Book Cover

Optimism is both a great driver of progress and problematic.  In this chapter, Kahneman explores the concept and impact of optimism bias. This bias causes a person to believe that they are less likely to experience a negative event. For example, most software engineers believe that they have never met a problem they can’t solve — an unrealistic assessment in any complicated environment. Another typical example, most drivers think they are better than average — a statistical impossibility. A third example that we have commented on before, estimates chronically fall prey to optimism bias. The list of examples could go on nearly forever. This effect is driven by the propensity of individuals to exaggerate their abilities.    

Optimism bias makes it easy to take risks. Kahneman points out that by facilitating risk-taking, this bias is the engine of capitalism. Optimists form new companies and organizations, ignoring the chances of success. According to Forbes.com, 90% of startups fail.  Entrepreneurs feel that they can overcome any of the problems they might encounter (we have heard that before). On the positive side, lots of different experiments are executed and some of them survive however, for every Google and Tesla there are numerous failures.  Kahneman points out that not all of the problems with entrepreneurial failures can be attributed to purely optimism bias. For example, he cites studies that celebrity CEOs tend to spend too much time away from the business as they celebrate their successes at the expense of moving forward. In addition, other common biases have their hand in the pie including:

  • Anchor bias
  • Illusion of control
  • Focusing on what we know and neglecting what we don’t

Neglecting what we don’t know leads can lead to a blindness to the competition. One impact of competition neglect, as Kahneman describes the effect, is that too many firms enter a market that can’t compete in because of a dominant player or too many competitors. When there are too many organizations competing in the same market, many will fail. Optimism bias, by inoculating the organization through a dose of resilience, facilitates hanging on longer than a good understanding of the probability of success would suggest.  

One of the suggestions recommended by Kahneman for overcoming optimism bias and competition neglect is the premortem. Premortems are a useful tool for helping project teams anticipate risks.  Premortems were described in the Harvard Business Review, September 2007 by Gary Klein.

Kahneman titled chapter 24, The Engine of Capitalism. Optimism convinces entrepreneurs to take risks and start new firms even when statistically most will fail for a myriad of reasons. This type of bias pushes to start-ups to be resilient in the face of adversity.  We are describing a double-edged sword. Long live optimism because with a bit of tempering it is a force that can define the future. 

Remember, if you do not have a favorite, dog-eared copy of Thinking, Fast and Slow, please buy a copy.  Using the links in this blog entry helps support the blog and its alter-ego, The Software Process and Measurement Cast. Buy a copy on Amazon,  It’s time to get reading!

 

The installments:

Week 1: Logistics and Introduction – http://bit.ly/2UL4D6h

Week 2: The Characters Of The Story – http://bit.ly/2PwItyX

Week 3: Attention and Effort – http://bit.ly/2H45x5A

Week 4: The Lazy Controller – http://bit.ly/2LE3MQQ

Week 5: The Associative Machine – http://bit.ly/2JQgp8I

Week 6: Cognitive Ease – http://bit.ly/2VTuqVu

Week 7: Norms, Surprises, and Causes – http://bit.ly/2Molok2

Week 8: A Machine for Jumping to Conclusions – http://bit.ly/2XOjOcx

Week 9: How Judgement Happens and Answering An Easier Question – http://bit.ly/2XBPaX3

Week 10:  Law of Small Numbers – http://bit.ly/2JcjxtI

Week 11: Anchors – http://bit.ly/30iMgUu

Week 12: The Science of Availability – http://bit.ly/30tW6TN

Week 13: Availability, Emotion, and Risk – http://bit.ly/2GmOkTT

Week 14: Tom W’s Speciality – http://bit.ly/2YxKSA8

Week 15: Linda: Less Is More – http://bit.ly/2T3EgnV

Week 16: Causes Trump Statistics – http://bit.ly/2OTpAta

Week 17: Regression To The Mean – http://bit.ly/2ZdwCgu

Week 18: Taming Intuitive Predictions — http://bit.ly/2kAHClJ

Week 19: The Illusion of Understanding – http://bit.ly/2lK954p

Week 20: The Illusion of Validity –   http://bit.ly/2mfyrYh

Week 21: Intuitions vs Formulas – http://bit.ly/2kx7kri

Week 22: Expert Intuition – http://bit.ly/2ooe50h

Week 23: Chapter 23: The Outside View http://bit.ly/35dOibJ