I liked the intriguing idea of how this article started but it did end on a cop-out, “now that I have suggested this phenomenon rather than understanding what causes it so that we can harness it in practice, I invite you (what must necessarily be the majority of my readership if the pattern holds true) to quit your jobs!”
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.
I suspect a big cause of nonlinear productivity effects like this is the experience and skills required to do the job.
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.
Perhaps it's a bit like traffic flow. Once you go beyond capacity, things slow down (productivity) but if you can offload some of the traffic load (to a low volume side street) the main highway becomes productive again.
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 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.