Data- vs. intuition-driven Decisions

Business decisions

People in businesses make many decisions, ranging from high-profile decisions that define the future, to ones that define the culture, to many ad-hoc decisions that collectively contribute to how the company performs usually guided by the values it stands for.

Decision Types

McKinsey categorizes decisions based on risk, familiarity, and decision-making frequency.

Company-defining big-bets

Leadership teams make most of the high-risk big-bet decisions. These decisions are rare, have a high stake, and broad scope. Each decision is relatively new and therefore, leadership teams research, gather data and facts, debate, reach a consensus, and strategize before making such high profile and high impact decisions.

E.g. We are betting the company on Generative Adversarial Networks and therefore we must acquire GANSoft.

Connected Collaborative Decisions

Some decisions span and affect multiple departments and business units. These are frequent in occurrence, i.e. decision-makers have seen a variance of them, and have a broad scope. They are usually made up of a series of collaborative decisions, each of which is familiar to the people with the insights, knowledge, and understanding. Since these are familiar and frequent in occurrence, companies have created processes and use tools to structure or automate them.

E.g. We are rolling out physical tap-to-pay credit card to complement our mobile-wallet based credit card.

Quick Ad-hoc Decisions

Individual team members make most of the infrequent, low stake, and ad-hoc decisions. The team members mostly rely on instincts, experience, tacit knowledge, and intuition to make such decisions. These decisions have a narrow scope and decision-makers have no or little familiarity with them. The company culture heavily influences how individuals make such decisions.

E.g. Handover support calls related to screen flicker to a triaging group so they can understand the root cause.

Structured Assigned Decisions

Frequent and low-risk decisions are expertly handled by an individual or working team, with access to insights and with limited input from others. The decision-making thrives when the individual or working team making the decision, have familiarity with the environment, have explicit and clear delegation of authority, and are empowered with insights and support to make such decisions.

E.g. Start a promotion in Shanghai for iPhone XR models


In addition to decision categories outlined by McKinsey, entrepreneurs and experienced leaders also make decisions based on tacit knowledge, intuition, insights, and instincts. Where to invest for the future? What will people need in 10+ years? What technology to bet the company on? A moonshots are ambitious projects without any expectation of near-term profitability.

E.g. Inhabiting Mars, autonomous air taxis, artificial super intelligence, non-invasive brain machine interface.

Data- vs. Intuition-driven decisions

Keith Rabois in Stanford lecture, ponders about what decisions to make on your own and what to delegate.

“A more nuanced answer that I came up with, is how to make decisions. Delegating vs doing it yourself. You don’t want to do it yourself too often. So I basically borrowed from Peter, this is my first two by two matrix ever in my life, but he taught me something at least. You basically sort your own level of conviction about a decision on a grate, extremely high or extremely low.

There’s times when you know something is a mistake and there’s times when you wouldn’t really do it that way but you have no idea whether it’s the right or wrong answer. And then there is a consequence dimension. There are things that if you make the wrong decision are very catastrophic to your company and you will fail. There are things that are pretty low impact. At the end of the day they aren’t really going to make a big difference, at least initially.

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So what I basically believe is where there is low consequence and you have very low confidence in your own opinion, you should absolutely delegate. And delegate completely, let people make mistakes and learn.

On the other side, obviously where the consequences are dramatic and you have extremely high conviction that you are right, you actually can’t let your junior colleague make a mistake. You’re ultimately responsible for that mistake and it’s really important. You just can’t allow that to happen. Now the best way to do that is to actually explain your thinking why. It’s easy to shortcut when you get busy explaining ways in the world but it’s very important to try.”  Source

Leadership teams make the bulk of big bet decisions and delegate other types to empowered groups and individuals, who rely on insights, intuition, and instincts to make decisions.


Data-driven decisions

Leadership teams and team members readily use all available data, insights, and dashboards when making high-risk and unfamiliar decisions.

Intuition-driven decisions

Business team members, make a large volume of low-risk, ad-hoc low-stakes, and parts of collaborative decisions based on instincts and intuition, and rarely consult dashboards when doing so.

leadership vs delegated

Working teams and individuals make better and informed decisions if they have access to, and understanding of insights. Sharing knowledge helps improve intuition and instincts of decision makers.

Reference vs Knowledge

How and what you share is important. Sharing too much causes analysis paralysis and disengagement, causing the teams to become immune to insights similar to how we ignore ads on a web page.

Ideally, you want to:

  • build reference for decisions makers to refer to, e.g., dashboards
  • impart knowledge via videos or wiki, so decision makers build tacit knowledge, intuition, and instincts.
  • keep the knowledge up-to-date and fresh using blogs, podcasts, videocasts, and storycasts.