This sounds interesting and relevant. Here's my input: I read this back in 2008 and I am summarising it from memory, so I may make a few factual errors. But I read that one of the problem facing large Internet companies like Google is the size of their server farms, which need cooling, power, space, etc. Optimising the algorithms used can help enormously. A particular program was responsible for allocating system resources so that the systems which were operating were operating at near full capacity, and the rest could be powered down to save energy. Unfortunately, this program was executed many times a second, to the point where the savings it created were much less than the power it used. The fix was simply to execute it less often. Running the program took about the same amount of time no mater how many inefficiencies it detected, so it was not worth checking the entire system for new problems if you only expected to find one or two.

My point: To reduce resources spent on decision-making, make bigger decisions but make them less often. Small problems can be ignored fairly safely, and they may be rendered irrelevant once you solve the big ones.

I was having similar thoughts the other day while watching a reality TV show where designers competed for a job from Philippe Starck. Some of them spent ages trying to think of a suitable project, and then didn't have enough time to complete it; some of them launched into the first plan they had and it turned out rubbish. Clearly they needed some meta-planning. But how much? Well, they'll need to do some meta-meta planning...

I'd be happy to give your post a read through.

ETA: The buck stops immediately, of course.

Upvoted for importance of subject - looking forward to the post. Have you read up on Information Foraging?