Decision Making Essentials You Always Wanted to Know

Vibrant Publishers

• Publisher: Vibrant Publishers
• Year: 2020
• ISBN:
  9781636510033
• Edition: 1
• Topic: Business
• Subtopic: Decision Making
• Index: Business

Includes

• Introduction to Decision Making

• Scenario Planning and Prediction Markets

• Group Mechanics

• Heuristics and Programmed Decisions

• Probability and Base Rate Neglect

Decision Making Essentials You Always Wanted to Know prepares new managers and leaders to make those tough decisions they face by providing them with a tool box of decision analysis techniques to help them understand and analyze the decisions they make.

The chapters describe key techniques of decision analysis, including:

• Cognitive biases and Prospect Theory

• Heuristics

• Probability and Expected Value

• Bayes Theorem

• Multi-attribute decision making, including the SMART, Elimination by Aspects, and Even Swaps methods

• Game Theory

• Prediction Markets

• Brainstorming and Groupthink

• Black Swan Events.

Each chapter provides clear examples of the decision making tools and includes practice examples to help train the reader in using these critical tools.

Cognitive Processes and Their Limitations

2.1 Introduction

Classical economics asserts we are rational decision-makers. This chapter explores why we may not be because of our biases and cognitive processing issues. Behavioral economics, including prospect theory, is also discussed.

Professional theologians coined the term hermeneutic insight. In its simplest form, this theory of textual interpretation states anyone reading a sacred scripture will interpret the whole of the document by reference to certain parts of it. The overall understanding of the document will depend on each reader’s understanding of the passages selected. This has been labeled as the “canon within the canon” problem, or the emphasizing of certain parts of the scripture and the deemphasizing or total exclusion of other parts. As one of my professors once put it, “everyone brings their own baggage to scripture.” The economics profession did not come to widely understand or appreciate this insight until the later part of the twentieth century.

We would all like to believe we make decisions in a completely rational manner. Economic theory assumes this is the case, giving rise to the image of the economic man⁵: a person who makes decisions rationally and with perfect information in order to satisfy his or her utility function. As we will see, it may not be practical, desirable or even possible to fulfill the perfect information requirement. Many decisions are made under conditions of uncertainty, a condition we will turn to in later chapters.

The fields of behavioral finance, behavioral economics and psychology have challenged the assumption of the economic man. As it turns out, decision making processes are much more complex than the simple calculus of economics supposes. Classical economics was criticized for assuming the maximization of profit was the same as maximizing utility. It also does not leave room for cognitive biases and limitations in the decision making process. This chapter explores some of the interesting cognitive processes we employ when we are making decisions, the biases we possess, and the limitations of our cognitive processes.

Before we begin though, it is also important to note these fields of study are not without their critics. The best term to describe what many minimizers of the study of the behavioral scientists believe is the entire field is relatively unstructured. Any deviation from the result predicted by classical economics can be ascribed to one or more of the phenomena described in this chapter or in other studies after the fact. The various behavioral theories described in this this chapter read like a laundry list of cognitive processing errors, but they may not accurately predict how someone comes to choose any one particular option. Critics ask for a behavioral theory that is predictive.⁶ They ask for a unified theory that can explain the entire range of phenomena. These commentators deny the behavioral disciplines provide a refutation of the classical economic model. In the field of behavioral finance, Eugene Fama (b. 1939), a Nobel Prize winning economist notes the behavioral schools are not consistent in explaining the reasons why decisions may vary from classical economics. In some studies deviations are cited as both overreactions and as underreactions to market forces.

The behavioral schools make many valid points about decision making but the extent these factors impact decisions is still controversial. While it is difficult if not impossible to eradicate all bias and cognitive processing limitations from any one individual, organizations understand this as they require major decisions to be vetted by either a committee of decision-makers or senior management. Major decisions are kicked up to the board of directors. The hope is by that point all emotion, cognitive biases and potential errors have been filtered out of the decision-analysis.

2.2 Information Processing Issues

In his book Thinking Fast and Slow, Daniel Kahneman adopts the terms System 1 and System 2 (originally coined by Keith Stanovich and Richard West) to describe the functioning of the human brain. They do not reside in any particular part of the brain but are rather a description of how the brain functions when it makes a decision. System 1 is always active and is responsible for making quick decisions and automatic responses such as routine driving skills, reacting to loud noises, reading facial cues, doing simple mathematics, etc. It is impulsive and intuitive. That is not so say System 1 is primitive, but it acts quickly and spontaneously to stimuli and comes to quick conclusions. We do not have conscious access to System 1. Other characteristics of System 1 include:

• Generating skilled intuitions;
• Making causal connections;
• Suppressing doubt;
• Substituting an easier question for a more difficult one; and
• Over weighting low probabilities.

System 2 on the other hand is the analyzer of complex data and does the heavy lifting when it comes to making weighty decisions. System 2 engages when the decision has the potential for significant risk and reward. It approves the actions of System 1 and can override System 1. System 2 is not good at multi-tasking, requires a lot of energy, and is cautious by nature. System 2 is our aware self.

System 1 is marvelously efficient, but also can jump to quick conclusions. Unfortunately, these quick, intuitive decisions can be wrong. System 1 is where bias and information processing issues arise. Bias can be defined as systematic errors occurring in predictable patterns. When making crucial decisions for an organization such as those described later in this book, we strive to get the decision making process into System 2. Organizations take this one step further by having vetting major decisions by senior management, experts in the area of the decision, and even the board of directors. Yet, System 1 does not shut off. We are still subject to its vicissitudes. System 2 may generate a correct answer for us, but we still need to understand the influence System 1 has even when System 2 made the decision. System 1 impacts our decisions through biases, or the interpretation of decisions generated by System 2.

Knowing when someone has engaged their System 2 is critical for discussing the decision with other stakeholders and getting their “buy-in. We all have encountered coworkers or managers who are laser-focused on some problem at hand and don’t seem to hear or let alone comprehend what you are saying about another topic. Their System 2 has been engaged and multi-tasking (meaning listening to you) is simply not in the cards. We seem to instinctively know that as well because more often than not we will simply become quiet and wait to finish our conversation until the person completes the first task at hand. Picking the time to engage other stakeholders in a conversation about a complex decision is critical to gaining acceptance for it. You must make sure they have engaged their System 2 and it is focused on your decision.

Besides the issues caused by Systems 1 and 2, decision-makers also have limited cognitive capacity. For instance, memory is a critical factor in decision making. We tend to remember unusual items or repeated items. The easier we remember something the easier it can be applied to a decision. We overweight decision factors we remember more easily. To compensate for this shortcoming in today’s world, we tend to remember how to access information rather than the information itself. The internet gives us quick access to untold amounts of information. We often don’t remember all of the details about a decision attribute, but we remember how to research them.

Aside from dealing with our “split personalities” of Systems 1 and 2 and cognitive limitations decision-makers may suffer from poor information processing caused by other factors. Examples are becoming fatigued or feeling pressured because of deadlines.

The following is not an exhaustive list, but are examples of common processing issues decision-makers should be aware of:

Overweighting recent evidence

Forecasting is a difficult thing to do under any circumstances, but decision-makers tend to place too much weight on recent evidence and experience. This can make the forecast either too rosy or too pessimistic since there is normally uncertainty in the data being used in the decision making process.⁷

Overconfidence

Decision-makers tend to be quite optimistic about their own ability to make decisions, to the point where they can exclude other legitimate points of view. Overconfidence can sometimes result from relying on one’s intuition too much. One acerbic commentator pointed out how often successful entrepreneurs ignore good business advise by asking, “If you are so smart why aren’t you rich?” The point being past success may spur on over-confidence. Needless to say, overconfidence in one’s own ability to make decisions can produce bad decisions as critical information can be ignored and doubts are suppressed. Ask Hilary Clinton about her overconfidence in the 2016 American Presidential election.

Overconfidence of leadership can be disastrous. History is littered with examples of bad decisions made through overconfidence. Custer at the Battle of the Little Big Horn, Hitler invading the Soviet Union, and Varus in Germany are just a few sensationally bad decisions that come to mind. Significantly, each of these military decision-makers had been extremely successful in previous endeavors. In the business world overconfidence can lead corporations to overpay in mergers (Malmendier & Tate, CEO Overconfidence and Corporate Investment, 2004) and a lower, not higher stock price.

Closely related to the over-confidence effect is decision-makers tend to believe desirable outcomes are more probable. Ask anyone who plays the lottery! We overestimate the probability of desirable outcomes, sometimes dismissing the true probability of success.

Conservatism

Sometimes decision-makers will be too slow or too conservative to change their beliefs. This could cause an under-reaction to a new challenge or environment. The way decision-makers should take into account new information is described by the use of Bayes Theorem, a topic for later discussion. Conservatism is a debated subject. Sadly, Kahneman and Tversky proved most people are not very adept Bayesian thinkers and don’t handle probability well at all. Rather than failing to extract probabilities from data, decision-makers tend to extract unwarranted certainty from data.

Emotions

Long thought to be impediments to making clear decisions, recent thinking on the subject suggests emotions are necessary for making a decision.⁸ However, moods do impact decisions in interesting ways. Happiness will generally prompt less analysis when making a decision. Sadness will cause more detailed analytical thinking. Overall positive and negative feelings could influence one’s perception of the risks and rewards associated with a decision. A feeling of “good” or “bad” may attach to a particular decision. For example, investors may feel “good” about investing in socially responsible corporations or companies interested in social justice even if this isn’t the best financial decision for that particular decision-maker.

Reason-based choice

Decision-makers will often find reasons to make a decision and then justify the decision to themselves and others. In such situations, the decision-maker is vulnerable to making the decision on irrelevant attributes. The decoy effect, described in the next section, is an example of this.

Decoy effect

Sometimes adding a third option to a set of two options changes the stated preferences for the first two options. A consumer may prefer Product A over Product B. Product C is introduced, with attributes inferior to Product B. This will give some consumers a reason to change their minds and choose Product B. In effect, introducing a new option can give us a new reason to choose the alternative not selected before.

Suppose you are considering the purchase of an office copier. The decision attributes you are using are cost and need for service. The higher cost copier has a relatively low level of service required compared to the more inexpensive model. Both copiers have built-in staplers. You then add a third model int...