Quality Management, Information Prediction, and Pre-Optimized Resource Networks

One of the problems of this information-chocked world is that answer-seeking becomes too quick to be well-refined. Artificial Intelligence pioneer Herbert Simon explains this problem very well with his term “Satisfice”.

Satisfice: a hybrid word formed from satisfy and suffice, referring to the tendency of time-starved, information-overloaded users to select the first good-enough solution that crosses their path. Users often use satsificing as a triage strategy, based on the time and effort a more comprehensive search might entail.

How does one avoid making mediocre choices due to last-minute information needs? The solution is to predict what future information will be needed, and then create networks of experts based on those future needs.

Where to start?

  • A good place is Linkedin.com Answers (when people you don’t know answer your questions well, add them to your network).
  • Facebook notes (tag friends in a note and ask for experts, blog reccommendations, and books).

In this way, your network researches for you en masse, and you can simply wait for the information to return. In the future, your network may rely on you for your specific expertise in order to avoid their own Satisfice on the subject.

Definition of Satisfice taken from Bob Goodman’s Usability Glossary.

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