“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.” – Donald Rumsfeld – US Secretary of Defense – 2001-2006
What is a decision?
What was the last tough decision you made? Why was it hard? What were the stakes? Who was impacted?
Merriam-Webster online dictionary defines the word decision in a few ways:
- as the act or process of deciding
- the moment of decision has come;
- a determination arrived at after consideration.
We make decisions constantly ever day of our lives. Most of our decisions are small and only affect ourselves. However, leadership decisions directly affect others, ranging from a small few to an entire organization. Therefore, it is important for leaders to understand the art and science of decision making not only for themselves, but their colleagues and customers.
Decision making can be very challenging for leaders because of the impact. Since leadership decisions often have public implications, leaders are subjected to second guessing regularly. Psychologically the very act of making a decision is stressful because of the risk of making the wrong choice. Every decision we make means all other options were rejected in favor of one choice. This sense of finality can be scary. Sometimes people avoid making a decision altogether. However, not making a decision is a form of decision making with consequences in itself. Deferring decisions may be useful at times, but often there comes a point where making a decision is unavoidable.
Known and Unknown
When Secretary Rumsfeld initially made the comment shared at the top of this article, he became the subject of much ridicule. At first glance his statement seemed like bureaucratic nonsense with no connection to the real world. Yet over time the statement has been re-evaluated. In fact, it has become so connected with him that Secretary Rumsfeld titled his own memoir Known and Unknown.
The act of leadership requires decisions be made on a constant basis. The challenge is that leaders must often do so in the face of limited knowledge and varying degrees of uncertainty. Rumsfeld’s analysis breaks down the types of challenges facing decision makers. To illustrate these types, let’s use an example of buying a used car from a dealer.
- Known Knowns:
- Sticker price
- Published model reviews
- Odometer reading
- Manufacturer recall history
- Known Unknowns:
- Repair history,
- Dealer negotiation range,
- Previous owner’s name and address,
- Driving history
- Unknown Unknowns:
- Internal parts condition (ones that can not be seen)
- Future recalls
- Better deal elsewhere
- Driving needs change due to new job
Psychoanalytic philosopher Slavoj Žižek expanded on Rumsfeld’s observation to include a fourth factor he called, the Unknown Known. This is knowledge we intentionally refuse to acknowledge. In other words, information that we deliberately refuse to examine when making a decision which could impact the result. In the case of buying a used car, an example of an Unknown Known could be income. A buyer may be short on money, but ignores the status of their bank account to buy an expensive vehicle because of the emotional appeal.
The Search for Homo Economicus
Although it is easy to view the discipline of economics as simply about money and prices, it is at its heart the science of how decisions are made. That is, the economy is the sum total of the decisions made by the people participating in it. Any market, whether it be for houses, concert tickets, or collectable shoes, has its price largely decided by supply and demand and bounded by regulations and laws. Economics is full of models that seek to determine how people operate in markets, along with understanding the obstacles in the process. The sub-field of Behavioral Economics specifically examines how people actually make decisions.
At the core of classic economics is a fictitious being called Homo Economicus. He is the completely rational man who makes optimal decisions based on his own well-defined set of interests. For example, when Homo Economicus is shopping for a used car, in theory his preference criteria would be clearly ranked in advance such as:
- Price
- Safety
- Fuel Economy
- Repair History
He would not be confused by dealer sales, car color, stylish floor mats, or the time of day, week, or month. Homo Economicus would move dispassionately through his criteria in a quest to make the optimum decision between Car A, Car B, or Car C. However, when economists search for Homo Economicus in the real world, it is like hunting for Bigfoot. Rumored sightings abound but he is never found.
The reason why Homo Economicus is a myth is simple: humans do not think rationally without a lot of effort! Our emotions and embedded cognitive misunderstandings constantly lead us astray. We are often driven by fear, anger, love, and beauty. These emotions pass quickly, yet can strongly influence our decisions in the heat of the moment. Many people buy a car based on its color and styling. These are attributes that have little economic impact, but lots of emotional weight. One need remember how the pandemic lead to a rush on toilet paper. The fear of being without those white little squares drove people to stockpile the product even though supply lines were functioning normally. Homo Economicus we are not!
Your Brain on Fallacies
The ability for our minds to think rationally is a developed skill, which even in experts can quickly go faulty. Our brains were built in an age when life and death decisions were made on the Savannah of Africa. Unfortunately, they struggle to adapt to the complex modern world, where evolutionary cognitive short cuts lead to faulty decision making. These modes of thinking are known as fallacies. Out of the hundreds of documented fallacies there are a few major ones that seriously impact decision making.
Here are a few examples:
- Sunk Cost Factor – When people make a decision to continue on a path based on the amount of time and resources already expended rather than understanding the potential value saved by stopping. Summed up in the phrase, “Throwing good money after bad.”
- Confirmation Bias – Seeking only data that supports the decision maker’s preferred choice and rejecting all evidence to the contrary. For example, “I only get my news from Alphabet New Channel because Beta News Channel is biased against my candidate.”
- Availability Bias – Making a decision based only on the evidence that is readily available. The decision maker does not dig deeper or wider to find contradictory evidence. For example, “My five friends all liked my product idea, so it must be great!”
Probabilistic Misunderstandings
Have you ever heard someone say, “Show me the numbers,” when wrestling with a decision? Oftentimes numerical data can be a big asset for making a decision. “Numbers don’t lie,” is a common saying, but statistics are one of the easiest things to manipulate. Former U.K. Prime Minister Benjamin Disraeli famously said, “There are three kinds of lies: lies, damned lies, and statistics.” However, even when presented honestly, interpreting statistical data can lead us straight into the same set of fallacies listed above. It may also be unclear which statistic is actually useful for solving a problem. Take the COVID-19 statistics. Which ones are the most important for understanding the spread of the virus?
- Hospitalizations
- Confirmed cases
- Deaths
- Number of tests completed
- Rate of infection
- Comparisons to other states or countries
All these stats provide valuable data, but ranking their importance is challenging for fully understanding the problem.
Additionally humans are not built to comprehend probability. Our minds prefer definite answers over ones based on chance. Studies have shown we have difficulty understanding probabilistic results. Here is a simple example. Which form of transportation is more dangerous, cars or planes? Based on sheer probability a person is more likely to die in a car accident. Yet thanks to the availability bias, we ignore the probabilities and focus on the news reports of the few big plane crashes rather than the under reported but more numerous daily road accidents.
A classic puzzle that demonstrates how our minds fail to grasp probability is The Monty Hall Problem. This puzzle imagines a player on the game show Let’s Make a Deal. The contestant is asked to pick one of three doors to win a new car. After their initial pick, the host opens ones of the other doors to show a worthless “zonk” prize. The host then offers the player a chance to switch doors. The puzzle asks whether switching doors increases the player’s chance of winning, makes no difference, or reduces their chances. Most people assume it does not matter, but in reality, the probability of winning goes up when the player switches doors. It is counter-intuitive to how we regularly consider probabilities, but is proven through a simple charting of the results.
“Kind” vs “Wicked” Environments
Decision making is also challenging because a choice made one day may not be the best choice on a subsequent day. Environmental conditions surrounding the choice have a direct effect on our ability to choose. In the book Range David Epstein shares research on “Kind” versus “Wicked” environments. A “kind” learning environment is one where the rules are fixed, allowing for easy feedback and adjustment. Think of chess where the games stays the same no matter where it is played. Players can improve quickly since the parameters are fixed and the lessons of a prior game can be directly applied to future games. This is contrasted by a “wicked” learning environment where the rules are either vague or change over time. For example, imagine an entrepreneur who grows an Internet start-up. They think they can repeat the success with a new company, but even after following their prior model the company is derailed by a change in the law, or an upstart competitor, or even a shift in user tastes.
Models for Making Effective Decisions
With all these factors conspiring against leaders, is it possible to learn how to make better decisions in “wicked” environments? An approach that can help is to use a model to frame the thinking process. Models are helpful because they provide a way to study a problem along with a systematic approach to resolving it. Here are examples of six models with a pro and con for each:
Dictator Model
The leader is the only one involved in the decision-making process. They make the decision and expect everyone to follow it with little debate.
- Pro: Decisions can be made quickly in the face of rapid changes
- Con: Creates blind spots as alternative views and experiences are left unconsidered
Executive Committee Model
The leader consults with a small committee of trusted lieutenants to make a decision. Typically the group is expected to come to an agreement after discussion.
- Pro: Allows multiple viewpoints to be heard and debated
- Con: Excludes the rest of the organization and can lead to groupthink
Democratic Model
The leader polls the entire organization to seek out the preferred choice. This could be through voting, town halls, feedback forms, or face-to-face meetings. The choice with the most votes wins.
- Pro: Builds deeper consensus as everyone plays a role in the process
- Con: Very slow process, could be problematic in rapidly changing situations
Satisficing Model
The leader and the team work on a problem until they find the first “good enough” solution. They use a limited amount of the organization’s people and resources in the process.
- Pro: Pragmatic approach that prevents wasted time seeking perfection
- Con: Stopping too soon and potentially missing out on a better solution
Incremental Model
The leader breaks the problem down into smaller subsets which are solved as needed by the appropriate team. They are only concerned with finding short term solutions to issues rather than tackling the larger problem all at once.
- Pro: Keeps the organization moving forward with smaller manageable decisions
- Con: May lose sight of the bigger picture as smaller decisions lead them off track
Outsider/Consultant Model
The leader approaches the problem like an outsider. They imagine what would happen if they were a new boss who joined the organization and was unattached to prior decisions.
- Pro: Averts the sunk cost factor and allows the leader to see the problem from a different perspective
- Con: May come across as cold and out of touch if the organization’s culture is ignored
Experimental Leadership
There is an old saying loosely translated from the writings of Voltaire that “perfect is the enemy of good.”
A major trap in the decision-making process is the desire to make the “right” decision. Too often this leads to an endless search process that causes a leader to never make a decision. This is known as analysis paralysis. As described in Wikipedia:
Analysis paralysis (or paralysis by analysis) describes an individual or group process when over-analyzing or overthinking a situation can cause forward motion or decision-making to become “paralyzed”, meaning that no solution or course of action is decided upon.
The first step to avoid this problem is to acknowledge that no real-world decision can be perfect due to a lack of information. Essentially, it is an understanding that most decisions are made in “wicked” environments. To move forward, making a decision provides the only way to gain additional information. By trying a solution and seeing the results the decision maker gains valuable data which they use to adjust and make the next decision. This moves them step by step towards an optimal solution.
An expression of this form of leadership decision making is the Design Thinking Model. It is a process centered on continuous experimentation and feedback. There are five stages to design thinking.
- Empathize – Research the problem
- Define – Clearly state the problem
- Ideate – Create ideas and challenge assumptions
- Prototype – Identify possible solutions
- Test – Implement a solution and gain feedback
During the process, the designer will cycle between some or all of the five stages until they reach a point where the problem is effectively resolved. For an experimental leader, a process like Design Thinking is a good way to resolve the fear of mistakes. Not only are mistakes expected in the process they are required to gain important feedback.
Many professions use this approach including software engineers. Venkatesh Rao in his collected online essays entitled “How Software is Eating the World” notes that when creating new code software engineers try their best to make it fail. It is only through breaking the code that problems can be identified and improvements made. For example, when coding a new video game, the designer will test out unusual keyboard combinations to make it crash. If they do, the code is examined and then improved for the next test. This is important because it is better for the designer to find the bugs early rather than outsource that process to their customer after they buy the game!
Rallying Teams Around a Decision
Making a decision is only one step. Implementing the decision is crucial, especially when other people are needed to carry out the plan. Here are a few points for leaders to consider in order to get a team to support a decision.
- Participation in the Process – People support what they help to create. When team members are included in the larger decision-making process they are more likely to be invested in the outcome.
- Trust – Leaders who have developed strong bonds with their team and have shown proven success create a foundation to move people forward even in the face of uncertainty.
- Listen and Empathize – A leader that invests time listening to their team and strives to understand their concerns can build strong support. Oftentimes people simply want to know that they are heard.
- Agree to Reassess – People may support a decision when defined reflective points are included in the implementation. Promises to examine results after a set amount of time or progress can reassure a team that the end result will be good.
The Unexpected
As the past few months have demonstrated all leaders are at the whim of unexpected events. Crisis coming out of left field challenge our standard decision-making process and upset prior conclusions very quickly. In his book, The Black Swan, author Nassim Nicholas Taleb reflects on how the unexpected has more of an outsized impact on our lives than most people appreciate. He believes that “our blindness with respect to randomness, particularly large deviations” causes us to naively believe that present conditions will exist for the foreseeable future, changing only gradually. In fact, they change more rapidly than we expect and in ways we cannot foresee.
Taleb’s argument encapsules many of the topics expressed in this article, including our inability to comprehend probability, the availability and confirmation bias fallacies, and failure to appreciate that most of our decisions are made in “wicked” environments.
One approach to counter these faults is to consider in advance how decisions can go wrong and how projects may fail, such as using Gary Klein’s pre-mortem strategy. The pre-mortem is an exercise were participants consider all the ways a project might fail. The challenge is to reverse engineer solutions to the failures into the project design in anticipation of their need. Again, it is not possible to anticipate everything, but the wider the thoughts the more likely surprises can be mitigated.
Conclusion
The field of decision making is immense. The skill is not one that is mastered in a short time. Instead, leaders must commit to improve their abilities continually over the course of their careers. Leader must be willing to remain a perpetual student, always learning and never being satisfied with their current state. That is the burden and the reward of leadership.