Surprisingly, anchors influence us even when they bear no relationship to the estimated value, and even when they’re patently absurd. Following the seminal experiments of Kahneman and Tversky in the 1970s, two German researchers named Thomas Mussweiler and Fritz Strack demonstrated this effect with remarkable creativity. In one of their experiments, they divided their subjects into two groups, asking one group whether Mahatma Gandhi was over or under 140 years old when he died, and the other whether he was over or under 9 years old when he died. Obviously, no one had trouble answering these questions. But when the respondents were then asked to estimate Gandhi’s age at death, these clearly ridiculous “anchors” made a difference: the group anchored on 140 thought, on average, that Gandhi had died at age 67, whereas the group anchored on 9 believed he had died at age 50. (Actually, Gandhi died at age 78.)
Tag: You’re About to Make a Terrible Mistake!: How Biases Distort Decision-Making and What You Can Do to Fight Them
💎 Kleiner Perkin’s tactic for avoiding their staff developing entrenched positions in meetings (flip-flop)
Another renowned venture capitalist, Kleiner Perkins’s Randy Komisar takes this idea one step further. He dissuades members of the investment committee from expressing firm opinions by stating right away that they are for or against an investment idea. Instead, Komisar asks participants for a “balance sheet” of points for and against the investment: “Tell me what is good about this opportunity; tell me what is bad about it. Do not tell me your judgment yet. I don’t want to know.” Conventional wisdom dictates that everyone should have an opinion and make it clear. Instead, Komisar asks his colleagues to flip-flop!
💎 Analysing successful brands can be misleading (survivorship bias)
The models whose success we admire are, by definition, those who have succeeded. But out of all the people who were “crazy enough to think they can change the world,” the vast majority did not manage to do it. For this very reason, we’ve never heard of them. We forget this when we focus only on the winners. We look only at the survivors, not at all those who took the same risks, adopted the same behaviors, and failed. This logical error is survivorship bias. We shouldn’t draw any conclusions from a sample that is composed only of survivors. Yet we do, because they are the only ones we see.
Our quest for models may inspire us, but it can also lead us astray. We would benefit from restraining our aspirations and learning from people who are similar to us, from decision makers whose success is less flashy, instead of a few idols
