How Decision Science Helps Snag the Stanley Cup and Shape Retail KPIs
How Decision Science Helps Snag the Stanley Cup and Shape Retail KPIs

Apple, Beauty and Biscuit. No these are not the names of celebrity children. I am talking about hockey as a metaphor for KPIs. With the NHL playoffs right around the corner, my thoughts naturally center on KPIs and analytics. So lets get our Mitts and Twigs ready and dive into how these things are related.

For example, when down by 1 or more points, it is common for coaches to replace the goaltender, known as pulling the goalie, with an offensive player in the final 1-2 minutes of the game as a last-ditch effort to at least bring the game to a tie and force overtime. Of course, exposing the goal this way involves some risk-reward analysis, but could result in a Celly. If your sole objective is to win the game, exactly when is this best done?

Several recent studies employing decision science have revealed that the optimal time to pull the goalie when down by 1 point is actually with about 5 minutes left in the game, and with about 11 minutes left when down by 2 points. But, while the science at least appears to be influencing coaches to pull goalies slightly earlier now, it's never by nearly that much. Why is that? Don't they want to score a Gino and win?

Well, they do, but apparently winning isn't the only objective. Another objective might be optimizing fan sentiment, which would be harmed by a higher point-margin loss resulting from pulling the goalie earlier, especially for fans that paid a small fortune to see a live Gongshow.

Recall in a previous post, New KPIs of Retail, the recommendation to tie KPIs to objectives and objectives to goals, for context in how to interpret them to inform critical decisions. If one of those two objectives above (winning and optimizing fan sentiment) weren't considered, the decision on when to pull the goalie would be very different. Goals, objectives and KPIs are, wait for it...a trifecta!

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