As the Metaverse and other virtual reality worlds grow in popularity, they are increasingly populated by virtual avatars. These digital representations are unique and personal, becoming an extension of the user and replicating their real-time movements in the virtual world. Though driven by an actual person, these avatars are not bound by the restrictions of reality. In VR, we can fly, travel to another world, or even get a tattoo without worrying about the consequences!
Developing technology now allows us Supply Chain Managers to create avatar-like versions of our own businesses and processes. We call these virtual replicas digital twins. These digital twins are virtual models of a physical object, process, or system intricately crafted using real-time data and sophisticated modeling techniques. In the dynamic world of Supply Chain and Operations Management (SCOM), digital twins have emerged as a game-changing innovation that promises to revolutionize how organizations visualize, analyze, and optimize their operations.
While digital twins are being applied in various industries as digital replicas of products and processes, their role in SCOM goes beyond mere simulation; they are powerful tools that enable organizations to gain unprecedented insights into their supply chain networks, processes, and interactions.
Researchers have recently outlined seven key elements crucial for comprehending digital twins in SCOM:
1. Technology
2. People
3. Management
4. Organization
5. Scope
6. Task
7. Modeling
While these elements serve as the foundation for digital twins, the dynamic landscape of SCOM requires a multidisciplinary approach to harness this emerging technology's capabilities fully. Below, we will elaborate on some fundamental elements and highlight the value that diverse business perspectives bring to developing and applying digital twins for supply chain management.
Technology & Modeling
The value of digital twins is that they leverage real-time, comprehensive data to fully mirror the actual object or process. Therefore, true digital twins must integrate diverse information systems to aggregate signals and generate insights properly. Inputs usually include design (CAD/CAM), manufacturing (MES), relationship management (CRM), and/or process management (ERP) and consider factors such as decision-making competency and cognitive bias in human-AI interaction. Sophisticated modeling and analytics, supported by optimization and machine learning, then interpret this flood of data. The resulting 'digital companions' can simulate outcomes, identify inefficiencies, and bolster decision-making.
Scope & Task
Within any organization, there are likely many opportunities for improved efficiency and performance, each uniquely challenging or complex. In Supply Chain, we always aim to hone our inventory management, sourcing, production, warehousing, or logistics. Digital twins can support decision-making in critical SCOM responsibilities, from demand planning to predictive maintenance, by providing descriptive, predictive, and prescriptive analytics to guide future action.
Numerous studies have showcased the various applications of digital twin technology. For instance, it can be utilized to visualize supply chain dynamics and resilience impacts in automotive supply chains. Another study has shown that it can be used for optimized humanitarian logistics. In all these cases, digital twins have been applied to existing supply chain networks to visually represent their performance, predict their behaviors, and recommend strategies for success.
Value of a Multidisciplinary Approach
Though digital twins can be powerful tools, they must first be created, modeled, and polished before any benefit can be achieved. Increasingly, business operations are becoming less siloed, revealing the value of incorporating diverse skills and perspectives in our decision-making. So, too, do digital twins improve in performance and utility when varied disciplines inform their development and application.
Mechanical and industrial engineers drive the development of the digital twin product. Their expertise lies in crafting intricate models and simulations that faithfully represent physical objects and processes, laying the groundwork for effective digital twins.
Operations research professionals delve deep into modeling to optimize and refine the algorithms that power decision-making. Their knowledge of mathematics, optimization, and simulation techniques ensures the enterprise operates at peak efficiency, driving tangible improvements in SCOM.
Business management focuses on the practical implications and applications of digital twin analytics. By scrutinizing real-world scenarios and organizational dynamics, it reveals how digital twins can empower decision-makers and reshape operational strategies.
Organizational professionals are drawn to the transformative potential of digital twins on organizational structures and dynamics. Questions of hierarchy, communication channels, and decision-making processes uncover how digital twins can catalyze organizational change and foster collaboration.
Computer scientists and data engineers’ expertise in data management, system integration, and software development is pivotal for ensuring seamless interactions between digital twins and the broader SCOM ecosystem. From designing robust data pipelines to implementing cutting-edge algorithms, they pave the way for digital twins to thrive in a complex and interconnected world.
The collaboration of various experts in the field of SCOM digital twins is not just a simple partnership but a strategic necessity. Combining knowledge and skills from many disciplines can help us gain valuable insights, drive innovation, and create an effective and resilient supply chain.
As digital transformation continues to impact organizations, the significance of digital twins in SCOM will only increase. By harnessing this emerging technology, organizations can fully leverage the value of these “industry avatars” and realize a more efficient and robust supply chain in the future.
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