Quantitative Intuition: The Path to Great Decisions

One might think that with so much data available on nearly every conceivable issue, decision-making today would be easier than ever. But then there’s that pesky thing called information overload. The authors of Decisions Over Decimals weigh in.

You believe Quantitative Intuition (QI) can produce more effective decisions. In a nutshell, how does it work? Christopher Frank:

With the abundance of data today, there is the erroneous belief that we can achieve the perfect decision. However, perfect decisions don’t exist. We still need to use intuition and judgment in decision-making. But it’s a different type of intuition— one that combines information with human judgment, which we call Quantitative Intuition, or QI.

QI is the ability to make decisions with incomplete information via a three-pronged approach: First, ask powerful questions; second, put the data into context; and finally, synthesize (as opposed to summarizing) the information by combining the information with judgment.

Oded Netzer:

As part of the programs we teach, we’ve asked executives to identify the aspect of decision-making they think represents the biggest gap in their organizations when it comes to making smarter data-driven decisions. Across thousands of executives, we’ve found that the biggest gap is not in having more data or a better analysis tool to crunch the numbers. The gaps lie in defining the essential question, generating meaningful insights, and converting these insights into action. The problem in today’s data-rich environment is not information, but rather the judgment to use it.

What mindset adjustments are required of someone who wants to employ QI?

Paul Magnone:

Every decision represents change, and humans are not wired for change. Most of us retreat to comfort zones— some to data and others to gut instinct. Great decision-makers judiciously explore opportunities with probing curiosity. They’re open to alternatives while being focused on essential outcomes. You also must get past the belief that you need to be a math expert to make sound, fact-based decisions. People avoid using quantitative analysis because they believe they won’t have the ability to navigate the data. The data is the means and not the end. The QI decision-maker uses the combination of precision questioning, contextual analysis and synthesis to see the whole situation to move forward despite incomplete information.

Talk about the power of ‘I Wish I Knews’, or IWIKS. Frank:

Agile decision-making is grounded in how you think, not how hard you work. That starts with a deceptively simple,

yet extremely powerful, question: What do I wish I knew to make the best decision? This question generates a sequence of statements we refer to as IWIK™ (I wish I knew). The key word here is wish, because it grants permission for open exploration and not simply rehashing what is already known.

The IWIK statements your colleagues or clients provide reveal a deep understanding of their actual needs. IWIKS enable you to focus on the essential question and prioritize your teams to make effective decisions.

How can decision makers become more skilled at ‘fiercely interrogating’ the data they’re using to inform their decisions?

Netzer:

At the heart of interrogation is the skill of asking the right questions. People often consider data without taking the time to ask for context. To put data in context, you must always triangulate it by looking at it in (1) absolute terms, (2) over time, and (3) relative to what’s going on elsewhere. Data without context is dangerous; it leads to wrong conclusions and poor decisions.

The main skill needed to interrogate data is not a technical one. It involves putting the data in the context of the business and asking yourself, ‘what surprises me about this?’ By definition, surprises are a mix of intuition and information. When the information doesn’t match your intuition or the context, we get a surprise. And it’s often exactly at these points that the magic of meaningful insights occurs.

What can leaders do to help cultivate a Quantitative Intuition culture in their organizations?

Frank:

Decision-making is a team sport. Build a team composed of four roles—data scientists, data engineers, data translators and data leaders. The current gap in the workforce is less about people with deep analytical skills and more about leaders who can lead them to make better decisions with analytics and judgment.

As we hire for QI skills, we should focus on leaders’ ability to ask precise questions, put the data in context by interrogating it, and synthesize the information. These steps require asking powerful questions. Leaders should develop inquisitive teams that constantly ask questions as opposed to jumping directly into solution mode. Invest time and energy in visualization, with a focus on ‘data translators’ who sit between the data and the business context.

A longer version of this interview appeared at Forbes.com

This is an open-ended question WHAT SURPRISED YOU ABOUT _____? designed to reduce bias. The word surprise is a powerful bias killer. We all have preconceived notions. Some are conscious and others are unconscious. Without being aware of their influence, implicit biases affect how we interpret and tell a data story.

An analyst — as someone who is expected to interpret data rationally and logically — may be hesitant to share data they cannot explain. They may be tempted to label an unexplained result as an outlier and either disregard it or relegate it to an appendix. As the leader in such scenarios, you may miss a rich data point or a potential winning solution by not knowing about these outliers. When you ask, ‘What surprised you?’ you are giving your colleague permission to share what they did not expect to see.

‘What surprised you?’ creates a trusting, inviting space for an open discussion. In our experience, asking your analyst this powerful question often leads to two additional beneficial outcomes. First, it releases the analyst from the need to describe their hard work and chronologically go through all of the analysis that they have performed over the past few weeks. It cuts straight to the chase to the interesting findings. Second, by their definition, surprises are likely to be patterns that are not easily explained. Identifying these surprises may help you quickly identify problems with the analysis.

STEP 2: RESPOND, DON’T REACT. EMBRACE SILENCE

‘Active listening’ involves paying close attention to words and nonverbal actions and providing feedback to improve mutual understanding. But have you ever stopped to consider ‘passive listening’? This also involves listening closely to the speaker, but without reacting. Instead, passive listening leaves space for silence. By combining both of these modes, you can achieve what we call effective listening.

To create a learning environment built on trust, you need to listen, and listening begins with silence. Because it creates a void, silence may cause some discomfort, but it is an effective way to enhance learning. During the silence, the speaker will fill the void, often revealing more information; and hence you learn more. Silence signals that you are fully engaged; you are listening intently, considering what is being shared so you can respond in a meaningful way.

The difference between reacting and responding lies in the level of consideration. Reactions tend to be instinctual, spontaneous impulses driven by emotion without considering the result. Reactions often come without a filter, without much thought or analysis, and without taking time to consider possible implications. Even if a reaction isn’t intense or negative, it disrupts communication. For example, a listener may feel the need to share a related story. The intent is positive — to show understanding — but the unintended consequence is to redirect the speaker’s attention towards the listener. The listener has shifted the conversation and taken control of the discussion.

Contrast this with responding. A response is thoughtful, logical and informed. Responding uses your head and your heart to consider the outcomes of a reply before speaking. Responding is thoughtful; it involves taking time and using silence to process new information.

Responding is also proactive, using intuition and experience to consider what is optimal for you, for others in the meeting and for the desired outcome. You can then engage in a way that is accretive to the result you’re trying to achieve. In many situations, work or personal, responding versus reacting will yield richer results.

STEP 3: ASK A STREAM OF QUESTIONS

One of the most powerful response techniques is the ability to ask questions. Questions frame the issue, remove ambiguity, expose gaps, reduce risk, give permission to engage, enable dialogue, uncover opportunities and help to pressure-test logic. Varying the questions sustains engagement and fosters creative thinking. The goal is not to achieve a single right answer but to accumulate and expand knowledge through the questioning process. Returning to our camera lens analogy, open-ended questioning provides a wide-angle lens. It enables you to capture the broader picture and take in crucial background elements, allowing you to explore the scene with an unrestricted view rather than through a narrower analytical lens.

Of course, this wide view can also create distortion. Openended questions provide much more real estate to work with, but ultimately, we need a sharper picture to make smarter decisions. To quote the famous photojournalist Robert Capa, “If your photographs aren’t good enough, you’re not close enough.” Questions also allow you to narrow the lens, to get closer. By asking a stream of questions and using the four different types outlined earlier, you can ‘focus’ the data picture.

Your ability to focus starts with developing comfort with the four types of questions. This is the ‘question library’ that equips you with the capacity to ask a stream of questions. As you progress with the discussion, the secret to asking questions is to be precise. Your questions are still open-ended but focus on particular aspects of an outcome you are looking to achieve.

Start to transition from a broad question — How do we increase sales? — to more precise questions:

-What specific promotion has had the highest response among older Millennials?

-Did your analysis uncover any variations by gender? -Were there surprises in the sales data from a geographic view? -How would your conclusion change if you were the competitor? -As you consider the new information shared, are you clear on how it relates to the original problem or the outcome you are working towards?

In closing

Always remember: The smartest person in the room is not the one with an answer, but the person asking the best questions. One of the biggest mistakes we have observed is leaders expecting the data to provide both the question and the answer. It is your responsibility, as a decision-maker, to first define the problem. Then, if the data can provide sufficient evidence towards an answer — and if you are fortunate enough to have the right set of skills in your organization to appropriately mine the data for the answer — you may find a solution to the problem you have so carefully defined.

Christopher Frank is VP of Global Marketplace Insights at American Express and Adjunct Professor at Columbia Business School. Paul Magnone is Head of Global Strategic Alliances at Google and an adjunct faculty member at Columbia University. Oded Netzer is Vice Dean of Research and Samberg Professor of Business at Columbia Business School. They are the co-authors of Decisions Over Decimals: Striking the Balance Between Information and Intuition (John Wiley & Sons, 2023). Excerpted with permission from the publisher. Copyright © 2023 by John Wiley & Sons, Inc. All rights reserved.