A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design

Abstract

We present a principal-agent model of a one-shot, shallow, systems engineering process. The process is "one-shot" in the sense that decisions are made during one time step and that they are final. The term "shallow" refers to a one-layer hierarchy of the process. Specifically, we assume that the systems engineer has already decomposed the problem in subsystems, and that each subsystem is assigned to a different subsystem engineer. Each subsystem engineer works independently to maximize their own expected payoff. The goal of the systems engineer is to maximize the system-level payoff by incentivizing the subsystem engineers. We restrict our attention to requirement-based systemlevel payoffs, i.e., the systems engineer makes a profit only if all the design requirements are met. We illustrate the model using the design of an Earth-orbiting satellite system where the systems engineer determines the optimum incentive structures and requirements for two subsystems: the propulsion subsystem and the power subsystem. The model enables the analysis of a systems engineer's decisions about optimal passed-down requirements and incentives for sub-system engineers under different levels of task difficulty and associated costs. Sample results, for the case of risk-neutral systems and subsystems engineers, show that it is not always in the best interest of the systems engineer to pass down the true requirements. As expected, the model predicts that for small to moderate task uncertainties the optimal requirements are higher than the true ones, effectively eliminating the probability of failure for the systems engineer. In contrast, the model predicts that for large task uncertainties the optimal requirements should be smaller than the true ones in order to lure the subsystem engineers into participation.

Toward a Theory of Systems Engineering Processes: A Principal–Agent Model of a One-Shot, Shallow Process

“…Our study does not examine all possible combinations of cost, quality, and utility functions that could have been considered. Indeed, as we showed in our previous work [10], there are situations in which a smaller-than-the-true requirement can be optimal. 2) Moral hazard with RPI transfer and value functions: This case is identical to Sec.…”

“…III. As we have shown in earlier work [10], the optimal passed-down requirement differs from the true system requirement. For example, the SE should ask for higher requirements for the design task with low-complexity.…”

“…In the field, the reward could be explicitly implemented as an annual performance-based bonus, or, as it is the case most often, it could be implicitly encoded in expectations about job security, promotion, professional reputation, etc. To capture the human aspect in SEPs, one possible way is one needs to follow a game-theoretic approach [9], [10]. Most generally, the SEP should can be modeled as a dynamical hierarchical network game with incomplete information.…”