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The premise of the article may be valid, but the author's top source is not sound. The piece quotes Jay Porter extensively and links to his blog post. Jay Porte

by gkop 13y ago

The premise of the article may be valid, but the author's top source is not sound. The piece quotes Jay Porter extensively and links to his blog post. Jay Porter is a failed restaurateur whose restaurants have all shut down [0] [1], not a source to be trusted on the subject of well-run restaurants. [0] http://www.yelp.com/biz/el-take-it-easy-san-diego http://www.yelp.com/biz/el-take-it-easy-san-diego [1] http://www.yelp.com/biz/the-linkery-san-diego http://www.yelp.com/biz/the-linkery-san-diego

tveita 13y ago
I found his blog posts to be well-argued and sourced. I think they stand on their own even if his restaurants weren't ultimately successful.
kennywinker 13y ago
The high failure rate in the restaurant industry means these businesses could have failed for entirely stochastic reasons unrelated to Jay Porter. If 80 of all restaurants fail, then he's got to start 8+ before we start to find out if he's the common denominator.
- gkop 13y ago
  That's not how probability works [0]. Say we assume a more realistic 40% success rate figure [1], given Jay's 2 trials: Probability of 1 success: (2 choose 1)(0.4^1)(0.6^(2-1)) = 0.48 Probability of 2 successes: (2 choose 2)(0.4^2)(0.6^(2-2)) = 0.16 0.48 + 0.16 gives us a 64% of at least one of Jay's restaurants succeeding. So the odds were in fact in his favor. [0] https://en.wikipedia.org/wiki/Binomial_distribution#Cumulative_distribution_function https://en.wikipedia.org/wiki/Binomial_distribution#Cumulati... [1] http://www.businessweek.com/stories/2007-04-16/the-restaurant-failure-mythbusinessweek-business-news-stock-market-and-financial-advice http://www.businessweek.com/stories/2007-04-16/the-restauran...
  - kennywinker 13y ago
    My apologies! I'm a long way out from stats class now, but I've been doing some light A/B testing so I've been thinking about things from the perspective of statistical significance rather than simple probability. So with that in mind, only having two trials, can we really determine a deviation from the norm? The odds were in his favour (slightly) but not so much that we can say with any certainty that he or his tipless restaurants were the issue. I'm rusty on the math or I'd actually calculate statistical significance (p value?) of 2 tries 1 success vs two tries 0 successes. I suspect it's below 95% though.
    - gkop 13y ago
      I agree we should not draw any conclusions from my arithmetic above. I just couldn't resist the opportunity to correct someone's math on HN :)
  - Dylan16807 13y ago
    You're still trying to draw conclusions from a 2-sample almost-even-odds outcome, which we really can't.
anigbrowl 13y ago
I was struck by his quote: 'The other reason we didn’t accept tips was that removing any option for tipping was the only way to remove those two parasitic businesses — the side business between the server and guest, and the side business between the server and cooks — from our own company.' So he sees tips as a drain on his income stream.

by gkop 13y ago

tveita 13y ago

I found his blog posts to be well-argued and sourced. I think they stand on their own even if his restaurants weren't ultimately successful.

kennywinker 13y ago

The high failure rate in the restaurant industry means these businesses could have failed for entirely stochastic reasons unrelated to Jay Porter. If 80 of all restaurants fail, then he's got to start 8+ before we start to find out if he's the common denominator.

gkop 13y ago
That's not how probability works [0]. Say we assume a more realistic 40% success rate figure [1], given Jay's 2 trials: Probability of 1 success: (2 choose 1)(0.4^1)(0.6^(2-1)) = 0.48 Probability of 2 successes: (2 choose 2)(0.4^2)(0.6^(2-2)) = 0.16 0.48 + 0.16 gives us a 64% of at least one of Jay's restaurants succeeding. So the odds were in fact in his favor. [0] https://en.wikipedia.org/wiki/Binomial_distribution#Cumulative_distribution_function https://en.wikipedia.org/wiki/Binomial_distribution#Cumulati... [1] http://www.businessweek.com/stories/2007-04-16/the-restaurant-failure-mythbusinessweek-business-news-stock-market-and-financial-advice http://www.businessweek.com/stories/2007-04-16/the-restauran...
- kennywinker 13y ago
  My apologies! I'm a long way out from stats class now, but I've been doing some light A/B testing so I've been thinking about things from the perspective of statistical significance rather than simple probability. So with that in mind, only having two trials, can we really determine a deviation from the norm? The odds were in his favour (slightly) but not so much that we can say with any certainty that he or his tipless restaurants were the issue. I'm rusty on the math or I'd actually calculate statistical significance (p value?) of 2 tries 1 success vs two tries 0 successes. I suspect it's below 95% though.
  - gkop 13y ago
    I agree we should not draw any conclusions from my arithmetic above. I just couldn't resist the opportunity to correct someone's math on HN :)
- Dylan16807 13y ago
  You're still trying to draw conclusions from a 2-sample almost-even-odds outcome, which we really can't.

anigbrowl 13y ago

I was struck by his quote: 'The other reason we didn’t accept tips was that removing any option for tipping was the only way to remove those two parasitic businesses — the side business between the server and guest, and the side business between the server and cooks — from our own company.' So he sees tips as a drain on his income stream.