Computational Simulation of Distributed Work as a Discovery Tool for Envisioning Future Operations

Abstract

Envisioning new kinds of operations requires systematically developing architectures, work procedures, and artifacts to support human and machine agents in coordinating within dynamic environments. Accurately predicting how envisioned operations will unfold is challenging as (1) early design-phase descriptions of architectures, work procedures, and artifacts are often underspecified, and (2) key outcomes of interest emerge from interactions between cognitive work and environmental dynamics. This paper discusses how computational simulation of work can serve as a discovery tool for envisioning future operations. We introduce a three-phase approach using the Work Models that Compute (WMC) framework, which involves converting paper-based representations of work into computational models, developing scenarios and test conditions, and simulating work dynamics to analyze emergent behaviors. We illustrate this approach through a case study on developing contingency management procedures for envisioned air transport operations, specifically Urban Air Mobility (UAM). The case study demonstrates how computational simulation can (1) reveal the need for clearer design specifications, (2) uncover interactions and emergent behavior that may lead to undesirable outcomes, such as coordination surprises, and (3) identify trade-offs between multiple design options. Insight from simulation can complement other cognitive systems engineering methods to refine and enhance the feasibility and robustness of envisioned operations.