Everyone is Data Driven

Everyone is data driven.

The difference is that some index more highly on external data (objective measures and validation from the external world), while others rely more on internal data (intuition and intrinsic impulses).

The former is more useful in contexts in which collective alignment is needed because the data itself can be commonly visible, understood, and shared. The latter tends to be more efficient and defensible, especially when one is empowered to fully trust and follow it.

Relying on internal data is more efficient because it enables one to shortcut decision making by going straight from impulse to action, and results in more defensible outcomes because those actions are informed by unique datasets that no one else can access. Internal data tends to be where the alpha is.

While internal data can be advantage, it needs to be developed and maintained with the right dataset. Internal data is the aggregate of all of the interconnected (and messy) data records one accumulates in a lifetime. It is the sum of one’s experiences, thoughts, observations, feelings, and more. This dataset can be intentionally curated, or left to emerge on its own.

Internal data is only reliable when trusted fully. Its conclusions are often the result of tons of invisible and unknown correlations that we do not consciously reason or understand. Internal data is encoded in one’s biology as a whole. It cannot be deconstructed into parts because we don’t know what the parts are. This is what makes it so special, but also so obscure.

Trusting our internal data is the ultimate productivity hack when used personally, but looses its efficiency advantage when used in the context of larger groups. It is harder to work with and get value from when it can’t easily be translated into shared context. This is where the use of external data becomes inevitable, but also dangerous. We can become dependent on external data to justify most things in exchange for the benefit and comfort of external validation. We override internal signals, and eventually lose touch. Those that fall into this modus operandi tend to label themselves as “data driven”, yet they are not more data-driven than any other - they are just more reliant on external data relative to one that might navigate between external and internal datasets more effectively. Paradoxically, the one who is “data-driven” may have a smaller and more commoditised dataset to work with. It is arguable whether or not that is a good thing, and depends on context.

The ideal strategy would be to merge both - to have internal data be more explicit, and external data be encoded into our intuition more easily.

I doubt that “intuition wearables” or subconscious data monitoring dashboards are coming anytime soon. I also doubt that our biology will adapt to absorb the entire world index in a near future. In the meantime, we can only imagine what that could look like, and leverage both in the process.