  People are often confronted with problems whose complexity exceeds their
cognitive capacities. To deal with this complexity, individuals and managers
can break complex problems down into a series of subgoals. Which subgoals are
most effective depends on people's cognitive constraints and the cognitive
mechanisms of goal pursuit. This creates an untapped opportunity to derive
practical recommendations for which subgoals managers and individuals should
set from cognitive models of bounded rationality. To seize this opportunity, we
apply the principle of resource-rationality to formulate a mathematically
precise normative theory of (self-)management by goal-setting. We leverage this
theory to computationally derive optimal subgoals from a resource-rational
model of human goal pursuit. Finally, we show that the resulting subgoals
improve the problem-solving performance of bounded agents and human
participants. This constitutes a first step towards grounding prescriptive
theories of management and practical recommendations for goal-setting in
computational models of the relevant psychological processes and cognitive
limitations.
