Price's Law: Why Only a Few People Generate Half of the Results
dariusforoux.com
dariusforoux.com
The guy recommending the bonus was bit generous (really good at attributing bonus to the person who put in the hard work barring other bias) and the guy handing out the bonus was the one who battled hard to reduce every bonus as the company had hired him to limit the unnecessary bonus to employees.
Every employee thought that he is the one fighting management to get them their bonus and got lots of love/respect and the generous guy got nothing.
It would be very interesting to work out a probability distribution f(r), 0 < r < ∞ support, such that when sampled N times independently half of the total sum is contained in the top √N terms. Like I would suspect it can be done with long-tailed distributions, though they might need to have an undefined cumulant or so... just that trying to set up that “sum of the top √N” integral sounds very tricky in a way that would foster some clever insight.
But of course the more likely explanation would probably have something to do with network effects. If you imagine that each person is a morphism (or a bounded number of morphisms?) in a category for example, perhaps whose objects are indirectly profit centers, then having N profit centers correlates to having N objects that your company relates, which correlates to N^2 employees connecting them together, so if the top 50% of profit resides in some fixed number of these objects, then only the ~N employees out of the ~N^2 who happen to deal with these “cash cows” would make up half of the profit. To detect this you would want to show that rather than linearly scaling with employees, the returns to scale might show a characteristic pattern of profit versus company size.
In the example cited, sales, the best salespeople have long-built networks of personal connections. That allows them to bring in deals that new people can’t access. It’s very different than retail work where it’s hard to greatly outperform your peers and little training is needed.
So agree models like this can be created but my feeling is the key aspects of the model relate to experience (related to your cash cow) rather than scale. At least for creative jobs.
That's to say, while not producing equally as high producers, the slackers do in a way help high producers produce in high volume by offloading some of the more interruptive tasks. Kind of like an executive needing an executive's assistant.
It's the same reason the myth of the 10x engineer is so popular. I've worked with some people who certainly thought they were the 10x engineer. As far as I could tell, they were just showboats who did highly visible work, leaving little things like technical debt for others. Or the "brilliant" engineer who make things that require high cognitive load to understand, instead of doing the extra work to make them clear. [1] Or who shirk the work of supporting colleagues and building strong teams.
So basically I think these are the people who optimize for the visible success metric, not the ones creating the most value.
[1] Just this week a friend took over responsibility for an internal build system. The previous author had written it in JavaScript. Except that he was really excited about functional languages, so he wrote it in a highly functional style incomprehensible to anybody not used to it. Now this either needs to be mostly rewritten or anybody who wants to work on the build system needs to spend 6 months learning Haskell first. I'm sure this guy looked productive and got to sound brilliant in meetings, but a better productivity analysis would include the significant costs he imposed on others.
I understood why people believe the "10x engineer" stories after meeting 0.1x engineers.
(And I don't mean juniors. I mean highly-paid consultants.)
"Work done" is certainly one component of having a much-cited paper; you are simply not going to have a relatively large number of cited papers if you have not written a relatively large number of papers. But there's the question of what other factors lead papers to awareness, recognition of value, and citation, and those questions likely don't have a linear relationship with "value created."
Given the description of some of the dynamics involved as a "preferential attachment process" involving "cumulative advantage" (https://en.wikipedia.org/wiki/Preferential_attachment ), Price seems to have recognized this and probably had a different conception than the author of the piece we're discussing.
(Peterson, who the author indicates brought Price's law to his attention, seems to recognize this as well, and sometimes suggests that it's best to assume that people who aren't at the top of some Pareto distribution "P" in contributing value are probably contributing value in some other way that isn't visible to people focusing on P. )
Price's law doesn't fit the data. (DOI 10.1016/0306-4573(88)90049-0)
It certainly shouldn't be randomly reapplied to things besides scientific publication. Even within scientific publication, the uneven distribution of publications is a result of far more complicated mechanisms than some simple measure of results. Remember, by bibliometric methods, Newton, Feynman, and Perelman are some of the lowest performers ever to work in science.
The marginal utility of hiring additional workers in an organization is smaller for each additional employee. This is both obvious, and completely accounts for the effect on its own.
One of Peterson’s main arguments is about college campuses and politics. But 85% of HARD scientists - who have nothing to do with politics - are liberals (2015 AAAS poll). That argues that smart people like those at universities see through right wing propaganda - they’ve read Orwell and Arendt and Altemeyer and John Dean and “Manufacturing Consent” and understand how propaganda works.
Peterson is toxic and definitely not an intellectual model.
If we're talking intellectual models, I doubt people are going to be impressed by that approach.
Since we're here, though, I'm interested in evidence that Peterson is on the fringes of Psychology (the WaPo link does not make that case; it's not even clear it's a criticism of Peterson, though it arguably damns with faint praise). I think he and his audiences could use more good critics.
Reading liberal arts is right up there with reading bondage magazine monthly in terms of popularity and taboo.
The definition of liberal is much closer to libertarian. I've never heard people make a defense of pedophilia in public outside of a lab at 8pm when all the normal people have left.
Working with that 85% of "HARD scientists", yeah, they're mostly pretty liberal, but they're just as likely to spout off horrible conspiracy theories and assume all conservatives are backwater inbreds as anyone else. That bias is supremely real, and it's not because scientists have a magical, rational filter against propaganda.
Another good source is Josh Greene’s book on Bannon. That book describes how Bannon used GOP billionaire money (Mercer) to intentionally try to radicalize young tech-savvy men for the conservative cause. Bannon realized (and Prager around the same time) that with some propaganda he could persuade young mostly-white men to vote for the pro-billionaire agenda of the Republicans.
I won’t say more here to avoid getting into politics on HN. But check out those sources for more info.
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On the the square root phenomenon, I wonder whether this arises due to the experience required to be very productive at creative work. Factory workers have little ability to be twice as productive as their peers. But the best salespeople and programmers can easily be many times as productive as at the entry-level. There’s a nonlinear function of experience and skills.
I bet one could build some automata/stat mech type models of this. (And it’s not even clear you need to care about interactions). See if nonlinearities in productivity as a function of experience (and as importantly, luck- and maybe talent) hold in soft fields and creative fields.