Title:
Towards a Methodology for the Definition and Evaluation of Enterprises through Modeling and Simulation: Application to Product Development

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Capgemini_Scitech_Paper_final.pdf (2.1 MB)
Author(s)
Mueller, Sean Ryan
 Pinon Fischer, Olivia J.
 Bagdatli, Burak
 Cimtalay, Selcuk
 Mavris, Dimitri N.
 Faveto, Alberto
 Boulbene, Benjamin
 Mazzoldi, Antonio
 Croue, Nicolas
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Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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https://hdl.handle.net/1853/77075
Abstract
Enterprises today have to navigate a rapidly evolving landscape driven by technological advancements, intensifying global competition, and shifting market dynamics. To remain competitive, organizations must adopt agile and digital solutions that enhance operational efficiency, optimize processes, and accelerate time-to-market. This research introduces a comprehensive methodology designed to evaluate enterprise performance across a variety of scenarios, with a specific focus on product development processes. The proposed methodology rests on three pillars: modeling, simulation, and their integration. Leveraging Model-based Systems Engineering (MBSE) and the Unified Architecture Framework (UAF), the methodology provides a structured approach to model organizational elements such as processes, resources (tools, personnel), and goals, establishing a cohesive enterprise architecture. A holistic agent based simulation facilitates a granular analysis of the enterprise operations. The simulation captures dynamic interactions and emergent behaviors, enabling quantitative evaluations of the individual impacts of digital tools, processes and human resources on organizational outcomes. The seamless integration between the modeling and simulation environments is ensured through the use of a centralized Authoritative Source of Truth (ASOT), maintaining consistency and traceability. This end-to-end approach enables scenario-based assessments and quantitative evaluations of alternative configurations, addressing the limitations of traditional EAframeworks by capturing dynamic interactions and emergent behaviors. This methodology therefore lays the groundwork for the further development of Digital Twins of Organizations (DTOs), one that facilitates strategic decision-making and optimization in complex enterprise environments.
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2025-01
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