The combination of stats and storytelling in these books make my data viz nerd brain go a bit gooey. They’re so good, I managed to read all three books in about 4 days. (Aided by Kindle and the beach).
The Freakonomics series explores how statistical methods can be used to shed light on social phenomenon, sometimes revealing an insight that goes against the conventional wisdom. Like… does the amount of campaign funding contribute towards a candidate’s chances of winning? Or does the winning candidate just attract more campaign funding? (The answer, according to the numbers, seems to be the latter).
One story that stood out for me is the one about Paul Feldman and his bagel deliveries. Feldman basically started a business delivering bagels to offices and selling them on an honour system by leaving a box where people could deposit money if they took a bagel.
“So by measuring the money collected against the bagels taken, he found it possible to tell, down to the penny, just how honest his customers were. Did they steal from him? If so, what were the characteristics of a company that stole versus a company that did not? Under what circumstances did people tend to steal more, or less?”
Each office had their own percentage return, which formed an index into how honest the office was. This index said a lot about the office (smaller offices had a higher honesty index than bigger ones, probably due to the familiarity and social bond between people), managers and executives have a lower return than workers. What’s interesting to me is that through Feldman’s experience with these offices, he saw the index as an indicator of the morale of the office.
For a measure that is soft and intangible like employee morale or how your office is doing, what could be 2nd or 3rd-hand indicators? Feldman’s honesty index isn’t, of course, a scientific measure, but it’s one that could be tracked over time to indicate when something might be going wrong… or as a comparison tool with other offices.
What are soft, intangible things about your office that you can’t measure for? And what indexes could we create to measure them?