Analytic model driven organizational design and experimentation in adaptive command and control

The purpose of this article is to present a methodology for organizational design, as well as to provide guidelines for the design of experiments to examine organizational behavior of command and control teams operating in a complex mission environment. We begin by describing the process of developing a quantitative model of a mission and of the concomitant organization tasked to execute the mission. The hypotheses, to be tested experimentally, are expressed via equations involving the model variables; they provide the criteria for organizational design. We present a multi‐objective design process to generate a set of organizational architectures to test the hypotheses. The underlying model is used to provide quantitative predictions of organizational performance. We discuss the model‐driven tuning of experimental parameters to amplify the performance differences among distinct organizational designs. The structural diversity of the generated architectures and the variety of performance measures from the models, coupled with experimental data, provide the basis for validating or rejecting the original hypotheses, for identifying human limitations and biases, and for formulating new hypotheses. We also discuss the software implementation of the above steps that not only automates the design process, but also presents the Command and Control (C2) researchers a tool for generating new measures and hypotheses. The methodology presented in this paper can be used to design an executable model for human‐in‐the‐loop model‐based experiments that provide the necessary empirical components for current and future research in adaptive C2 architectures. We illustrate our organizational design process via a joint‐task‐force scenario as operationalized on the distributed dynamic decision‐making team‐in‐the‐loop simulator, the DDD‐III. The methodology and the software environment introduced constitute valuable instruments for scientific research in the area of organizational decision‐making and human team behavior. © 1999 John Wiley & Sons, Inc. Syst Eng 2: 78–107, 1999