I mused about this yesterday and scribbled some thoughts on it on Twitter here.
“When should you pool all resources into your current best bet vs spread them across N ~independent parallel plans each of which will have lower probability of success?”
Investing marginal resources (workers, in this case) into your single most promising approach might have diminishing returns due to A) limited low-hanging fruits for that approach, B) making it harder to coordinate, and C) making it harder to think original thoughts due to rapid internal communication & Zollman effects. But marginal investment may also have increasing returns due to D) various scale-economicsy effects.
There are many more factors here, including stuff you mention. The math below doesn’t try to capture any of this, however. It’s supposed to work as a conceptual thinking-aid, not something you’d use to calculate anything important with.
A toy-model heuristic is to split into N separate approaches iff the extra independent chances counterbalance the reduced probability of success for your top approach.
One observation is that the more dependent/serial steps (k) your plan has, the more it matters to maximise general efficiencies internally (c), since that gets exponentially amplified by k.[1]
You can view this as a special case of Ahmdal’s argument. If you want. Because nobody can stop you, and all you need to worry about is whether it works profitably in your own head.
I mused about this yesterday and scribbled some thoughts on it on Twitter here.
Investing marginal resources (workers, in this case) into your single most promising approach might have diminishing returns due to A) limited low-hanging fruits for that approach, B) making it harder to coordinate, and C) making it harder to think original thoughts due to rapid internal communication & Zollman effects. But marginal investment may also have increasing returns due to D) various scale-economicsy effects.
There are many more factors here, including stuff you mention. The math below doesn’t try to capture any of this, however. It’s supposed to work as a conceptual thinking-aid, not something you’d use to calculate anything important with.
A toy-model heuristic is to split into N separate approaches iff the extra independent chances counterbalance the reduced probability of success for your top approach.
One observation is that the more dependent/serial steps (k) your plan has, the more it matters to maximise general efficiencies internally (c), since that gets exponentially amplified by k.[1]
You can view this as a special case of Ahmdal’s argument. If you want. Because nobody can stop you, and all you need to worry about is whether it works profitably in your own head.