Think Twice – Mauboussin

All decisions don’t require you to think twice. Simple decisions should be made simply. You need to think twice only when you face high stakes decisions. You should use the following ideas to improve your thinking. They emphasize preparation, recognition and application. The ideas help identify mistakes that are common, identifiable, and preventable. Mauboussin draws from the top experts in many fields to form his decision making framework.

1.1 The ouside view

This is about being overly optimistic because you focus on a specific task and use information close at hand to make predictions on that narrow view. The inputs may include anecdotal evidence and false perceptions. The outside view asks if their are similar situations that provide a statistical basis for decision making. What have others faced that is similar to the current situation. If there is precedent, how did it turn out? Why do we prefer the inside view? Most are too optimistic. Least capable people have the biggest gaps between what they think they can do and what they can actually do. Illusion of optimism, my results will be better than others. Illusion of control, I can control chance events. Poor at estimating the future, big gap between what people think they can accomplish and what they actually can. How to avoid falling into the trap?

1.1.1 Find a reference class

  1. Something representative of the situation

1.1.2 Access the distribution of outcomes

  1. Look close at the success and failure rate
  2. Must be reasonably stable over time
  3. Watch out for systems where small changes cause large perturbations.

1.1.3 Make a prediction

1.1.4 Access the reliability of your prediction and refine

1.2 An insufficient consideration of alternatives

The world is not black and white, consider alternatives

1.2.1 Explicitly consider alternatives

  1. Know your batna, your walkaway price and the same two items for the person your negotiating with

1.2.2 Seek dissent

1.2.3 Keep track of previous decisions

1.2.4 Avoid making decisions at emotional extremes

1.2.5 Understand incentives

1.3 Collectives are sometimes, a lot of times, better than experts

In a lot of situations it’s better to have a collective decision than it is to rely on the advice of an expert. Collective error = avg. individual error – prediction diversity (Scott Page) Expert intuition works well if the expert has put in enough deliberate practice, most have not. Deliberate practice includes: activities designed to improve performance, repeatable tasks, high quality feedback, and is not much fun. Most do not come close to satisfying the requirements. Don’t rely too much on either collective or experts, both have their flaws.

1.3.1 Match the problem you have with the most appropriate solution

  1. There is not one decision making technique that fits all problems

1.3.2 Seek diversity

  1. Foxes (broad skills) are usually better than hedgehogs (deep skill) Tetlock

1.3.3 Use technology when possible

  1. Lots of companies not taking advantage of technology

1.4 Situation influences our decisions enormously

We are overly influenced by our situation and surroundings. From words to environment to people. Easterners are attuned to environments, westerners to objecs. Westerners believe they are more in control, easterners are more open to change (Nisbett) Westerners focus on individual, easterners on relationships and social context. People who structure choices create a context for decision making (thaler, sunstein) We often ignore expected utility. Affect, how we feel about something influences decisions. Be careful not to explain peoples behavior by focusing on their disposition, rather than considering the situation (Milgram) Be mindful of what is going on around you. Be aware of inertia, why do we always do it this way? How regulatory inertia trumped the good decision of using a checklist (Gawande) Primes, defaults, affect and the behavior of others around us weigh on how we decide and it is often unconsious.

1.4.1 Be aware of your situation

1.4.2 Consider the situation first and the individual second

1.4.3 Watch out for the institutional imperative

  1. Mindlessly imatate what peers are doing
    1. Want to be part of in group
    2. Incentives

1.4.4 Avoid Inertia

1.5 Complex adaptive systems

Made up of three parts, a group of heterogenous agents (different and evolving decision rules that both reflect the environment and attempt to anticipate change in it). Agents interact and create structure (emmergence). The structure that emerges behaves like a higher level system and has properties and characteristics that are distinct from those of the underlying agents themselves. Ex. Individual ant is inept, but colony as a whole is smart. Humans have a deep desire to understand cause and effect. In CAS, there is no simple method for understanding the whole by studying the parts. We inappropriately extrapolate individual behavior to explain collective behavior. Mistake with behavioral finance is that since individuals are irrational, markets must be irrational. With systems, collective behavior matters more. You must carefully consider the unit of analysis to make a proper decision. Unintended consequences are always an issue in these types of systems. Don’t isolate individual performance from their surrounding system. “Orderly processes in creating human judgement and intuition lead people to wrong decisions when faced with complex and highly interacting systems.” Jay Forrester

1.5.1 Consider the system at the correct level

  1. More is different
  2. If you want to understand the stock market, consider it at the market level

1.5.2 Watch for tighly coupled systems

  1. Most CAS are loosly coupled, removing parts don’t make a big impact
  2. When agents loose diversity and act in similar fashion, can become tighly coupled (booms, crashes)

1.5.3 Use simulation to create virtual worlds

1.6 The importance of understanding context

Frequently, people try to cram the lessons or experiences from one situation into a different situation (see 1st chapter about looking for reference class, is this why?) The answer to most questions that professionals seek is, “It depends”

1.6.1 The process of theory building (Carlile & Christensen)

  1. Observation – measuring and documenting results
  2. Classification – simplify and organize
  3. Definition – describe relationship between categories and outcomes

    Ex. from using flapping wings to create flight to using an airfoil to create lift. Colonel Blotto, game in which each party gets a number of soldiers to distribute in a number of battlefields, the most soldiers in a battlefield wins the battle, most battles won wins the war. Gives insight into a failure to think about our competitive circumstances. High dimension contests increase the uncertainty of outcomes. Watch out for the correlation implies causality mistake. You must adpat your decision making process, even if it is psychologically taxing. Be careful not to be over anxious to leverage your favorable experiences by applying the same approach to the next situation. Find out what it “depends on”

1.6.2 Ask whether the theory behind your decision making accounts for circumstances

1.6.3 Watch for the correlation and causality trap

1.6.4 Balance simple rules with chaning conditions

1.6.5 Remember their is no best practice in domains with multiple dimensions

1.7 Phase transitions

Where small incremental changes lead to big effects. With lots of phenomena, outcomes don’t stray too far from average, but there are systems with heavily skewed distributions where the idea of average holds little or no meaning. This is where black swans come into play and the story of the turkey (chicken). Problem of induction, be careful to extrapolate from what you see. You have to look for things that disprove the idea. Reductive bias, a tendency for people to treat complex systems as much simpiler than they really are. A system that is complex and non-linear will often be reduced to a system that is simple and linear. Ex. Using normal distribution to explain asset price moves (Mandelbrot critisized, to no avail, if he’s right most current methods are obsolete) Near the center of the 2007-09 crisis is a little known formula by David Li called the Gaussian copula, which measures correlation of default between assets. The problem is correlation is not a static number, it changes as markets become worse. By modeling different worlds, you can see how hard prediction really is.

1.7.1 Study the distribution of outcomes for the system you are dealing with

  1. If we know the distributions, then they can be modeled, and are called grey swans
  2. Many are not burned by black swans, but their failure to prepare for grey swans

1.7.2 Look for phase transition moments (ah-whooms)

1.7.3 Beware of forecasters

1.7.4 Mitigate the downside, capture the upside

  1. Kelly Criterion (Thorpe)

1.7.5 Slow down when you see systems with phase transitions

1.8 Luck or Skill

Reversion to the mean. Causes three mistakes:

1.8.1 Thinking your special

1.8.2 You misinterpret what the data says

  1. If you truly have reversion to the mean, you get the same results backward or forward

1.8.3 Feedback on the luck part is useless, focus it on the process or skill part

The halo effect, when the overall impression of something obscures the details (Thorndike) Mean reversion shapes company performance, which in turn manipulates perception (this is a money making idea!) Top selling business books fall prey to the halo effect because it tells managers what they want to hear: any company can be successful by taking these steps. In fact, no simple formula ensures success in a rapidly chaning business environment. (Finally the first negative review of Good to Great, never saw why it was so popular.)

1.8.4 Evaluate the mix of skill and luck in the system you are analyzing

  1. Simple heuristic: ask if you can lose on purpose, if so skill is involved
  2. When something good happens, we say its skill, when bad, its chance. So forget about the outcomes and focus on process

1.8.5 Carefully consider the sample size

  1. Don’t extrapolate conclusions from small sample sizes
  2. The more luck involved, the bigger the sample size you need
  3. Streaks usually indicate skill

1.8.6 Watch for change within the system or of the system

1.8.7 Watch out for the halo effect

1.9 How to put these ideas to practice

1.9.1 Raise your awareness

  1. Look for poor thinking and second rate decision making in others
  2. Write to clear your thinking
  3. Watch for hindsight bias

1.9.2 Put yourself in the shoes of others

  1. Think about the outside view
  2. Think about the power of the situation
  3. Think about how your actions trigger reactions, and so on
  4. Consider incentives and motivations
  5. Develop empathy

1.9.3 Recognize the role of skill and luck

  1. When luck is involved, you should expect reversion to the mean
  2. Constructive critisism only on the process part, the part they control

1.9.4 Get Feedback

  1. You must be open to it, not useful if you can’t absorb it
  2. Use a decision making journal
    1. Audit decisions
    2. Find patterns in your thinking
    3. Allows introspection

1.9.5 Create a checklist

  1. Useful in stable environments
  2. Should balance: general enough for varying conditions, specific enough to guide action
  3. Not too long, one or two pages at most

1.9.6 Perform a postmortem

  1. And possibly a premortem (Gary Klein), where before the decision you pretend it has failed and why

1.9.7 Know what you can’t know

  1. Consider worst case scenarios
  2. Resist temptation to treat complex system as simple
  3. Everyone realizes how important decision making is, but few practice

Prepare your mind, recognize the context, apply the right technique and practice!!!