> One man cannot ever get over a 10 foot wall. > Two men together can absolutely do it.

Sure. But the counter example (which is what I believe the article is arguing) is that one woman can make a baby in 9 months, but 9 women cannot together make a baby in one month.

Whether an organisation's "work capacity" is bottlenecked by things like gestation periods which cannot be circumvented, or things like 10 foot walls which can be cooperatively circumvented - is a great question though.

I think you bring a great point, creativity, ideation and making good decisions. More people means more ideas being bounced around, that could lead any one person to a solution which would have not happened otherwise.

But I think there's a cap to that as well, if you bring 10 people do they get over the 10 foot wall faster than 2 people would?

No they probably don't.

So from 1 to 2 you've got great added productivity, but at 10 you're majorly wasting resources.

That's where the other advice would kick in, getting over that wall won't get any faster, you can't scale beyond a point, unless you use other strategies:

1. Build better tools/frameworks, like say have a team build a ladder, now 1 person can get over the wall as fast as 2 people could prior.

2. Diversify your offering, have the other 8 work on other stuff that don't depend on getting over this wall.

I think that's all the ones mentioned on the article, but it be interesting to see if there could be more?

Now, maybe it takes 10 people to think about the problem of how to get over the 10 foot wall repeatedly and efficiently, at lower cost, for example to invent a ladder assuming ladder's didn't exist. I'll give you that, this is an interesting take.

But did it really take 10 people, or it's more that only 1 out of 10 people will come up with this great solution? And if so, you could find yourself adding 100 people with no one thinking of the solution and a competitor with only a single person might think of building a ladder. So what's the takeaway for scaling here?

I think the point is that these concerns are largely orthogonal. Work (equiv. labor), is the time/effort that your employees are devoting to your business processes. That work can be more or less productive as you say, or some part of the work could be devoted to making other kinds of work more productive. However it happens to be apportioned, there is some amount of time/effort that that work will take. The questions discussed in the essay are not about how to decide how to apportion the work. Instead, it's about issues that arise from coordinating that (predetermined amount of) work among N workers in a company. That's where you can have e.g. contention for shared resources or critical sequential segments.

What you're saying is like looking at Amdahl's law (mentioned in the essay) and saying "WTF? This is a bad way to think about parallelism, because what if I could just come up with a better algorithm?" Amdahl's law is not about choosing the right algorithm, it's about how much time you can save by parallelizing the algorithm you have. Clearly choosing the right algorithm is important, but it is a different kind of question.

The article is addressing a more fundamental point I think.

You cannot escape Little's Law for instance. You can change the variance but in the long run the average is what matters.

Yes, you can. The whole point of white collar work is to escape Little's Law. Automation, outsourcing, better processes etc..

So that's neat, but not what I was saying.

This is completely the wrong way to think about division of labour.

We started to figure this out 300 years ago for god's sake.

It's not helpful think about our tasks as a series of bits of work to be accomplished that we hire spigot-workers to do. White collar work is mostly not labour in that sense.

Thinking about your organization like a CPU doing calculations is utterly the wrong analogy.

More like band, playing a song - most tasks have some level of optimal participation you don't want to be below or over, and/or it might be incrementally harder to improve quality depending on variables. And 'talent' usually matters more than anything.

We started to figure this out 12,000+ years ago at the dawn of civilization, when specializations finally show up in the archeological records.

If you want to build a cart you need a woodworker and a couple of blacksmiths feeding your cartwright the proper materials. You’re right that five blacksmiths won’t get the cart built faster, but there’s a whole world of items, including in software, that are composites of anywhere from a handful to a hundred specialties.

I don’t feel like you’ve countered my theory about the need for higher order creation. Someone somewhere had to look at how many musical instruments there were in the world and think, “composer” and “conductor”, which not only gave you a job but suddenly put a bunch of musicians to work.

> You only get linearity if you discover the existing team is less capable than the newly added members

Could you explain your reasoning? This doesn't seem right to me. If you have linearity, this means that every new individual is exactly as productive as all other individuals

If you get twice as much work done by 10 people as 5, you need to think about what the new people brought to the table, or the old ones don’t.

If the team didn’t have a facilitator, for instance, some team members may not be coordinating, causing issues with finishing tasks.

Because despite having a factorial increase in communication paths, you still got twice as much done? Are you sure?

You have to ask these questions because at worst something bad is happening. At best someone new brought in new techniques that work better than your old ones. You need the answer in either case.

This doesn't make sense to me. Adding more people add communication overhead so you would get sub-linear return. I don't see how you can even expect more than linear return.