My argument for why treating a company as a coherent entity[1] is not that crazy:
I think if you want a simple model of what a company is likely to do, modeling it as an profit-maximizing agent with certain resources at its disposal gives you pretty good predictions.
Sometimes you can do more. If you have a a few more sentences and want to dive into empirical divergences, then adding additional sentences about the company’s character: “This company’s leftist, so you should expect them to take actions in accordance to being leftist.” [2] Or “this company’s big into ESG” or “This company has sclerotic decision-making processes” or “this company’s slow to adapt” gives you additional useful predictions.
It’s possible to do better by modeling the company in more detail and not as a coherent entity. For example, rather to tease out the relevant principal-agent dynamics, or various sub-coalitions in the company. Or by assessing the divergences from “rationality” by looking at specific character traits of the CEO or other important individuals.
But this is a) much harder to do (and a less parsimonious model), and b) does not obviously yield better predictions in practice, a lot of the time.
[1] This is taking the “intentional stance” approach to companies. To be clear, I don’t think you should use this for all collections of individuals. Eg, this type of coherence would be a poor model for social classes, and a very poor model for people sharing an astrological sign. States are somewhere in between.
[2] I’m uncertain how much you can get from this beyond “profit-maximizing institution plus noise” but I do think “how has this company diverged from simple profit-maximizing in the past” probably gives you better predictions on net for “how will this company diverge from profit-maximizing in the future” than, e.g., trying to suss out details about CEO character.
maybe i spend too much time inside the company and not enough time inside the set of people with the same astrological sign, but it feels to me like companies are often defined by a “vibe”, and that vibe happens to have been selected for profit maximizingness in the past (because if that vibe always sucks at profit it will go bankrupt), and companies will try to correct the vibe if they are obviously failing at maximizing profit, but most day to day decisions are guided by some mix of that vibe and a bunch of subagents that do random shit, and course correcting is really really fucking hard. i can easily think of half a dozen examples of companies being poorly described as primarily profit-maximizing with some minor divergences. google is a fountain of money with an AGI lab attached, and also a bunch of random side projects bolted on because doing a side project is good for your promo packet. meta is zuck’s personal kingdom and reflects his taste in exciting new directions. quant firms are basically statistical analysis firms that thumb their noses at deep learning. kodak was a film company that forgot to notice this was no longer a profitable vibe. ibm is a mainframe company that forgot to pivot into newer kinds of computers and is now desperately trying to pretend to be relevant in AI. tsmc is an ultra conservative fab company that has seen countless fads rise and fall and is scared to make big bets.
My argument for why treating a company as a coherent entity[1] is not that crazy:
I think if you want a simple model of what a company is likely to do, modeling it as an profit-maximizing agent with certain resources at its disposal gives you pretty good predictions.
Sometimes you can do more. If you have a a few more sentences and want to dive into empirical divergences, then adding additional sentences about the company’s character: “This company’s leftist, so you should expect them to take actions in accordance to being leftist.” [2] Or “this company’s big into ESG” or “This company has sclerotic decision-making processes” or “this company’s slow to adapt” gives you additional useful predictions.
It’s possible to do better by modeling the company in more detail and not as a coherent entity. For example, rather to tease out the relevant principal-agent dynamics, or various sub-coalitions in the company. Or by assessing the divergences from “rationality” by looking at specific character traits of the CEO or other important individuals.
But this is a) much harder to do (and a less parsimonious model), and b) does not obviously yield better predictions in practice, a lot of the time.
[1] This is taking the “intentional stance” approach to companies. To be clear, I don’t think you should use this for all collections of individuals. Eg, this type of coherence would be a poor model for social classes, and a very poor model for people sharing an astrological sign. States are somewhere in between.
[2] I’m uncertain how much you can get from this beyond “profit-maximizing institution plus noise” but I do think “how has this company diverged from simple profit-maximizing in the past” probably gives you better predictions on net for “how will this company diverge from profit-maximizing in the future” than, e.g., trying to suss out details about CEO character.
maybe i spend too much time inside the company and not enough time inside the set of people with the same astrological sign, but it feels to me like companies are often defined by a “vibe”, and that vibe happens to have been selected for profit maximizingness in the past (because if that vibe always sucks at profit it will go bankrupt), and companies will try to correct the vibe if they are obviously failing at maximizing profit, but most day to day decisions are guided by some mix of that vibe and a bunch of subagents that do random shit, and course correcting is really really fucking hard. i can easily think of half a dozen examples of companies being poorly described as primarily profit-maximizing with some minor divergences. google is a fountain of money with an AGI lab attached, and also a bunch of random side projects bolted on because doing a side project is good for your promo packet. meta is zuck’s personal kingdom and reflects his taste in exciting new directions. quant firms are basically statistical analysis firms that thumb their noses at deep learning. kodak was a film company that forgot to notice this was no longer a profitable vibe. ibm is a mainframe company that forgot to pivot into newer kinds of computers and is now desperately trying to pretend to be relevant in AI. tsmc is an ultra conservative fab company that has seen countless fads rise and fall and is scared to make big bets.