Builds on concepts from:

Summary: If you're trying to preserve your sanity (or your employees') by scaling back on the number of things you're trying to do... make sure not to accidentally scale back on things that were important-but-harder-to-see, in favor of things that aren't as important but more easily evaluated.

Epistemic Effort: Had a conversation, had some immediate instinctive reactions to it, did not especially reflect on it. Hope to flesh out how to manage these tradeoffs in the comments.

Zvi introduced the term "Slack" to the rationaljargonsphere a few months ago, and I think it's the most clearly useful new piece of jargon we've seen in a while.

Normally, when someone coins a new term, I immediately find people shoehorning it into conversations and concepts where it doesn't quite fit. (I do this myself an embarrassing amount, and the underlying motivation is clearly "I want to sound smart" which bodes ill).

By contrast, I experienced an explosion of people jargon-dropping Slack into their conversations and every single instance was valid. Lack-of-slack was a problem loads of people had been dealing with, and having a handle for it was a perfect instance of a new name enabling higher level discussion.

This hints at something that should be alarming: "slack" is a useful term because nobody has enough of it.

In particular, it looks like many organizations I'm familiar with run at something like -10% slack, instead of the 40% slack that apparently is optimal across many domains.

Gworley noted in the comments of Zvi's post:

If you work with distributed systems, by which I mean any system that must pass information between multiple, tightly integrated subsystems, there is a well understood concept of maximum sustainable load and we know that number to be roughly 60% of maximum possible load for all systems.

The probability that one subsystem will have to wait on another increases exponentially with the total load on the system and the load level that maximizes throughput (total amount of work done by the system over some period of time) comes in just above 60%. If you do less work you are wasting capacity (in terms of throughput); if you do more work you will gum up the works and waste time waiting even if all

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