In the summer of 2006, Todd Carlisle, a Google analyst with a doctorate in organizational psychology, designed a 300-question survey for every Google employee to fill out, The New York Times later reported.
Some questions were straightforward: Have you ever set a world record? Other queries had employees plot themselves on a spectrum: Please indicate your working style preference on a scale of 1 (work alone) to 5 (work in a team). Other questions were frivolous: What kind of pets do you own?
Carlisle crunched the data and compared it to measures of employee performance. He was looking for patterns to understand what attributes made a good Google worker. This was strongly related to another question that interested his boss, Laszlo Bock, senior vice president of People Operations: What attributes could predict the perfect Google hire?
Ten years ago, Google was infamous for its complex application process and brain-teasers—something Bock recently admitted were "a complete waste of time.” Google was essentially trying to Google the human-resources process: It wanted a search algorithm that could sift through tens of thousands of people—Google’s acceptance rate is about 0.2 percent, or 1/25th that of Harvard University—and return a list of the top candidates. But after a great deal of question-asking and number-crunching, it turned out that the best performance predictor wasn’t grade-point average, or type of pets, or an answer to the question, “How many times a day does a clock’s hands overlap?” The single best predictor was: absolutely nothing.