Dime-a-dozen explanations of what makes companies successful are not new—these narratives have enjoyed a rich history of exploration in both academic and popular presses. However, the types of success stories which gain traction are fraught with bias. For instance, disproportionate attention is placed on wildly successful “unicorn” companies, while the far greater number of unsuccessful companies often goes unaccounted for.
Moreover, attempts to decipher what makes companies successful based on these examples are similarly skewed; explanations often highlight certain shared traits of successful companies while ignoring others, or turn a blind eye to the unsuccessful companies which exhibit the same “successful” traits.
The result? According to the researchers behind “Success stories cause false beliefs about success,” such non-representative sampling and explanatory cherry-picking means that “almost any feature of interest can appear to be associated with success” as long as there exist at least some examples of such an association.
In a new paper published in Judgment and Decision Making, Duncan Watts, Penn Integrates Knowledge Professor and Stevens University Professor in the Annenberg School for Communication with appointments in the School of Engineering and Applied Sciences and Wharton, and co-authors set out to determine whether these plainly biased narratives cause readers to arrive at incorrect inferences about reality—and, if so, whether these effects are large enough to matter.
Simply showing outlier examples of success substantially affected participants’ beliefs about what makes a company successful. This study shows that it is possible to lead people to unwarranted conclusions using manipulation that would easily pass a fact check—and that being aware of the information’s bias is not enough to offset these effects.
by Emma Arsekin.