Book Cover


Some characteristics influence the assessment of a situation more than others. We weight characteristics and attributes whether we are aware or not. When we are not aware we are defaulting to system 1 thinking which as we have read is very biased. This is one reason why formal decision-making processes codify the weighting of attributes to avoid personal biases. 

Kahneman discusses two effects that often affect the act of decision making in teams. The first is the possibility effect. The possibility effect occurs when the possibility of an outcome moves from zero probability to even a minor probability (5% probability). In this scenario, people perceive the possibility of the outcome as being far more probable. Earlier this year, I was discussing a request for a team to deliver 14 features by the end of the year. Based on the throughput of the team, the probability of delivery was approximately 3%. The department executive felt that it was possible they should commit to the request. The second effect, the certainty effect, occurs when a very possible outcome can be converted to certainty. In this scenario people overweight outcomes that are certain relative to those that are highly probable. A few evenings ago I heard an advertisement for a company that would convert a structured payment into a single payment (at a significant discount – I read the fine print). People that take this type deal trade structured payments that have a very high probability of payment for the absolute certainty of a single payment. It is easy to see both of these effects in software organizations.  The possibility effect contributes to leaders and project managers rationalizing work that is only nearly impossible while the certainty effect explains some of the resistance to the shifting continuous delivery and product models. 

The Fourfold Pattern provides a way to think about how people behave when faced with decisions that will yield gains and losses that either is a high probability (certainty effect) or q low probability. The Patten can be illustrated as a risk matrix (page 317 in my copy). Understanding the impact of risk on decision-making is useful when coaching and mentoring decision-makers to recognize their biases. In the end, Kahneman reminds us that, “People are not perfectly rational choosers.”

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 –    

Week 2: The Characters Of The Story –  

Week 3: Attention and Effort – 

Week 4: The Lazy Controller – 

Week 5: The Associative Machine – 

Week 6: Cognitive Ease – 

Week 7: Norms, Surprises, and Causes – 

Week 8: A Machine for Jumping to Conclusions – 

Week 9: How Judgement Happens and Answering An Easier Question – 

Week 10:  Law of Small Numbers – 

Week 11: Anchors – 

Week 12: The Science of Availability – 

Week 13: Availability, Emotion, and Risk – 

Week 14: Tom W’s Speciality – 

Week 15: Linda: Less Is More – 

Week 16: Causes Trump Statistics – 

Week 17: Regression To The Mean – 

Week 18: Taming Intuitive Predictions — 

Week 19: The Illusion of Understanding –  

Week 20: The Illusion of Validity –  

Week 21: Intuitions vs Formulas – 

Week 22: Expert Intuition –   

Week 23: Chapter 23: The Outside View

Week 24: Chapter 24 The Engine of Capitalism –

Week 25: Chapter 25  Bernoulli’s Errors 

Week 26: Chapter 26 – Prospect Theory  

Week 27: Chapter 27 – Endowment Effect 

Week 28: Chapter 28 – Bad Events