Optimization of decision networks in structured task environments

This paper considers the problem of determining the optimal distributed decision strategy for a team of decision-makers (DMs) arranged in an arbitrary acyclic organizational structure and controlling a complex structured process. Each DM has access to uncertain and partial information about the task environment and can control only a portion of it. We present an influence diagram model of the joint task-organization system and formulate the optimal team strategy in terms of a set of coupled hypothesis testing tasks at DMs. Specifically, we show that the scope of a local decision task is determined by the interaction of the task structure (what can be measured) and of the information access structure of the organization (who can measure what); while the control structure (who can influence what event) has an impact on the locally perceived costs associated with the decision options available. Theoretical results are illustrated via a numerical example, and connections to existing decision models are discussed.