“When someone is seeking, it happens quite easily that he only sees the thing that he is seeking; that he is unable to find anything, unable to absorb anything, because he is only thinking of the thing he is seeking, because he has a goal, because he is obsessed with his goal.
Seeking means: to have a goal; but finding means: to be free, to be receptive, to have no goal. You, O worthy one, are perhaps indeed a seeker, for in striving towards your goal, you do not see many things that are under your nose.” - Hermann Hesse
There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas. A hypothesis then becomes a liability for any night science explorations. The corresponding limitations on our creativity, self-imposed in hypothesis-driven research, are of particular concern in the context of modern biological datasets, which are often vast and likely to contain hints at multiple distinct and potentially exciting discoveries. Night science has its own liability though, generating many spurious relationships and false hypotheses. Fortunately, these are exposed by the light of day science, emphasizing the complementarity of the two modes, where each overcomes the other’s shortcomings.
The gorilla experiment
Many of us recall the famous selective attention experiment, where subjects watch a clip of students passing a basketball to each other. If you have not seen it, we recommend watching it before continuing to read.
As you watch the two teams in action, your task is to count the number of passes made by the team in white. About halfway through, a person dressed up as a gorilla enters the foreground. The gorilla pauses in the center, pounding its chest with its fists, before exiting to the opposite side of the frame. Surprisingly, half of us completely miss the gorilla, as we are focused on counting passes, even though hardly anyone overlooks it when simply watching the clip without the assignment.
We believe that a similar process happens in various phases of life.
Growth teams
Growth teams are laser focussed on hypothesis building, executing on the hypothesis, tracking progress against goals measured using metrics assumed to be impacted by the hypothesis. Some of these experiments lead to metrics wins and some of them not so much. It is equally important to distill learnings from the wins and the failures and articulate them to build the next hypothesis. This kind of learning at the project level, aggregated produces the future direction of the team and informs the organization level strategy in growth companies. Hence, the failures even though they seem innocuous or wasted opportunity at certain points serve the valuable purpose of informing future roadmap direction and strategy for the organization. This helps form the future organization level hypothesis, goal and metric. Also in committing to a hypothesis based on these learnings, there is also a pseudo commitment about not investing on other hypothesis (in case of limited team bandwidth). Hence the process of distilling the learnings in growth teams and the quality of the learnings serve the lifeblood of the organization.
Investing
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