Toward a normative theory of (self-)management by goal-setting

TL;DR

This paper develops a normative, resource-rational model for goal-setting in complex problem-solving, deriving optimal subgoals to enhance performance of bounded agents and humans, bridging theory and practical management strategies.

Contribution

It introduces a mathematically precise normative framework for goal-setting based on resource-rationality, linking cognitive models to practical recommendations.

Findings

Optimal subgoals improve problem-solving performance.

The model aligns with human goal pursuit mechanisms.

Grounds prescriptive management theories in computational cognitive models.

Abstract

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.