Let’s start with a few examples of very common real-world coordination problems.
The marketing department at a car dealership posts ads for specific cars, but the salespeople don’t know which cars were advertised, causing confusion when a customer calls in asking about a specific car. There’s no intentional information-hoarding, it’s just that the marketing and sales people don’t sit next to each other or talk very often. Even if the info were shared, it would need to be translated to a format usable by the salespeople.
Various hard problems in analysis of large-scale biological data likely have close analogues in econometrics. The econometricians have good methods to solve the problems, and would probably be quite happy to apply those methods to biological data, and the bio experimentalists would love some analytic help. But these people hardly ever talk to each other, and use different language for the same things anyway.
When the US invaded Grenada in the ’80’s, the marines occupied one side of the island and the army occupied the other. Their radios were not compatible, so if an army officer needed to contact their counterpart in the marines, they had to walk to the nearest pay phone and get routed through Fort Bragg on commercial telephone lines.
Various US intelligence agencies had all of the pieces necessary to stop the 9/11 attacks. There were agencies which knew something was planned for that day, and knew who the actors were. There were agencies which knew the terrorists were getting on the planes. There were agencies which could have moved to stop them, but unfortunately the fax(!) from the agencies which knew what was happening wasn’t checked in time.
There are about 300 million people in the US. If I have a small company producing doilies, chances are there are plenty of people in the US alone who’d love my doilies and be happy to pay for them. But it’s hard to figure out exactly which people those are, and even once that’s done it’s hard to get them a message showing off my product. And even if all that works out, if the customers really want a slightly different pattern, it’s hard for them to communicate back to me what they want—even if I’d be happy to make it.
So coordination problems are a constraint to production of all kinds of economic value. How taut are those constraints?
Well, let’s look at the market price of relaxing coordination constraints. In other words: how much do people/companies get paid for solving coordination problems?
When I think of people whose main job is to solve coordination problems, here are some occupations which spring to mind:
Entrepreneurs’ main job is to coordinate salespeople, engineers, designers, marketers, investors, customers, regulators, suppliers, shippers, etc…
Managers’ main job is to coordinate between their bosses, underlings, and across departments
Investment bankers coordinate between investors, companies, lawyers, and a huge number of people within each of those organizations
Real estate developers coordinate between builders, landowners, regulators, renters, and investors
Note that all of these are occupations typically associated with very high pay. Even more to the point: within each of these occupations, people who solve more complicated coordination problems (e.g. between more people) tend to make more money. Even at the small end, the main difference between an employee and a freelancer is that the freelancer has to solve their own coordination problem (i.e. find people who want their services); freelancers make lots of money mainly when they are very good at solving this problem.
Similarly with companies. If we go down the list of tech unicorns, most (though not all) of them solve coordination problems as their primary business model:
Google matches company websites to potentially interested users
Facebook is a general-purpose coordination platform
Amazon and Ebay are general-purpose marketplaces: they match buyers to sellers
Uber/Lyft are more specialized marketplaces
Again: solving coordination problems at scale offers huge amounts of money.
This suggests that coordination problems are very taut constraints in today’s economy.
It’s not hard to imagine why coordination problems would be very taut today. Over the past ~50 years, global travel/transportation has gone from rare to ordinary, and global communication has become cheap and ubiquitous. Geographical constraints have largely been relaxed, and communication/information processing constraints have largely been relaxed. The number of people we could potentially coordinate with has expanded massively as a result—a small doily business can now sell to a national or even global customer base; a phone app can connect any willing driver in a city to any paying rider.
Yet human brains have not changed much, even as the number of people we interact with skyrockets past Dunbar’s number. It’s hard for humans to coordinate with thousands—let alone billions—of other humans. The coordination constraint remains, so as other constraints relax, it becomes more taut.
What Would This Model Predict?
One prediction: suppose I’ve decided to become a freelancer/consultant. I can invest effort in becoming better at my object-level craft, or I can invest effort in becoming better at solving my coordination problem—e.g. by exploring marketing channels or studying my target market. Which of these will make more money? Probably the latter—coordination constraints are very taut, so there’s lots of money to be made by relaxing them.
More generally, when evaluating new business ideas, questions on my short list include:
How will this business find people who would want to buy the product?
How will this business make those people aware of the product?
To the extent that coordination is an unusually taut constraint, answers to these questions will be the main determinant of business profitability—even more so than product quality.
Coming from a different direction, when considering a business idea we should ask how many different kinds of people this business needs to coordinate. At one point I worked at a mortgage startup, where the list of internal departments included marketing, sales, underwriting, legal, and capital markets on the mortgage side, plus design, engineering, and ops on the tech side, and on top of that we had to interface to at least a dozen external companies on a regular basis. Coordination is the primary constraint at a company like that.
Yet another direction: if coordination constraints are very taut, then we expect adoption of technology which makes coordination easier. One form of this is outlined in From Personal to Prison Gangs: people make themselves easier to coordinate with, by following standardized patterns of behavior and fitting into standard molds. For instance, in large organizations (where more people need to coordinate) we tend to see group-based identity: rather than understanding what John or Allan does, people understand what lawyers or developers do. Interactions between people become more standardized, and roles more rigid—these are solutions to coordination problems. Such solutions entail large tradeoffs, but coordination constraints are very taut, so large tradeoffs are accepted.
Conversely, if we want a world with less pressure to standardize behavior, then we need some other way to relax coordination constraints—some technology which helps people coordinate at scale without needing to standardize behavior as much. Such technology would probably see wide adoption, and potentially make quite a lot of money as well.
Summary
I often hear people they’d like object-level skill/effort to be rewarded more than marketing/sales, or they’d like to see less pressure to standardize behavior, or they’d like the world to be more individualized and identity to be less group-based. To the extent that we buy the picture here, all of these phenomena are solutions to coordination problems. Society rewards marketing over object-level skill, and tries to standardize behavior, because coordination constraints are extremely taut.
If we want the world to look less like that, then we need alternative scalable technologies to solve coordination problems.
Coordination as a Scarce Resource
Let’s start with a few examples of very common real-world coordination problems.
The marketing department at a car dealership posts ads for specific cars, but the salespeople don’t know which cars were advertised, causing confusion when a customer calls in asking about a specific car. There’s no intentional information-hoarding, it’s just that the marketing and sales people don’t sit next to each other or talk very often. Even if the info were shared, it would need to be translated to a format usable by the salespeople.
Various hard problems in analysis of large-scale biological data likely have close analogues in econometrics. The econometricians have good methods to solve the problems, and would probably be quite happy to apply those methods to biological data, and the bio experimentalists would love some analytic help. But these people hardly ever talk to each other, and use different language for the same things anyway.
When the US invaded Grenada in the ’80’s, the marines occupied one side of the island and the army occupied the other. Their radios were not compatible, so if an army officer needed to contact their counterpart in the marines, they had to walk to the nearest pay phone and get routed through Fort Bragg on commercial telephone lines.
Various US intelligence agencies had all of the pieces necessary to stop the 9/11 attacks. There were agencies which knew something was planned for that day, and knew who the actors were. There were agencies which knew the terrorists were getting on the planes. There were agencies which could have moved to stop them, but unfortunately the fax(!) from the agencies which knew what was happening wasn’t checked in time.
There are about 300 million people in the US. If I have a small company producing doilies, chances are there are plenty of people in the US alone who’d love my doilies and be happy to pay for them. But it’s hard to figure out exactly which people those are, and even once that’s done it’s hard to get them a message showing off my product. And even if all that works out, if the customers really want a slightly different pattern, it’s hard for them to communicate back to me what they want—even if I’d be happy to make it.
So coordination problems are a constraint to production of all kinds of economic value. How taut are those constraints?
Well, let’s look at the market price of relaxing coordination constraints. In other words: how much do people/companies get paid for solving coordination problems?
When I think of people whose main job is to solve coordination problems, here are some occupations which spring to mind:
Entrepreneurs’ main job is to coordinate salespeople, engineers, designers, marketers, investors, customers, regulators, suppliers, shippers, etc…
Managers’ main job is to coordinate between their bosses, underlings, and across departments
Investment bankers coordinate between investors, companies, lawyers, and a huge number of people within each of those organizations
Real estate developers coordinate between builders, landowners, regulators, renters, and investors
Note that all of these are occupations typically associated with very high pay. Even more to the point: within each of these occupations, people who solve more complicated coordination problems (e.g. between more people) tend to make more money. Even at the small end, the main difference between an employee and a freelancer is that the freelancer has to solve their own coordination problem (i.e. find people who want their services); freelancers make lots of money mainly when they are very good at solving this problem.
Similarly with companies. If we go down the list of tech unicorns, most (though not all) of them solve coordination problems as their primary business model:
Google matches company websites to potentially interested users
Facebook is a general-purpose coordination platform
Amazon and Ebay are general-purpose marketplaces: they match buyers to sellers
Uber/Lyft are more specialized marketplaces
Again: solving coordination problems at scale offers huge amounts of money.
This suggests that coordination problems are very taut constraints in today’s economy.
It’s not hard to imagine why coordination problems would be very taut today. Over the past ~50 years, global travel/transportation has gone from rare to ordinary, and global communication has become cheap and ubiquitous. Geographical constraints have largely been relaxed, and communication/information processing constraints have largely been relaxed. The number of people we could potentially coordinate with has expanded massively as a result—a small doily business can now sell to a national or even global customer base; a phone app can connect any willing driver in a city to any paying rider.
Yet human brains have not changed much, even as the number of people we interact with skyrockets past Dunbar’s number. It’s hard for humans to coordinate with thousands—let alone billions—of other humans. The coordination constraint remains, so as other constraints relax, it becomes more taut.
What Would This Model Predict?
One prediction: suppose I’ve decided to become a freelancer/consultant. I can invest effort in becoming better at my object-level craft, or I can invest effort in becoming better at solving my coordination problem—e.g. by exploring marketing channels or studying my target market. Which of these will make more money? Probably the latter—coordination constraints are very taut, so there’s lots of money to be made by relaxing them.
More generally, when evaluating new business ideas, questions on my short list include:
How will this business find people who would want to buy the product?
How will this business make those people aware of the product?
To the extent that coordination is an unusually taut constraint, answers to these questions will be the main determinant of business profitability—even more so than product quality.
Coming from a different direction, when considering a business idea we should ask how many different kinds of people this business needs to coordinate. At one point I worked at a mortgage startup, where the list of internal departments included marketing, sales, underwriting, legal, and capital markets on the mortgage side, plus design, engineering, and ops on the tech side, and on top of that we had to interface to at least a dozen external companies on a regular basis. Coordination is the primary constraint at a company like that.
Yet another direction: if coordination constraints are very taut, then we expect adoption of technology which makes coordination easier. One form of this is outlined in From Personal to Prison Gangs: people make themselves easier to coordinate with, by following standardized patterns of behavior and fitting into standard molds. For instance, in large organizations (where more people need to coordinate) we tend to see group-based identity: rather than understanding what John or Allan does, people understand what lawyers or developers do. Interactions between people become more standardized, and roles more rigid—these are solutions to coordination problems. Such solutions entail large tradeoffs, but coordination constraints are very taut, so large tradeoffs are accepted.
Conversely, if we want a world with less pressure to standardize behavior, then we need some other way to relax coordination constraints—some technology which helps people coordinate at scale without needing to standardize behavior as much. Such technology would probably see wide adoption, and potentially make quite a lot of money as well.
Summary
I often hear people they’d like object-level skill/effort to be rewarded more than marketing/sales, or they’d like to see less pressure to standardize behavior, or they’d like the world to be more individualized and identity to be less group-based. To the extent that we buy the picture here, all of these phenomena are solutions to coordination problems. Society rewards marketing over object-level skill, and tries to standardize behavior, because coordination constraints are extremely taut.
If we want the world to look less like that, then we need alternative scalable technologies to solve coordination problems.