A new book attempts to make behavioral economics interesting and approachable by couching it in the world of sports. Personally I try to avoid books on economics, but I did find a review quite interesting. Not only did it help to explain why the Philadelphia Flyers lost the 1980 Stanley Cup, but it also helps to illustrate the limitations of crowd sourcing and the reality of Asymmetry in key driver analysis.
Behavioral economics studies the role of emotion in economic decision making (something marketers need to master). In application it can help to explain the illogical decision making of shoppers. A classic example of this is when someone spends $1000 on a product they don't need thanks to a price cut of say $200. They will often focus on what they saved ("I saved $200!!!) and not on what they spent or the actual need.
In sports terms the authors looked at statistics to determine if any similar odd economic-like thinking could be found. A great example can be found in golf (those of you who read this hoping that Tiger Woods' lessons on research would feature statistics involving waitresses named "Candy" will be disappointed). When the authors looked at putts of equal distance, they found that he was far more likely to miss if the putt was for birdie, than if it was for par. Since both count as one stroke, there is no reason to expect that his performance would differ (and by the way, all the golfers they looked at had similar stats, but putting "Tiger" in the title gets me more attention). So why did they?
The Authors theorize that he fears going over par and thus concentrates very hard on par putts. In other words he values it more. Mr. Spock would find this illogical. He would focus on his total score and recognize that every time he misses a putt his score goes up by one so he would see both putts as equal.
Since we don't sell to Vulcans however, understanding this decision making is critical. We see this all the time in how customers view transactions. It is evident in all the things that customers take for granted and the things they don't. Customers punish firms that do worse than expected and reward those that do better. For example, airlines that have good safety records are not rewarded, but those that have questionable safety are punished. By the same token, airlines generally are not punished for treating customers like cattle, but when they do something a bit different (such as Southwest Airlines having flight crews with personalities) they are rewarded. If we don't consider these asymmetric effects in our analysis we will miss important clues as to how consumers make decisions.
A second learning from the article is about referees (or umpires). The authors wanted to figure out why home teams win more often than visitors. What they found was that the refs favored the home team. Their theory is that the refs suffered from a "crowd sourcing" effect. For example, because they are biased, fans often see a bigger strike zone for their pitcher than they do for the opposing pitcher ("you call that a strike????"). The umpire might pick up on these cues and allow the wisdom of the larger group (the fans) to alter his decision making...even though that larger group is clearly biased.
Anyone who has ever been at a focus group with a strong personality in the mix has seen this in action and we'd be wise to keep this in mind as we work with increasingly unrepresentative samples. Understanding and accounting for the bias inherent in those samples will be critical if our work is to have value.
Perhaps the most important lesson, for me at least, is that it is time to forgive Leon Stickle...he wasn't blind, he was just crowd sourcing.
PS ...if you are not a Flyers fan, then you probably don't know that Leon Stickle allowed a player to score a goal while he was off sides in a game the Flyers went on to lose in overtime, giving the Islanders the Stanley Cup. Islanders fans are free to point out that we have no way of knowing how the game would have ended had Stickle gotten it right, but a representative sample of Flyers fans in our offices knows the Flyers would have won the Cup.
Rich brings a passion for quantitative data and the use of choice to understand consumer behavior to his blog entries. His unique perspective has allowed him to muse on subjects as far afield as Dinosaurs and advanced technology with insight into what each can teach us about doing better research.