Conversation

When a traditional org gets overwhelmed, people fall behind on email, and do the right thing late enough that it becomes the wrong thing When an open network org gets overwhelmed, people start dropping information, and do whatever part of the right thing they they can, on time.
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Imagine a stream of flowing information that everybody needs to fully process within a fixed time, say 24h, to do a project. Now imagine 2 failure modes: a) everybody delayed to by +T on every message b) everybody in Lucy mode: keeping up X%, but dropping 100-X% the messages
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The +T likely compounds in dependent sequences +T, +2T, +3T etc. I gotta think about how to model this properly. The problem I’m interested in framing is: what sorts of projects degrade better under delay vs drops? And how do you mitigate each?
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I *think* redundant comms and embarrassingly parallel actions address droppy/lossy processing vs delayed. In human projects this means repeating yourself a lot, and redundant staffing. Fo delay, you just add time. If cost of adding enough time exceeds value of project, kill it.
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