What Is Quantitative Intuition™ and How Do We Use It? 

by Christopher Frank, Paul Magnone and Oded Netzer

Quantitative intuition™ (QI)—the combination of data and analytics with Intuition—might sound like an oxymoron at first, but it is actually the key to effective decision-making. Simply put, QI is the ability to make decisions with incomplete information via precision questioning, contextual analysis, and synthesis to see the situation as a whole.

So, what is Intuition? In the context of decision-making, Intuition is human judgment developed through experience and observation. Intuition can be further defined with reference to three distinct features: it is a subconscious process, it involves parallel thinking and it involves your “gut” as well as your brain.

In Nobel laureate Daniel Kahneman’s seminal book Thinking, Fast and Slow, the Israeli American psychologist and economist introduces the concepts of System 1 and System 2 thinking to describe the different ways the brain forms thoughts.

System 1 is rapid, automatic, and unconscious; it kicks in when we pull our hand away from a hot stove or step out of the street as we see a car racing toward us. System 1 is probably at work right now if you’re a competent reader. You are making connections and associations without even realizing it.

System 2 is much slower, rational, and effortful. We rely on this system when we have to recall a series of numbers from memory or read a particularly technical passage of text. What’s 45 multiplied by 97? Your system 2 just got to work.

As a subconscious process, Intuition falls squarely into the domain of System 1 thinking. It tells us the answer to something before we even know we know the answer. It gets us to the top of the stairs, both literal and metaphorical, before we even become aware of moving our legs.

The second characteristic of Intuition is that it is parallel rather than sequential. When we employ Intuition, we see a problem holistically and simultaneously, considering all its features and components. Synapses fire furiously so we can appreciate the whole picture swiftly, much like a talented chess player looking multiple moves ahead to map out the future consequences. In the context of decision-making, analysts are trained to think systematically and sequentially about the steps of data analysis. On the other hand, decision-makers are often required to, and benefit from, consuming and synthesizing different pieces of information in parallel to arrive at a decision.

Finally, Intuition involves your “gut” as well as your brain. Of course, that’s not physiologically accurate — our stomachs can’t think — but when we say, “use your gut,” we are talking about human judgment that feels visceral and instinctive.

Being able to combine qualitative thinking and Intuition means possessing the ability to make confident decisions with incomplete information while counterbalancing our fear of failure. It means transforming different pieces of information into a decision by adopting a parallel view of all issues that matter rather than just considering each piece of information separately and sequentially. Furthermore, it means enhancing our business acumen with the ability to spot patterns while also challenging how much value we are willing to attribute to those patterns and the data.

There are five steps of decision-making we encourage executives to consider:

  1. Defining the problem
  2. Data discovery
  3. Data analysis
  4. Insights or delivery
  5. Implementation

While each step involves both quantitative and intuitive elements, you can think of steps 1, 4 and 5 as the more intuitive steps (I in QI) involving leadership and management skills. Steps 2 and 3 can be thought of as the more quantitative steps (Q in QI) requiring mostly analytic skills. Across hundreds of business executives we surveyed, it became very clear that leaders find a much bigger gap in the intuition steps than in the quantitative steps. While some leaders pointed out that their organizations suffered from a lack of reliable data, the most common gaps were identifying the problems and converting the analysis to insights and actions. There is an abundance of companies selling us data and the newest three-letter acronym analytic tools but we get very little help defining the problem, generating insights, and converting these insights to actions.  

Excerpted with permission from the publisher, Wiley, from Decisions Over Decimals by Christopher Frank, Paul Magnone, Oded Netzer. Copyright © 2023 by John Wiley & Sons, Inc. All rights reserved. This book is available wherever books and eBooks are sold.

This book will help readers to develop both sides of the coin and integrate Quantitative Intuition into their team’s ways of working. It will serve as an aid when faced with small decisions that must be made briskly, but also when faced with weighty decisions with the potential to have a major impact on business, lives, and livelihoods. 

Christopher Frank is vice president of global marketplace insights at American Express, where he leads the communications and brand research and analytics group. He is an adjunct professor at Columbia University. His ability to connect insight to strategy in a coherent and actionable way has won him global recognition as a leader in his field, as well as a plethora of industry awards.

Paul Magnone is head of global strategic alliances at Google, where he is developing a growing ecosystem of partners that will unlock the next generation of business value via the cloud and related technologies. Previously at Deloitte and IBM, he is a systems thinker and business builder focused on understanding where technology is headed and answering what it means for a business. He is an adjunct faculty member at Columbia University.

Oded Netzer is the vice dean of research and the Arthur J. Samberg Professor of Business at Columbia Business School, an affiliate of the Columbia Data Science Institute, and an Amazon Scholar. He is a world-renowned expert in data-driven decision-making and extracting meaningful insights from data. His award-winning research is broadly read and high-cited. He holds a PhD in Business and MSc in Statistics from Stanford University.

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