A connection is traced from the informal policy maps of managers, to s
ome formal methods that have been reported for eliciting causal policy
maps from the minds of managers, to commercially available computer-d
riven methods for storing, displaying, and analyzing policy maps in a
group setting. A gap in available techniques for analyzing policy maps
is identified, and a path-finding algorithm built into an artificial
intelligence program is put forward as a step toward closing this gap.
It is used to demonstrate a causal-map analysis as an aid to a group
policy meeting.