it. This is the entire point of causal inference. Presumably we want to infer causality so that the next time around we can leverage it to achieve desired aims, armed with the knowledge of the likely impact of our actions.
In effectual reasoning, the ability the control the future obviates the need to predict it in the first place. This avoidance of prediction echoes advice from Nassim Taleb. Rather than attempt to predict the future, effectual reasoning believes that action creates the future in the first place. There is not a future that exists as a concept separate from our actions, that could be discovered without any action. Peter Thiel has made a similar point on numerous occasions.
Acknowledging this agency, effectual reasoners create games they are likely to win, rather than try to predict the outcome or come up with optimal strategies for existing games. In fact, the predictability of existing games makes them poor targets, as they are likely competitive, escalating conflicts. Unpredictable games are more easily shaped. Invest in unknowns.