  The design and operation of systems are conventionally viewed as a sequential
decision-making process that is informed by data from physical experiments and
simulations. However, the integration of these high-dimensional and
heterogeneous data sources requires the consideration of the impact of a
decision on a system's remaining life cycle. Consequently, this introduces a
degree of complexity that in most cases can only be solved through an
integrated decision-making approach. In this perspective paper, we use the
digital twin concept to formulate an integrated perspective for the design of
systems. Specifically, we show how the digital twin concept enables the
integration of system design decisions and operational decisions during each
stage of a system's life cycle. This perspective has two advantages: (i)
improved system performance as more effective decisions can be made, and (ii)
improved data efficiency as it provides a framework to utilize data from
multiple sources and design instances. From the formal definition, we identify
a set of eight capabilities that are vital constructs to bring about the
potential, as defined in this paper, that the digital twin concept holds for
the design of systems. Subsequently, by comparing these capabilities with the
available literature on digital twins, we identify a set of research questions
and forecast what their broader impact might be. By conceptualizing the
potential that the digital twin concept holds for the design of systems, we
hope to contribute to the convergence of definitions, problem formulations,
research gaps, and value propositions in this burgeoning field. Addressing the
research questions, associated with the digital twin-inspired formulation for
the design of systems, will bring about more advanced systems that can meet
some of the societies' grand challenges.

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