3BI: decision-making biases in technology, sports, and the legal system
Hello everyone!
Last month, Nir Eyal and I wrapped up the latest cohort of our Product Psychology Bootcamp with an awesome group of students. If you’re interested in joining a future session of the class, you can sign up for the wait list on the course page to be the first to know when the next one is scheduled.
This week’s edition focuses on examples of how psychological biases can still be rampant in high stakes decisions in sports, business, and even the legal system.
Layoffs as social contagion
Layoffs at technology companies have been headlining business and economic news lately:
It is estimated that in 2022 alone, over 120,000 people have been dismissed from their job at some of the biggest players in tech – Meta, Amazon, Netflix, and soon Google – and smaller firms and starts ups as well.
Interestingly, many of the layoffs are strikingly similar in scope, with a number of major companies letting go a nearly identical percentage of their workforce.
While there are certainly economic factors at play, there’s also likely an element of psychology motivating these decisions, especially a concept called “social contagion,” where a behavior spreads through a network as decision-makers follow the lead of others. From Stanford Business School professor Jeffrey Pfeffer, who studies the hiring and firing practices of companies:
The tech industry layoffs are basically an instance of social contagion, in which companies imitate what others are doing. If you look for reasons for why companies do layoffs, the reason is that everybody else is doing it. Layoffs are the result of imitative behavior and are not particularly evidence-based.
I’ve had people say to me that they know layoffs are harmful to company well-being, let alone the well-being of employees, and don’t accomplish much, but everybody is doing layoffs and their board is asking why they aren’t doing layoffs also.
According to Pfeffer’s research, layoffs are generally an ineffective mechanism for cutting costs or increasing stock prices and their consequences (like lower morale among remaining employees or a poorer customer experience) are often costlier than anticipated. According to his findings, companies would be better off long-term by replacing layoffs with other strategies, like retaining staff and accepting less profit in the short term, reducing cost with broad pay cuts, or even increasing investment by hiring talent let go by others. Such evidence is ignored, however, because of pressure to follow the lead of competitors.
Writer Derek Thompson attributes such copycat behavior to uncertainty:
Chief Executives are people, and people navigate uncertainty by copying each other. When you don’t know what to do, you copy people.
Imagine being at…[an amusement park], and you don’t know what ride to take next, and…you see a mass of people that are moving toward one ride or attraction, and you’re like, ‘oh, where’s that crowd going?’ You’re more likely to copy behavior when you’re uncertain.
When all of your competitors are laying off 10% of their staff, and they’re being rewarded by investors for doing so…that makes it easier to cull 10% of your staff and expect that we’re not going to get dinged for it because everyone else is doing it.
This hints that following the lead of others is not necessarily a strategy for optimization, but for risk reduction. There’s much less reputational risk when doing something everyone else is doing.
This isn’t to say that there aren’t real financial or strategic reasons for widespread layoffs in an industry, because of course there are. But, it’s an example of how there are a variety of hidden and often illogical influences to our decisions, even for big shot CEOs with a lot of money on the line.
Biases of the NFL Draft
Technology executives aren’t the only one susceptible to cognitive biases for important personnel decisions. With the NFL season officially over after last night’s Super Bowl, teams will begin to shift their attention to the draft, where they decide which young talent to invest in for the future.
NFL teams have more information on potential employees than most companies that make hiring mistakes. The draft is their most effective method of landing stars on the cheap, and the stakes are especially high when it comes to scouting a quarterback, where one pick can be the difference between a dynasty and dysfunction. They want as much data as they can get. Only in sports do people get their hands measured down to an eighth of an inch before their first day of work.
Despite having better data on candidates than nearly any other employer, teams still struggle to properly identify talent, in part because having more data doesn’t eliminate psychological biases. In 2013, economists Cade Massey and Richard Thaler (who later won the Nobel Prize for his work helping establish the field of behavioral economics) published a paper studying the decision-making of NFL teams in the draft:
The economists found several cognitive errors associated with uncertainty and overconfidence that can fool teams, including the false-consensus effect, when people believe their own beliefs are more common than they really are. In the NFL draft, that delusion can be costly. When the researchers studied more than 1,000 trades involving draft picks over 25 years, they discovered that teams overpay to trade up and select the player they covet. They are terrified another team will grab him first.
Instead of becoming overly invested in individual players, teams would be better off accepting their inability to predict the future and aim to acquire more players at lower costs:
…the year before they drafted Mr. [Brock] Purdy, the [San Francisco] 49ers made a bold trade, parting with three first-round picks to move from No. 12 to No. 3 so they could draft Trey Lance in 2021. They were confident that he was the quarterback who would take them to the Super Bowl. Instead, his season-ending ankle injury helped clear the way for the 2022 draft’s last pick, someone who wasn’t guaranteed a spot on the team and barely made the roster.
The scholars advise NFL teams with top picks to do the opposite of what the Niners did: trade down and collect multiple shots at players for the price of one. There comes a point in every draft when teams might as well trash their models and throw darts at their boards. To maximize their chances of being right, they need to acknowledge they will be wrong—and remember that even the 262nd pick can be a profitable investment.
If this season had unfolded the way the 49ers planned, Mr. Purdy would still be holding a clipboard on the sideline. But once he saw the field, he was better than anyone expected, including the team that drafted him.
Humility is key in decison-making. Data shows that even experts with all of the information in the world can’t predict the future, so we should make decisions accordingly.
Read more at the Wall Street Journal.
Emotions and Legal Decisions
Cognitive biases aren’t limited to those in the business world. They impact everyone - even those in the justice system. When judges are in a bad mood, data shows they’re less forgiving in their sentencing.
In a study of 207,000 immigration cases, researchers found that judges get annoyed when the weather is too hot:
…a 10 ◦F degree increase in case-day temperature reduces decisions favorable to the applicant by 6.55%. This is despite judgements being made indoors, ‘protected’ by climate-control. Results are consistent with established links from temperature to mood and risk appetite and have important implications for evaluating the influence of climate on ‘cognitive output’.
Another study found that judges in Louisiana were similarly impacted when the Louisiana State University football team lost in an upset, especially if they were alumni of the school:
We find that unexpected losses increase sentence lengths assigned by judges during the week following the game. Unexpected wins, or losses that were expected to be close contests ex ante have no impact.
The impact of upset losses on sentence lengths is larger for defendants if their cases are handled by judges who received their bachelor's degrees from the university with which the football team is affiliated.
The impact of those decisions was significant. In total, these harsher sentences resulted in an additional 1,296 days of punishment to juvenile defendants and 136 extra days of jail time.
This and the previous examples don’t necessarily mean that the judges, executives, or team general managers are uniquely biased or poor at their jobs. It means that they’re human and that we must design systems that account for the biases we all face, especially when the decisions have high stakes:
These results provide evidence for the impact of emotions in one domain on decisions in a completely unrelated domain among a uniformly highly educated group of individuals (judges) who make decisions after deliberation that involve high stakes (sentence lengths). They also point to the existence of a subtle and previously-unnoticed capricious application of sentencing.
HT to Ethan Mollick for sharing these studies.
That’s all for this edition. Have a great week!