Tiponomics: Analytics for Waiters
A recent lunchtime conversation with a friend reminded me that data-mining/analytics/optimization opportunities are lurking everywhere.
It all started innocently enough. I miscalculated the tip at lunch and was about to leave a 10% tip (rather than the 20% that I was planning to) when my friend pointed out the error. He said that he had been sensitized to tip amounts by his college-age son who had done part-time/summer jobs as a restaurant waiter for several years. He went on to share fascinating examples of how his son made real-time decisions to maximize his tips.
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