Lessons from the Human Brain in Decision Making

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Managing Partner & Founder, Knowledge Partners International LLP
Barbara von Halle is founder and a managing partner of Knowledge Partners, International LLC (KPI). She, together with Larry, is the co-developer of the Decision Model, and co-author of The Decision Model: A Business Logic Framework Linking Business and Technology. Barb is well known for pioneering in Business Rules through writings and consulting work, as early as the 1980s. In 1996, she was inducted into the Data Management Hall of Fame when she received the honored Outstanding Individual Achievement Award from the International Data Management Association.

I am not a poker player.  This is probably wise since my grandfather lost the family farm one night in a poker game.  Sadly, as the story goes, he never won it back.  This caused me to wonder how he made the decision to bet the farm on a game.  Which decision-making mechanisms were at play?  Which were flawed? In addition, more likely, which had shut down for the evening?

Interestingly enough, there is a recent book called How We Decide by Jonah Lehrer.  It studies decision-making in humans, such as that of a championship poker player and so much more.  Packed with true stories, events and science, the book delights the reader with the anatomy and neurochemistry behind how humans make decisions.  Examples include how consumers select cereals, how military experts make wartime decisions, how pilots make decisions that avert unforeseen disasters and more.

Therefore, this month’s column takes a different, hopefully interesting, maybe entertaining, turn.  It explores the biological basis of human decision-making based on Lehrer’s book.  However, it also suggests that lessons from the human brain can sharpen our decision models and enhance the process by which we create and manage them.

What parts of the brain are responsible for human decision-making?

Lehrer explains that there are two parts of the human brain involved in decision-making.  The obvious part is the rational brain.  This is the part we can control and is the source of rational thought.  “Plato associated rationality with logic, which he believed made humans think like gods.”  This bodes well for The Decision Model.

The other part of the brain involved in decision-making is the emotional brain.  Surprisingly, this is the part by which we learn lessons from our past, create expertise and gain wisdom.  More later.

What are the flaws in our decision-making capabilities?

It is no surprise that, as far as decision-making is concerned, our brain has flaws.  Lehrer explains that these are merely characteristics that are obsolete at this point in our evolution.  Regrettably, he points out that these flaws can be dangerous – leading us to make poor decisions.  Therefore, it behooves us to understand them.  In fact, marketers and advertisers understand and use some of them so that we are apt to buy things we do not really need or want.

Apparently, one flaw is that our brain very much hates us to lose anything, be it money or lives.  For that reason, we have a propensity for loss aversion, which leads us to favor conclusions that avoid a loss over conclusions that lead to a loss but may be better in other ways.  Our brain’s flaw of choking is the act of thinking too much which leads us to poor conclusions.  A bias for certainty is the flaw by which we are likely to ignore information we do not want to think about.  Negativity bias is the flaw by which we experience bad feelings stronger than we do good ones.  His example of the latter is that, in a marriage, one critical comment needs five positive ones to compensate for the bad feeling. To better understand our flaws (and strengths); let us explore each part of our decision-making brain.

What role does our emotional brain play in our decision-making?

The emotional brain is driven by our dopamine system.  Dopamine is responsible for our emotions and is the fuel of our hidden decision-making. While it may seem that our emotions are somewhat instinctual, hence fixed, they are quite the contrary.  In fact, they reflect the emotional brain’s view of how the world is working at a particular point in time.

Dopamine is our reward system and dopamine neurons run on experience and expectation.  If dopamine neurons predict a reward (based on past experience) and the reward happens, we feel pleasure and the neurons retain the connection.  But, if the predicted reward does not happen, the dopamine neurons record the error for future reference.

Decisions from the emotional brain happen quickly, with little information, and feel like instinct or intuition.  Because a conclusion from the emotional brain is not rooted in logic, we are unable to justify it.  Instead, we feel that it is right, no reasons why.

Table 1 summarizes the strengths and weaknesses of the emotional brain. Table 1: Strengths and Weaknesses of Our Emotional Brain

Strengths Weaknesses
Knows more than we think we know
Creates our wisdom
Excels at complex decisions (too many factors)
Erroneously perceives patterns in randomness
Feels loses more than gains
Over-values immediate gains
Is useless with numbers


The emotional brain knows more than we think we do. It is always busy deciding how the world is working based on what we are experiencing and then rewiring itself.  As Lehrer states, “Even when we think we know nothing, our brains know something.  That’s what our feelings are trying to tell us.”

Science confirms that the emotional brain is how we become experts. An expert is someone “having, involving, or displaying special skill or knowledge derived from training or experience”.  Human expertise results, not from executing logic, but from our emotions.  Because experts make decisions without the overhead of logic, experts appear to operate effortlessly, on autopilot, no explanations necessary.

The emotional brain is best for decisions for which the quantity of conditions is overwhelming and there is too much information for us to process with logic.  “Complex problems….require the processing powers of the emotional brain, the supercomputer of the mind.”


Unfortunately, the emotional brain prefers to find patterns (dare we say, logic) where there is only randomness.  It also likes to feel good and so it seeks to maximize rewards, especially unpredictable ones.  Combining its susceptibility for invisible patterns and maximizing rewards, it can become quite excited when a slot machine, for no explainable reason, results in a win.

The emotional brain feels worse from losses than it feels good from gains.  Lehrer gives an intriguing example.  Credit cards alter the chemistry of our buying decisions!  When we pay cash, we feel the immediate loss of money, a bad feeling.  However, when we use credit cards, we feel the immediate gain of the purchased item without immediate loss (the loss is delayed).  Each of these buying experiences activates a different part of the brain.

The emotional brain over-values immediate gains. While all gains feel good, immediate gains feel even better.  Lehrer’s examples are fascinating.  One is the temptation of subprime mortgages.  The immediate gain that feels good is the buying of a house with a low fixed interest rate for the immediate future.  The related loss – the higher variable interest rate – occurs in the more distant future.  Therefore, the emotional brain is delighted with subprime mortgages.  In fact, Lehrer points out that even people who qualified for better financial terms of conventional mortgages fell prey to the brain’s delight with immediate gain.

The emotional brain is useless with calculations and probabilities.  Therefore, for example, it does not do well when considering odds in a poker hand.

What role does our rational brain play in our decision-making?

The rational brain lies in the prefrontal cortex and is larger in humans than in any other primate.  It is the home of our reasoning and problem-solving abilities.  We explain a conclusion that comes from this part of the brain by disclosing the conditions leading to it. The Decision Model is a technique that mimics the rational brain in a simple way.  In fact, the messages we associate with a Rule Family row explains the row’s conclusion based on the related conditions.

Table 2 summarizes the strengths and weaknesses of our rational brain. Table 2: Strengths and Weaknesses of the Rational Brain

Strengths Weaknesses
Handles panic and uncertain situations well
Serves as the foundation of our creativity
Is limited in its information processing


The rational brain handles panic and uncertain situations well.  When we panic, our emotional brain panics with us, narrowing its focus to the most basic information.  On the other hand, the rational brain can come to the rescue by going beyond the narrow focus, purposely extending our analysis.  In this way, it opens the door to other possible solutions.  However, it may not do this automatically.  We may need to force the rational brain to take over.

The rational brain is the foundation of our creativity.  It enjoys analyzing a problem from different angles, rethinking old problems, and applying abstract principles to new situations.  Rethinking logic and testing out conditions work well.


Unfortunately, the rational brain has a limit to its information processing.  There have been various experiments to determine how many things a human can remember at one time – is it four? Is it seven?  There is a similar limit to criteria we can process when making a decision.  Whatever the limit, it is a disappointingly small quantity.  While many people believe we make better decisions when we have more information, the science behind Lehrer’s book proves otherwise.   Our rational brain has “a spectacular inability to dismiss irrelevant information.”  This means, large quantities of information increase decision-making time and result in poor conclusions.

How do we function with two very different decision-making capabilities?

Like it or not, we all have these brain flaws, at least at this point in our evolution.  However, we also possess the ability to minimize their harmful impact on our decision-making by exerting balance over both brain parts.  We are able to analyze our own decision-making capabilities.  We can distinguish between decisions better handled with rational thinking versus those better handled with emotional learning.

What can we learn from this for our decision models?

The Decision Model, as a representation of logic, is a very primitive rational technique.  This is good news.  It means that decision models are very useful for decisions that benefit most from our rational brain. Specifically, these are decisions with any of the following characteristics:

Characteristic #1: Decisions expressed as conditions leading to conclusions. By definition, The Decision Model is an intellectual template whose sole purpose is to represent atomic elements of conditions leading to conclusions.  We describe The Decision Model as follows.  “Capturing business logic, from conditions to conclusions, and refining it until it is atomic, precise, unambiguous, and aligned with business objectives is what the Decision Model and its principles are all about.”

Characteristic #2: Decisions rich in computations

.  Practice proves that decision models are excellent for representing computations and calculations.  A Rule Family can determine which formula (in the conclusion cell) to use in particular circumstances (in the condition cells).  Formulas can also appear inside condition cells as needed.

Characteristic #3: Decisions requiring creative thinking or rethinking.  The Decision Model is extremely useful in brainstorming decisions which are new to the organization and worthy of careful consideration.  By iterating through skeletal decision models (i.e., before knowing any of the new logic), business leaders become creative thinkers.  Focusing on the conclusion first and considering business implications proves useful in stimulating business innovation.  We have described the use of skeletal decision models for business-driven brainstorming in a past BDM Bulletin column (October, 2009).

Characteristic #4: Decisions that benefit from testing various sets of logic before deploying.

When the full life cycle of business decisions is supported (i.e., from specification to automated deployment), The Decision Model decreases the change cycle time.  In some cases, organizations validate decision models against Decision Model principles prior to validation by SMEs and then easily test them prior to deployment.  Further, the rigor of The Decision Model makes possible the generation of test cases resulting in fewer test cases than any other approach, often reducing testing time and cost by 50%.

Characteristic #5: Decisions for the future.

By imagining potential future events, threats, opportunities, organizations can create and test decision models in advance.  This reduces future risk by being prepared for anticipated situations. The business is ready to react with high quality decisions.  An organization that models these kinds of decisions is operating at a high level of maturity.

Characteristic #6: Decisions occurring in panic situations.  These are unforeseen disasters when a business needs to make immediate decisions based on unknowables (i.e., unknown fact types or unknown condition values).  However, logic plays an important role in times of chaos.  “The Decision Model emerges as the primary business construct from which business leaders carve out islands of order from chaos and develop Decision Models for them.”

What can we learn from this for our decision modeling process?

Because our decision models are rational logic-based mechanisms, they represent only one part (and a simple version) of our human decision-making brain.  However, we can create a decision modeling process that leverages the advantages of our emotional brain (i.e., human wisdom and how we learn) and while compensating for our brain’s disadvantages.

Recommendations are:

  1. For wisdom: Include experienced business experts in decision model validation sessions.
  2. For learning: Incorporate Business Intelligence (i.e., BI) and analytics into the decision architecture, so that results from past decision executions lead to improvements in logic.
  3. For expertise: Create, test, and store multiple versions of decision models for past, present and future situations, simulating autopilot reactions.
  4. For neutralizing our bias for uncertainty: Invite and reward people who will debate and cast doubts about the logic in a decision model.

Above all, remain focused on the business itself. Associate every decision model with related business objectives.  Measure each decision model against actual business performance to see if it is doing its job.  In this way, you will uncover decision models with flaws, by which their logic misses the mark.  As you make changes, each version of a decision model should become smarter (dare we say, wiser?) than the one before it.


It turns out that poker is an interesting case study for human decision-making.  Part of the game is based on probability and statistics.  This is the part best played by the rational, logical, computational brain.  Then there is the other part of the game, based on the art of bluffing and recognizing bluffing.  It seems that this is the part best played by the emotional brain and its wisdom based on experience.

I am sure my grandfather would have much to say on the topic – not to mention what my grandmother would say!  However, Lehrer has the last word about poker, “The only way to win is to make better decisions than everyone else at the table.” This is also true of business today, when decision management is an emerging survival and competitive competency.

One more quote from Lehrer that predicts a bright future for decision management.  “The most astonishing thing about the human brain: it can always improve itself.  Tomorrow we can make better decisions.”

Therefore, too, we can always improve our decision models so that tomorrow the business itself will become smarter, one decision model at a time.

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