4 ms·
That's not necessarily survivorship bias. Survivorship bias would be "Here's 10 successful companies, do what they do". If you analyze a pool of random companie
by highd 10y ago
That's not necessarily survivorship bias. Survivorship bias would be "Here's 10 successful companies, do what they do". If you analyze a pool of random companies and then consider what the successful companies do differently then that would be decent scientific method (though you should form hypotheses first, really).
For example, if "risk-takers" both sometimes do very well and also often fail then you expect to capture the failed risk-takers in your initial sample, so you're not just biased by the successful risk-takers (said survivorship bias).
I'm not familiar with the book, but the snippet you reference describes something much closer to proper scientific method than most of the examples of this phenomena.
- jimbokun 10y agoNo, you can't just analyze the 11 successful companies. You need to consider multiple variables, then see if they correlate with success over the entire population. It's perfectly possible some traits of all 11 successful companies are also shared by most of the unsuccessful ones, too.
- PhilWright 10y agoYou have to identify something specific and then look at that specific factor across the entire population of companies. If you survey all CEO's of the Fortune 500 you might find that they are all workaholics. Do you conclude that being a workaholic will make you a CEO? Of course not. Did you look at how many workaholics there are that don't become CEO? That is survivorship bias. You also need to look at cause and effect. Is it that you must be a workaholic to become CEO? Or is it that as you climb the ladder you end up working hard and harder because that is a requirement of each position. Maybe being a workaholic is an effect of climbing high.