Fields in which Analytics Do Not Apply

[typefitter]

This is well put.
Correlation does not equal causality. Most people fail to understand that, leading to the overestimation of predictive accuracy.
Further, statistical analysis is one piece of the decision-making process.

And in many instances, people are not honestly considering the data. They are looking for patterns in the data that reinforce, correctly or incorrectly, already held objectives.
I can analyze market trends and figure out what type of restaurant is more likely to be successful at a given location. That is appropriate.
Often, though, I have seen a space I like, or I've already determined that I want to have an Italian restaurant, or I've already determined both - now I'm really just seeking data that can reinforce what I want to do.
Lastly, most restaurants fail. Period. The failure of my restaurant is conditional on a lot of factors. Saying that statistical analysis was not useful in my business endeavor would be false, although saying that might make me feel better.

In the end, analysis, statistical or otherwise, requires a defined and measurable objective in order to have any utility.
If my objective is to move units, statistical analysis can help me sign the right act.
If my objective is to be able to tell people I sighed the next Elvis and I bucked all the trends to do it, then my objective is tainted from a business perspective.

This is helpful. I'm asking honestly, for what it's worth. I wonder if there are things that are resistant to such analysis. Baseball managing, for instance, is another one that got me thinking about it—like, what makes a good manager? Winning percentage is about the only statistic we have to measure a manager's success. So when a GM is deciding whether a manager is "good" or not, what goes into that calculus? I imagine a lot of that comes down to gut or feel. Or at least something less than rigorous statistical analysis.

I'm not saying that's a good thing. I'm just wondering out loud.

 

[JC]

This is helpful. I'm asking honestly, for what it's worth. I wonder if there are things that are resistant to such analysis. Baseball managing, for instance, is another one that got me thinking about it—like, what makes a good manager? Winning percentage is about the only statistic we have to measure a manager's success. So when a GM is deciding whether a manager is "good" or not, what goes into that calculus? I imagine a lot of that comes down to gut or feel. Or at least something less than rigorous statistical analysis.

I'm not saying that's a good thing. I'm just wondering out loud.

Winning pct is largely placed on the talent you have to work with. Joe Torre was a shipty manager until he became the Yankees manager when he all of a sudden became brilliant.

 

[Donny in his element]

1. Horseshoes
2. Hand grenades

 

[typefitter]

Winning pct is largely placed on the talent you have to work with. Joe Torre was a shipty manager until he became the Yankees manager when he all of a sudden became brilliant.

Right—so how do you know who's a good manager?

 

[Songbird]

Maddon's 867-5309 lineup went 2 for 22 on 7/3/14. Good manager or bad?

Batting               AB R H RBI BB SO PA   BA  OBP  SLG  OPS
Desmond Jennings CF    4 1 1   0  0  2  4 .241 .334 .379 .714
Ben Zobrist SS         4 0 0   0  0  0  4 .250 .336 .394 .731
Matthew Joyce LF       3 0 0   0  1  1  4 .268 .352 .423 .775
Evan Longoria 3B       2 0 0   1  0  0  3 .261 .331 .390 .721
James Loney 1B         3 0 1   0  0  0  3 .280 .332 .385 .717
Vince Belnome DH       3 0 0   0  0  2  3 .000 .000 .000 .000
Kevin Kiermaier RF     3 0 0   0  0  1  3 .290 .331 .556 .887
Ryan Hanigan C         3 0 0   0  0  1  3 .223 .311 .344 .655
Cole Figueroa 2B       3 0 0   0  0  1  3 .150 .150 .200 .350
                                                            
Team Totals           28 1 2   1  1  8 30 .071 .100 .107 .207

Add in Hanigan's and Figueroa's o-fers and it's 2 for 28.

 

[Songbird]

With the Cubs struggling at the bat, Maddon inserts 6-foot-12 slugger Anthony Rizzo into the leadoff spot, where he proceeds to go nuts in those 42 at-bats.

Good manager or bad?

 

[Buck]

This is helpful. I'm asking honestly, for what it's worth. I wonder if there are things that are resistant to such analysis. Baseball managing, for instance, is another one that got me thinking about it—like, what makes a good manager? Winning percentage is about the only statistic we have to measure a manager's success. So when a GM is deciding whether a manager is "good" or not, what goes into that calculus? I imagine a lot of that comes down to gut or feel. Or at least something less than rigorous statistical analysis.

I'm not saying that's a good thing. I'm just wondering out loud.

I think in a case like hiring a baseball manager, statistical analysis has a place in the decision-making process, but it is one piece of the process.
Winning percentage is nice but you'd like to find a way to normalize that to account for roster talent.
As mentioned, roster talent is a key component to any manager's winning percentage.
Winning 95 games with a great team might take limited managerial ability.
Winning 85 games with a really crappy team might require Herculean managerial ability.
So you could normalize that statistically, and look for additional statistical indicators of managerial ability.

But you would not rely on statistical analysis solely. No good decision is made by relying on limited information and processes.
You'd talk to the guy's colleagues and previous bosses, maybe some of his former players.

But just because statistical analysis is not the sole criteria for making the hiring decision does not mean it should not be a component of the hiring decision or that is useless.

 

[Guy_Incognito]

I think in a case like hiring a baseball manager, statistical analysis has a place in the decision-making process, but it is one piece of the process.
Winning percentage is nice but you'd like to find a way to normalize that to account for roster talent.
As mentioned, roster talent is a key component to any manager's winning percentage.
Winning 95 games with a great team might take limited managerial ability.
Winning 85 games with a really crappy team might require Herculean managerial ability.
So you could normalize that statistically, and look for additional statistical indicators of managerial ability.

But you would not rely on statistical analysis solely. No good decision is made by relying on limited information and processes.
You'd talk to the guy's colleagues and previous bosses, maybe some of his former players.

But just because statistical analysis is not the sole criteria for making the hiring decision does not mean it should not be a component of the hiring decision or that is useless.

I'm not even sure that will help, because those extra 10 wins are constructed from better play, which implies that the team might just be better than you thought it was before the season.

 

[Evil ... Thy name is Orville Redenbacher!!]

Art and music and by extension artists and musicians.

What makes good, great and bad art?

And music?

Entertainers. Comedians, singers... I think analytics takes a backseat .

 

[dooley_womack1]

Baseball