6 ms·

What makes Moneyball a fascinating example is neither Brad Pitt's star-power nor Michael Lewis's writing. Baseball is an optimal canvas for finding market inef

What makes Moneyball a fascinating example is neither Brad Pitt's star-power nor Michael Lewis's writing. Baseball is an optimal canvas for finding market inefficiencies because everything is tallied and tracked. We can ascertain after the fact who ultimately did add value to their organizations. In this case, the author argues what Billy Beane argued, "if we think like the Yankees in here, we will lose to them out there." If non-FAANG companies compete for the same prospective employees as FAANG employees, they will lose to vastly superior compensation packages. Fair enough. So the question, which traits are analogous to on-base-percentage? Take the FAANG-hire-resume, then subtract features (e.g. lose the top-10 university credential, remove a couple years of experience, ditch the years with a trendy package, etc). Which decreases the hiring cost the most with the smallest loss of long-term value to the hiring company? What data set would track/measure this and what could be deployed as a proxy?

tialaramex 5y ago
> If non-FAANG companies compete for the same prospective employees as FAANG employees, they will lose to vastly superior compensation packages. Fair enough. Already this part is unclear. Baseball is different in another important respect: You have no choice about what you're doing. The Yankees, the As, anybody - is hiring you as, say, a pitcher. That's what you're good at, that's what you're doing. But I chose to work where I do now, for far less money (the people hiring weren't sure but they suspected the previous salary I listed, which was true, was more than the head of their entire 100+ person department, several steps above me on the hierarchy) because of what I do. What I do here makes a difference I care about, whereas say, working at an investment bank (as one of my ex-Google friends does) would not do anything except make rich people even richer. If you're a big deal maybe you can carve a niche so that whoever it is that hires you, they're really hiring you to do whatever it is you do anyway. I can't imagine Bjarne Stroustrup feels what he does (at ms.com ie Morgan Stanley) is mostly about making rich people richer, Morgan Stanley presumably mostly lets him get on with C++ stuff. Likewise hiring Linus Torvalds wouldn't redirect him from working on Linux. If that was going to happen it would have happened a decade or more ago. But for most of us in programming, where we work dictates what we do, and that influences whether I want a role I'm offered or not.
- sjg007 5y ago
  Hedge funds might be closer to baseball than regular business.. Software tools including programming languages and something like an operating system have transformative applications.
sjg007 5y ago
Companies largely succeed despite themselves when they find product market fit.
edmundsauto 5y ago
Moneyball wasn't about finding OBP - it's about finding what helps teams win (not making outs, ~2001) and simultaneously undervalues. The key thing here is this is dynamic - baseball no longer undervalues OBP. Otherwise agree with what you say - some set math of Successful_Employee_Characteristics - What_FAANG_values, recalculated every couple of years, is how I would summarize the strategy.
908B64B197 5y ago
> So the question, which traits are analogous to on-base-percentage? Take the FAANG-hire-resume, then subtract features (e.g. lose the top-10 university credential, remove a couple years of experience, ditch the years with a trendy package, etc). Which decreases the hiring cost the most with the smallest loss of long-term value to the hiring company? What data set would track/measure this and what could be deployed as a proxy? The other question is: Why not simply match FAANG comp package by raising more money? I'm being 100% serious here. Software is pretty much the only field which can scale almost infinitely and the only cost really is compensation (Compared to salaries, MacBooks are almost free!). Think about it, 3x comp to get a 10x engineer? Worth it.

tialaramex 5y ago

> If non-FAANG companies compete for the same prospective employees as FAANG employees, they will lose to vastly superior compensation packages. Fair enough. Already this part is unclear. Baseball is different in another important respect: You have no choice about what you're doing. The Yankees, the As, anybody - is hiring you as, say, a pitcher. That's what you're good at, that's what you're doing. But I chose to work where I do now, for far less money (the people hiring weren't sure but they suspected the previous salary I listed, which was true, was more than the head of their entire 100+ person department, several steps above me on the hierarchy) because of what I do. What I do here makes a difference I care about, whereas say, working at an investment bank (as one of my ex-Google friends does) would not do anything except make rich people even richer. If you're a big deal maybe you can carve a niche so that whoever it is that hires you, they're really hiring you to do whatever it is you do anyway. I can't imagine Bjarne Stroustrup feels what he does (at ms.com ie Morgan Stanley) is mostly about making rich people richer, Morgan Stanley presumably mostly lets him get on with C++ stuff. Likewise hiring Linus Torvalds wouldn't redirect him from working on Linux. If that was going to happen it would have happened a decade or more ago. But for most of us in programming, where we work dictates what we do, and that influences whether I want a role I'm offered or not.

sjg007 5y ago
Hedge funds might be closer to baseball than regular business.. Software tools including programming languages and something like an operating system have transformative applications.

sjg007 5y ago

Companies largely succeed despite themselves when they find product market fit.

edmundsauto 5y ago

Moneyball wasn't about finding OBP - it's about finding what helps teams win (not making outs, ~2001) and simultaneously undervalues. The key thing here is this is dynamic - baseball no longer undervalues OBP. Otherwise agree with what you say - some set math of Successful_Employee_Characteristics - What_FAANG_values, recalculated every couple of years, is how I would summarize the strategy.

908B64B197 5y ago

> So the question, which traits are analogous to on-base-percentage? Take the FAANG-hire-resume, then subtract features (e.g. lose the top-10 university credential, remove a couple years of experience, ditch the years with a trendy package, etc). Which decreases the hiring cost the most with the smallest loss of long-term value to the hiring company? What data set would track/measure this and what could be deployed as a proxy? The other question is: Why not simply match FAANG comp package by raising more money? I'm being 100% serious here. Software is pretty much the only field which can scale almost infinitely and the only cost really is compensation (Compared to salaries, MacBooks are almost free!). Think about it, 3x comp to get a 10x engineer? Worth it.