An investigation on requirement and objective allocation strategies using a principal–agent model. Issue 1 (10th October 2019)

• Record Type: Journal Article
• Authors: Vermillion, Sean D.; Malak, Richard J.
• Is Part Of: Systems engineering. Volume 23:Issue 1(2020)
• Page Start: 100
• Page End: 117
• Publication Date: 2019-10-10
• Subjects: delegation -- principal–agent -- requirement allocation -- value‐driven design; Systems engineering -- Periodicals; 620.0011
• DOI: 10.1002/sys.21511
• Languages: English
• ISSNs: 1098-1241

Abstract

Abstract: In this paper, we investigate the dichotomy between system design delegation driven by requirement allocation and delegation driven by objective allocation. Specifically, we investigate this dichotomy through the lens of agency theory, which addresses cases where an agent makes decisions on behalf of another, that is, a principal. In current practice, design delegation largely involves requirement allocation as a means to inform agents of the desirable system characteristics. The value‐driven design paradigm proposes replacing requirements with objective, or trade‐off, functions to better guide agents toward optimal systems. We apply and adapt the principal–agent mathematical model to the design delegation problem to determine if a principal, that is, the delegator, should communicate using requirements or objectives with her agent. In this model, we assume the case of a single principal and single agent where the agent has certain domain knowledge the principal does not have and the agent accrues costs while solving a delegated design problem. Under the assumptions of the mathematical model, we show that the requirement allocation paradigm can yield greater value to the principal over objective despite limitations requirement allocation places on the principal to learn information from the agent. However, relaxing model assumptions can impact the value proposition of requirement allocation in favor of objective allocation. Therefore, a resolution to the requirement–objective dichotomy may be context dependent. The results and the analytical framework used to derive them provide a new, foundational perspective with which to investigate allocation strategies.