For every complex problem there is an answer that is clear, simple, and wrong.

— H. L. Mencken

How do we go from indecision to decision? How are decisions actually made? What happens in the split second when a decision is reached? And what triggers the decision‐maker to finalize the actual decision?

Most decisions hinge on a combination of information and instinct. The synergy between those two forms of knowledge is at the heart of Quantitative Intuition (QI)™. QI strengthens our gut feeling—like Paul's skepticism about the Silicon Valley startup—and helps us understand whether we have enough information to make a decision.

Chapters 1–6 provide you with the QI tools you need to probe any problem or any presentation of data: powerful questioning, IWIKs™, working backward, interrogating the data, using guesstimation to develop numbers intuition, and synthesizing the insight into a recommendation. Now we're ready to examine the decision moment itself.

In this chapter, we focus on the decision moment. We deconstruct the main forces that shape and influence that moment: time, risk, trust, and the momentum of the decision‐making process itself. We expand on each of these dimensions to sharpen your awareness of these forces and enable you to understand the pressures, the process, and the necessary line of investigation, if more information is needed.

The decision moment itself should be founded in QI—not on the pressures of time, fatigue, or sheer momentum that we often succumb to in business.

Dimensions of the Decision Moment

If we deconstruct the decision‐making journey, we have a process that resembles Figure 7.1. We begin with problem definition or a problem statement, which typically flows into further consideration, discovery of data connecting to a period of discussion and synthesis, which then leads to a decision. Of course, the direction of the process is not one‐way: The period of definition and discussion and synthesis often involves an iterative cycle of data and discovery. During this discovery loop, the problem could be redefined, given new insights from the discussion and IWIKs, as is seen in Chapters 1–6.

Inevitably, the discussion fades or ends when time is up, and a stakeholder requests a decision. That moment often occurs when a deadline arises, if the discussion has become a debate that has dragged on longer than warranted, or when no more requests for data and analysis have been made and the decision‐makers feel sufficiently informed to reach a decision. In any case, the decision moment occurs when the person or team making the decision has, consciously or subconsciously, weighed three dimensions: time, risk, and trust. Let's look at each of these forces more closely.

The First Two Dimensions: Time and Risk

Let's start with time and risk. If we consider these two dimensions as axes, X and Y, the four quadrants that emerge are indicative of four quintessential operating modes (see Figure 7.2). These quadrants provide a framework for understanding the nature and pitfalls of these four modes. Later on, we will layer in IWIKs and use the Decision Moment Model mapping to organize areas of investigation and segments to ignore.

Time, the X axis in the figure, is a straightforward variable. It is often defined by the stakeholder. Do we have a tight time frame allocated, forcing us to a swift decision, or do we have an extended period of time? Is the time period fixed or can we shift it or extend further if need be? A shorter time frame can put constraints on data and discovery; it might limit the range of IWIKs we can get answers to or data we can reasonably request. It could also put constraints on the discussion: Is there enough time for a committee to meet? Can we debate all the particulars that merit attention, and syntheses that are consistent with the data pattern? A longer time frame may seem advantageous, but it can be expensive in terms of opportunity costs or the cost of your team's time and resources.

Risk, the Y axis in the figure, can be evaluated in two ways: situational risk relating to the defined problem being solved or the decision to be made, but also risk to the business or individual, which can have a broader impact on factors like reputation or brand.

Let's step through each quadrant and explore the different kinds of challenges each poses for the decision moment. In each quadrant, we also provide ways that QI can help you overcome the challenges.

The lower left quadrant is where decisions that have to be made quickly but don't come with much risk fall. These are likely to be System 1 thinking decisions (see the Prologue). The danger here is underestimating the risk just because the impact seems trivial and the time is short. Deciding quickly between a soup or salad for lunch doesn't entail much risk: getting it wrong certainly won't spell disaster. But when a colleague or your team leader asks to borrow your resources for a brief period, you might consider the decision to be simple, then discover that it's actually not. That brief period could easily become an undefined period at your expense and impact the projects that matter to you. Decisions in this quadrant can seem relatively straightforward, but they could also be costly.

The lower right quadrant of low risk with significant, flexible, or unbounded time leads to the enemy of decision‐making, analysis paralysis, failure to reach a decision by succumbing to a repetitive loop of over analyzing the virtues and pitfalls of an alternative, and thus never making a choice. Not only is analysis paralysis frustrating, but it can also prove to be costly with every day that passes if opportunities are missed.

Economists refer to this as the opportunity cost: the damage resulting from the loss of potential gains that would be captured from alternatives. The counter to this mindset is the Silicon Valley investor mantra of bias for action. Employing the backward approach to decision‐making (see Chapter 3), starting with the impending decision, and recognizing its low risk and unbounded time frame, may help you identify the unfavorable risk and time trade‐off, preventing you from overinvesting in the analysis paralysis path.

The upper right quadrant, with high risk and significant, flexible, or unbounded time is the domain of committee decision‐making. In committee situations—across business, government, and even in families—we often see that the number of opinions is exponentially growing with the number of stakeholders involved. Why? Because we are ultimately all lobbyists, and a stakeholder who enters a group with solid conviction in one direction can be swayed to suddenly question their original conviction and start weighing multiple alternatives. The permutations are fantastic. Like a geometrical explosion inside an Escher drawing, the committee discussion descends into an abyss and risks continuing in a useless, tragic loop.

Because of the complexity and time involved in making decisions that are allocated to the upper right quadrant, you should consider carefully which decisions truly belong to this costly quadrant. Ask yourself, can we break down the decision into smaller decisions that do not require as much time and/or have lower risk in and of themselves? This is where QI comes into play. The tools we develop in Chapters 1–3—precision questioning, IWIKs, and working backward—can all help break down a large decision or problem into smaller ones.

The upper left quadrant, with high risk and little time, is the realm of crisis management. Crisis experts assess the risk and business impact of an event or new issue through a series of steps: consider contingencies, build an action plan, and then consistently communicate to all parties with an active open feedback loop. This sequence usually works crisply in the military, in an emergency room or a control tower, or with firefighters and first responders. But how exactly do crisis experts decide what plan to build and what action to take? And how do they identify something as a crisis in the first place?

The professionals who step through crises efficiently and with confidence have a playbook born from years of practical experience and the latest best thinking from leaders in their field. Everyone knows their role on the battlefield, in the emergency room, or as a first responder. And they train. Each individual works to develop sharp skills, and then the unit—often a cross‐functional team in which each member knows their role—practices planned scenarios and quick alternatives to mitigate sudden surprises. This mode of decision‐making that involves building on experience and acumen to synthesize the incoming information in a short time period for detrimental decisions is probably the strongest demonstration of the use of QI skills. Extreme coordination of this sort is epitomized on a football field when a quarterback comes to the line and an audible (an alternative play) is called moments before the play starts. Millions of fans are watching, but only the quarterback and those with a trained eye can see the reason for the audible. The other members of the offensive unit don't stop and debate what each of them need to do for the alternate play; they are trained as a highly functioning unit working together.

One reason why we tend to make misguided decisions and yield to bias, is that we're not considering all the variables that are relevant, which in turn causes us to ignore factors that are important. We lack a frame for our decision‐making so we can quickly consider the underlying factors that are likely to be of importance. Such highly trained, coordinated teamwork should be the goal of general decision‐making in business, government, and other loosely affiliated large groups.

We've focused on the dimensions of time and risk in the decision moment, but to understand how teams work efficiently, even in extreme crises, we turn to a third dimension: trust. Trust is a crucial factor for the QI decision‐maker—a dimension that calls on our intuition.

The Third Dimension: Trust

While risk and time are often known, or can be determined, decision‐makers usually introduce a third (Z axis) dimension that gauges trust (see Figure 7.3). At a basic level, how much do they trust the information? Answering this question involves two forms of trust: one focused on the data itself and the other focused on the individual or organization bringing that information forward. For example, does the data come from a trustworthy source? Does the messenger have a track record of insightful synthesis of data or are they simply passing on raw data? Confidence in the individuals and the data could be gauged by a formal assessment of the data through the set of questions we propose in Chapter 4, or more intuitively, by a subconscious judgment on the quality and accuracy of the data presented.

The triangulation of trust with time and risk is most clearly seen in crisis situations. A crisis can be defined as “a time of intense difficulty when an important decision must be made.” Emergency room personnel, first responders, and soldiers on a battlefield have an acute awareness of the risks at hand and the time available, but they also weigh each decision against a measure of trust. Intuition is gained by the data synthesizer from the experience of similar situations as well as training and learning how various scenarios play out. When progressing through a crisis, these experiences are the basis for judgment that the synthesizer factors into the data to form a new synthesis and then take immediate action. Can we learn from those who operate at a highly advanced level in times of crisis and bring that decision‐making disciple to noncrisis situations?

As we've demonstrated in Chapters 4 and 5, intuition can be developed, and the tools that are presented in those chapters can help make up for a lack of business acuman and experience. But, in the decision moment, how do we weigh the three dimensions? What metrics can we come up with to improve our consistency and, efficient functioning—as individuals and as teams?

Measuring Time, Risk, and Trust

Against all three dimensions of time, risk, and trust, it may be tempting to put empirical values on a firm rating scale. But we advise you not to do that. Some norms and guardrails are possible and worthwhile, but decision‐making is not rigid. The art of decision‐making is fluid and involves balancing all three dimensions by using both quantitative skills and intuition aligned with your business goals.

Decision Reversibility

Closely related to the dimension of risk is reversibility, which needs to be considered as decision‐makers begin to settle on a preferred choice, can the decision be reversed? Would it be acceptable and even possible to go back to the original baseline condition? How much would that cost and what would the other implications of doing so be?

In our work, we see individuals and organizations stall daily out of fear of irreversible decisions. They often even fail to consider whether the decisions they stall are reversible or not. But even reversible decisions cause paralysis, for example, over the impact that a reversal could have on reputations or bottom lines.

Amazon refers to the assessment of decision reversibility as the One‐way versus Two‐way Door decisions. With One‐Way Doors, the decision is not easily reversed, has irrevocable consequences, and requires deep consideration. Two‐Way Doors have limited consequences and can evolve or be more easily reversed over time.

For Two‐way Doors, ask what is the worst‐case scenario? Is that an acceptable risk? How would the decision be reversed if necessary?

Amazon suggests the “Keys to decision‐making at speed”:²

• Recognize Two‐way Doors: While some decisions are One‐way Doors, others are Two‐way Doors, meaning they are reversible, and you can correct mistakes quickly.
• Don't wait for all the data: If you wait until you know everything, you are probably being too slow. Most decisions only need about 70% of the information you wish you had.
• Disagree and commit: People can disagree, but once a decision is made, everyone must commit to it. This saves time versus trying to convince each other.

Counterintuitively, walking through either a One or Two‐way Door is not based on just economics, but on reputation and trust. It may, in fact, be easier to spend significantly on a Two‐way Door and refuse a seemingly less expensive One‐way Door request.

Sir Richard Branson has shared that in 1984 he was only able to convince his business partners at Virgin Records to agree to the deal to launch Virgin Airlines after he got Boeing to agree to take back Virgin's one 747 jet after a year if the business wasn't operating as planned. While expensive, this was a classic example of a reversible Two‐way Door decision.

Angst over reversibility drives a lot of useless spinning, especially in large group discussions and decision‐making. It can lead to partial action. Decision‐makers often want the comfort of feeling that no options are ever really eliminated. This misplaced desire forestalls decisions or belabors the decision process in a waste of time and resources.

Aversion of making an irreversible decision can also inspire the roulette approach of spreading your bets around the table, pursuing multiple alternatives simultaneously. This can feel great and even energizing or empowering at first, especially since everyone gets to continue participating. But don't do it. Launching a fleet of sailboats while feeling entrepreneurial drains an organization's resources and prolongs the actual decision. Instead, consider launching a decision full sail, and correct your course if necessary.

Navigating Ambiguity

Now that we've explored the dimensions of time, risk, trust, and reversibility, let's move to our final considerations of the decision moment: ambiguity and uncertainty. Like irreversibility, these two conditions seem to cause nearly universal discomfort. In fact, a fundamental distinction of strong decision‐makers is the tolerance for ambiguity and the ability to focus on the decision that is possible, rather than lament and lock up over the ambiguous nature of the data or uncertain conditions for the decision.

The common battle cry is “I don't have the data” or “The data is somewhere in my organization or with my suppliers but I can't get to it.” The unspoken concern is “How can I calculate anything meaningful without the right data?” From a data science perspective, there are two alternatives—find more data from adjacent domains or impute the data so as to substitute a reasonable alternative value.

These alternatives are the critical steps to begin pushing through uncertainty. There is likely relevant information reflecting market trends available for your open question or for a related category. This is often the case for new product launches. Even if you are first to market there should be information available about the market characteristics. We can lean on Fermi's method that is discussed in Chapter 5 and some guesstimation to fill in the blanks. Next there is knowable information that can be determined even if it is not known today. To solve for that unknown, you must first identify what you really want to know to close the uncertainty gap. You can turn to IWIKs to directionally orient the discovery effort for what is missing. We can also employ the backward approach to create a set of dummy tables that would help you align on the necessary and only the necessary data to make the decision. With just these few steps you can started to create a frame around the uncertainty not all of which needs to be filled in. The leader will urge the group to fill in just enough to expose a reasonable next step and then repeat the process. Use IWIKs and the backward approach to fill in some of the uncertainty. As you fill the gaps, aim for vaguely right rather than irrelevant but precise information.

In this way, the decision moment triangulates across waves of data analysis filling in gaps between the decision to be made and the trust in the parties involved who are supplying the previously known or the new data. Further, the data may be emerging and materializing at high velocity, span multiple formats, and may be volatile with inconsistent availability. This is precisely where we can further rely on our QI toolkit: assess the situation and lean on IWIKs; challenge the data, individuals, and organizations to determine trust or at least enough trust within a confidence interval that matched the degree of certainty that is need for the decision at hand; and translate the synthesized views into action.

From IWIKs™ to Decisions

The journey from open‐ended possibilities to a clear decision can be accelerated by stepping through the QI process. Processing that decision is much like assembling a puzzle. This is where we combine the techniques in Chapters 1–6 and lay them against the dimensions of time, risk, and trust. This orientation must guide the decision in order to be efficient with resources and avoid preventable dead ends.

In the example of the Eyjafjallajökull volcano eruption, beginning with the essential question, the IWIKs as guided by awareness of time, risk, and trust, may have revealed that different information sources were being used. It also would have revealed that each country's Transport Association and trade ministers had different views and goals. Mapping the insights to the IWIK Knowledge Matrix would look like Figure 7.4. In addition to the dimensions of knowledge and needs in the Knowledge Matrix, you should also consider time, risk, and trust when evaluating IWIKs. You may find that some IWIKs would take months to find answers to, and hence would be deprioritized in the case of the Eyjafjallajökull volcano eruption. While realizing that uncertainty will always be there, for some IWIKs the level of trust in the data source is likely to be so low that you will not be able to get reliable answers to these IWIKs; again these IWIKs may be deprioritized. Finally, answering some IWIKs may involve risk. For example, in your quest to answer the IWIK, you may be revealing to your competitor that you are looking into this topic.

The essential question to be solved must be balanced against the decision attributes of time, risk, and trust. In physics, Boyle's Law describes the behavior of gases through the relationship between pressure, volume, and temperature. The condition and behavior of the gas is understood based on change in any of the three variables. Similarly, the conditions around a decision are affected by time, risk, and trust. If any dimension changes, it will have an effect on the other two and the decision process. Having clarity on even one or ideally two of the dimensions improves the decision process itself. Clarity on all three will allow the decision‐maker to move forward with high confidence.

Key Learnings ‐ Chapter 7

• Begin with agreement from stakeholders on the objective, timeline, and who must participate in a decision.
• Understand the elements of time, risk, and trust for both the decision to be made and for the organizational impact.
• Consider whether the decision is reversible or not, and if it is not reversible, can it become reversible.
• If dealing with high levels of ambiguity and uncertainty, document the plan to close those gaps via investigation of adjacent domains to find corollary insights.
• Focus on being vaguely right rather than precisely wrong. Get the best data you can even if it is not perfect. With or without perfect data a decision (and a good one) needs to be made.
• Involve large teams with heterogeneous expertise.